diff --git "a/data/resource_source_audit.csv" "b/data/resource_source_audit.csv" --- "a/data/resource_source_audit.csv" +++ "b/data/resource_source_audit.csv" @@ -1,431 +1,463 @@ row_id,title,url,url_kind,domain,audit_status,http_status,final_url,content_type,source_title,source_description,github_repo,github_stars,github_forks,github_open_issues,github_description,github_license,github_updated_at,arxiv_id,error,retrieved_at -ale-0001,Canonical Definition,DEFINITION.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/DEFINITION.md,,Canonical Definition,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0002,Loop Engineering Manifesto,MANIFESTO.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/MANIFESTO.md,,Loop Engineering Manifesto,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0003,Loop Engineering Taxonomy,TAXONOMY.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/TAXONOMY.md,,Loop Engineering Taxonomy,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0004,Loop Engineering Anti-Patterns,ANTI-PATTERNS.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/ANTI-PATTERNS.md,,Loop Engineering Anti-Patterns,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0005,Comparison Guide,COMPARISON.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/COMPARISON.md,,Comparison Guide,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0006,Sourced Signals And Quotes,QUOTES.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/QUOTES.md,,Sourced Signals And Quotes,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0007,Outreach Kit,meta/OUTREACH.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/meta/OUTREACH.md,,Outreach Kit,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0008,Loop Engineering,https://addyosmani.com/blog/loop-engineering/,external,addyosmani.com,ok,200,https://addyosmani.com/blog/loop-engineering/,text/html; charset=UTF-8,AddyOsmani.com - Loop Engineering,You don't really need to be good at prompting anymore. The thing to get good at is the loop that does the prompting for you. It's five building blocks plus s...,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0009,Loop Engineering,https://addyo.substack.com/p/loop-engineering,external,addyo.substack.com,ok,200,https://addyo.substack.com/p/loop-engineering,text/html; charset=utf-8,Loop Engineering - by Addy Osmani - Elevate,Loop engineering is replacing yourself as the person who prompts the agent.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0010,Peter Steinberger on designing loops,https://x.com/steipete/status/2063697162748260627,external,x.com,ok,200,https://x.com/steipete/status/2063697162748260627,text/html; charset=UTF-8,"Peter Steinberger šŸ¦ž on X: ""Hereā€™s your monthly reminder that you shouldnā€™t be prompting coding agents anymore. You should be designing loops that prompt your agents."" / X",Hereā€™s your monthly reminder that you shouldnā€™t be prompting coding agents anymore. You should be designing loops that prompt your agents.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0011,Boris Cherny: five tips for running Opus autonomously for hours or days,https://x.com/bcherny/status/2063792263067754658,external,x.com,ok,200,https://x.com/bcherny/status/2063792263067754658,text/html; charset=UTF-8,"Boris Cherny on X: ""Seeing a number of benchmarks showing Opus is the best model for long-running work. Five tips for running Opus autonomously for hours/days: 1. Use auto mode for permissions, so Claude doesnā€™t ask for approval 2. Use dynamic workflows, to have Claude orchestrate"" / X","Seeing a number of benchmarks showing Opus is the best model for long-running work. Five tips for running Opus autonomously for hours/days: 1. Use auto mode for permissions, so Claude doesnā€™t ask for approval 2. Use dynamic workflows, to have Claude orchestrate",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0012,Loop Engineering,https://cobusgreyling.substack.com/p/loop-engineering,external,cobusgreyling.substack.com,ok,200,https://cobusgreyling.substack.com/p/loop-engineering,text/html; charset=utf-8,Loop Engineering,The core of Loop Engineering,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0013,Loop Engineering: The Guide for AI Agents,https://lushbinary.com/blog/loop-engineering-ai-coding-agents-guide/,external,lushbinary.com,ok,200,https://lushbinary.com/blog/loop-engineering-ai-coding-agents-guide/,text/html,Loop Engineering: The Guide for AI Agents | Lushbinary,"Loop engineering means designing the systems that prompt your AI agents, not prompting by hand. The 5 building blocks, Claude Code & Codex commands, and risks. Updated June 2026.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0014,Stop Prompting. Design the Loop.,https://www.pulumi.com/blog/stop-prompting-design-the-loop/,external,www.pulumi.com,ok,200,https://www.pulumi.com/blog/stop-prompting-design-the-loop/,text/html; charset=utf-8,Stop Prompting. Design the Loop. | Pulumi Blog,"The unit of work moved from the prompt to the loop. The five pieces of loop engineering, the memory that makes it compound, and what it won't do for you.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0015,"Writing Loops, Not Prompts, Explained",https://rico.codes/loops-not-prompts,external,rico.codes,ok,200,https://rico.codes/loops-not-prompts,text/html; charset=utf-8,"Writing Loops, Not Prompts, Explained | rico.codes","Loop engineering is not about abandoning prompts. It is about moving repeated steering work into verifiable systems so attention can stay on judgment, review, and taste.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0016,Loop Engineering: A Guide for Engineers and Practitioners,https://medium.com/@adnanmasood/loop-engineering-a-guide-for-engineers-and-practitioners-893bb65ea943,external,medium.com,restricted,403,https://medium.com/@adnanmasood/loop-engineering-a-guide-for-engineers-and-practitioners-893bb65ea943,text/html; charset=UTF-8,,,,,,,,,,,restricted_or_rate_limited,2026-07-10T17:33:26+00:00 -ale-0017,"Loop Engineering: When Generation Gets Cheap, Judgment Gets Expensive",https://sderosiaux.substack.com/p/loop-engineering-cheap-generation,external,sderosiaux.substack.com,ok,200,https://sderosiaux.substack.com/p/loop-engineering-cheap-generation,text/html; charset=utf-8,"Loop Engineering: When Generation Gets Cheap, Judgment Gets Expensive","Agentic loops make code, plans, and PRs abundant. The scarce part is knowing what is right.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0018,Andrew Ng on Loop Engineering and the Three Loops of AI-Native Product Development,https://x.com/AndrewYNg/status/2071988145667928442,external,x.com,ok,200,https://x.com/AndrewYNg/status/2071988145667928442,text/html; charset=UTF-8,"Andrew Ng on X: ""ā€œLoop engineeringā€ is a hot buzzphrase after mentions of it by Boris Cherny (Claude Codeā€™s creator) and Peter Steinberger (OpenClaw's creator) went viral on social media. Loops are now a key part of how we get AI agents to iterate at length to build software. In this letter, Iā€™d https://t.co/bhuRw8lrFC"" / X","ā€œLoop engineeringā€ is a hot buzzphrase after mentions of it by Boris Cherny (Claude Codeā€™s creator) and Peter Steinberger (OpenClaw's creator) went viral on social media. Loops are now a key part of how we get AI agents to iterate at length to build software. In this letter, Iā€™d",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0019,From Prompting Agents to Loop Engineering,https://x.com/omarsar0/status/2068008743153832264,external,x.com,ok,200,https://x.com/omarsar0/status/2068008743153832264,text/html; charset=UTF-8,"elvis on X: ""https://t.co/d8LgEwfVH6"" / X",https://t.co/d8LgEwfVH6,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0020,I Now Just Write Loops To Prompt Claude Code: Claude Code Creator Boris Cherny,https://officechai.com/ai/i-now-just-write-loops-to-prompt-claude-code-claude-code-creator-boris-cherny/,external,officechai.com,ok,200,https://officechai.com/ai/i-now-just-write-loops-to-prompt-claude-code-claude-code-creator-boris-cherny/,text/html; charset=UTF-8,I Now Just Write Loops To Prompt Claude Code: Claude Code Creator Boris Cherny,"The definition of top tier coding is changing month-on-month in the AI era. Boris Cherny, the creator of Claude Code at Anthropic, has...",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0021,My Lord! AI Programming Undergoes Another Major Shift,https://eu.36kr.com/en/p/3844224911346184,external,eu.36kr.com,ok,200,https://eu.36kr.com/en/p/3844224911346184,text/html; charset=utf-8,My Lord! AI Programming Undergoes Another Major Shift: Claude Code Father & Lobster Founder Endorse New Paradigm - Could It Kill Prompt Engineering?,Stop writing prompts for programming agents now.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0022,The Anthropic leader who built Claude Code ditched prompting - now he writes loops,https://thenewstack.io/loop-engineering/,external,thenewstack.io,ok,200,https://thenewstack.io/loop-engineering/,text/html; charset=UTF-8,The Anthropic leader who built Claude Code says he ditched prompting ā€” now he just writes loops. - The New Stack,Loop engineering ā€” the practice of designing automated agent workflows instead of prompting manually ā€” is reshaping how developers use Claude Code and OpenAI Codex in 2026.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0023,Engineering for Agents That Never Sleep,https://nader.substack.com/p/engineering-for-agents-that-never,external,nader.substack.com,ok,200,https://nader.substack.com/p/engineering-for-agents-that-never,text/html; charset=utf-8,Engineering for Agents That Never Sleep - by Nader Dabit,Originally posted on X.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0024,PR babysitter,patterns/pr-babysitter.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/pr-babysitter.md,,PR babysitter,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0025,CI repair loop,patterns/ci-repair-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/ci-repair-loop.md,,CI repair loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0026,Docs drift collector,patterns/docs-drift-collector.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/docs-drift-collector.md,,Docs drift collector,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0027,Deploy verifier,patterns/deploy-verifier.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/deploy-verifier.md,,Deploy verifier,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0028,Feedback clusterer,patterns/feedback-clusterer.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/feedback-clusterer.md,,Feedback clusterer,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0029,Dependency triage loop,patterns/dependency-triage-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/dependency-triage-loop.md,,Dependency triage loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0030,Evaluation regression loop,patterns/evaluation-regression-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/evaluation-regression-loop.md,,Evaluation regression loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0031,Security review loop,patterns/security-review-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/security-review-loop.md,,Security review loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0032,Cost-control loop,patterns/cost-control-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/cost-control-loop.md,,Cost-control loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0033,Bug hunting loop,patterns/bug-hunting-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/bug-hunting-loop.md,,Bug hunting loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0034,Enterprise approval loop,patterns/enterprise-approval-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/enterprise-approval-loop.md,,Enterprise approval loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0035,Incident response loop,patterns/incident-response-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/incident-response-loop.md,,Incident response loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0036,Data-quality loop,patterns/data-quality-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/data-quality-loop.md,,Data-quality loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0037,Release-note loop,patterns/release-note-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/release-note-loop.md,,Release-note loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0038,Model-routing loop,patterns/model-routing-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/model-routing-loop.md,,Model-routing loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0039,Automations - Codex app,https://developers.openai.com/codex/app/automations,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/automations?surface=app,text/html; charset=utf-8,Scheduled tasks | ChatGPT Learn,Schedule recurring tasks in ChatGPT,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0040,Follow a goal - Codex use cases,https://developers.openai.com/codex/use-cases/follow-goals,external,developers.openai.com,ok,200,https://learn.chatgpt.com/use-cases/follow-goals,text/html; charset=utf-8,Follow a goal | ChatGPT use cases,Use `/goal` when a task needs Codex to keep working across turns toward a verifiable stopping condition.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0041,Worktrees - Codex app,https://developers.openai.com/codex/app/worktrees,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/environments/git-worktrees,text/html; charset=utf-8,Worktrees | ChatGPT Learn,Use Git worktrees in Codex in the ChatGPT desktop app to run tasks in parallel,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0042,Prompting - Codex,https://developers.openai.com/codex/prompting,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/prompting,text/html; charset=utf-8,Prompting | ChatGPT Learn,"Write useful prompts for Chat, ChatGPT Work, and Codex",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0043,Customization - Codex,https://developers.openai.com/codex/concepts/customization,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/customization/overview,text/html; charset=utf-8,Customization | ChatGPT Learn,"How to customize Codex with project guidance, skills, MCP, and subagents",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0044,Agent Skills - Codex,https://developers.openai.com/codex/skills,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/build-skills,text/html; charset=utf-8,Build skills | ChatGPT Learn,Give Codex new capabilities and expertise,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0045,Plugins - Codex,https://developers.openai.com/codex/plugins,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/plugins,text/html; charset=utf-8,Plugins | ChatGPT Learn,"Browse, install, and use plugins in ChatGPT and Codex clients",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0046,dotskills,https://github.com/vincentkoc/dotskills,external,github.com,ok,200,https://github.com/vincentkoc/dotskills,text/html; charset=utf-8,"GitHub - vincentkoc/dotskills: šŸ™ A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns. Ā· GitHub","šŸ™ A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns. - vincentkoc/dotskills",vincentkoc/dotskills,97,9,8,"šŸ™ A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns.",MIT,2026-07-09T13:12:22Z,,,2026-07-10T17:33:26+00:00 -ale-0047,Slash commands in Codex CLI,https://developers.openai.com/codex/cli/slash-commands,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/developer-commands?surface=cli,text/html; charset=utf-8,Developer commands | ChatGPT Learn,Reference for commands and slash commands in Codex developer surfaces,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0048,Autonomous Loops,https://claudecodeguide.dev/docs/patterns/autonomous-loops,external,claudecodeguide.dev,ok,200,https://claudecodeguide.dev/docs/patterns/autonomous-loops,text/html; charset=utf-8,Claude Code Autonomous Loops | Claude Code Guide,"Point Claude Code at a problem, walk away, come back to a green build. Task templates, kill switches, and why boundaries matter more than anything else.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0049,Claude Code Glossary,https://code.claude.com/docs/en/glossary.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/glossary.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0050,Keep Claude working toward a goal,https://code.claude.com/docs/en/goal,external,code.claude.com,ok,200,https://code.claude.com/docs/en/goal,text/html; charset=utf-8,Keep Claude working toward a goal - Claude Code Docs,Set a completion condition with /goal and Claude keeps working across turns until the condition is met.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0051,Run prompts on a schedule,https://code.claude.com/docs/en/scheduled-tasks,external,code.claude.com,ok,200,https://code.claude.com/docs/en/scheduled-tasks,text/html; charset=utf-8,Run prompts on a schedule - Claude Code Docs,"Use /loop and the cron scheduling tools to run prompts repeatedly, poll for status, or set one-time reminders within a Claude Code session.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0052,Automate work with routines,https://code.claude.com/docs/en/routines,external,code.claude.com,ok,200,https://code.claude.com/docs/en/routines,text/html; charset=utf-8,Automate work with routines - Claude Code Docs,"Put Claude Code on autopilot. Define routines that run on a schedule, trigger on API calls, or react to GitHub events from Anthropic-managed cloud infrastructure.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0053,Desktop scheduled tasks,https://code.claude.com/docs/en/desktop-scheduled-tasks,external,code.claude.com,ok,200,https://code.claude.com/docs/en/desktop-scheduled-tasks,text/html; charset=utf-8,Schedule recurring tasks in Claude Code Desktop - Claude Code Docs,"Set up scheduled tasks in Claude Code Desktop to run Claude automatically on a recurring basis for daily code reviews, dependency audits, or morning briefings.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0054,Run parallel sessions with worktrees,https://code.claude.com/docs/en/worktrees,external,code.claude.com,ok,200,https://code.claude.com/docs/en/worktrees,text/html; charset=utf-8,Run parallel sessions with worktrees - Claude Code Docs,"Isolate parallel Claude Code sessions in separate git worktrees so changes don't collide. Covers the --worktree flag, subagent isolation, .worktreeinclude, cleanup, and non-git VCS hooks.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0055,Automate actions with hooks,https://code.claude.com/docs/en/hooks-guide,external,code.claude.com,ok,200,https://code.claude.com/docs/en/hooks-guide,text/html; charset=utf-8,Automate actions with hooks - Claude Code Docs,"Run shell commands automatically when Claude Code edits files, finishes tasks, or needs input. Format code, send notifications, validate commands, and enforce project rules.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0056,Hooks reference,https://code.claude.com/docs/en/hooks.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/hooks.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0057,Common workflows - Claude Code,https://code.claude.com/docs/en/common-workflows,external,code.claude.com,ok,200,https://code.claude.com/docs/en/common-workflows,text/html; charset=utf-8,Common workflows - Claude Code Docs,"Step-by-step guides for exploring codebases, fixing bugs, refactoring, testing, and other everyday tasks with Claude Code.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0058,Manage multiple agents with agent view,https://code.claude.com/docs/en/agent-view.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/agent-view.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0059,Run agents in parallel,https://code.claude.com/docs/en/agents.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/agents.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0060,Orchestrate subagents at scale with dynamic workflows,https://code.claude.com/docs/en/workflows,external,code.claude.com,ok,200,https://code.claude.com/docs/en/workflows,text/html; charset=utf-8,Orchestrate subagents at scale with dynamic workflows - Claude Code Docs,"Dynamic workflows orchestrate many subagents from a script Claude writes and you can rerun. Use them for codebase audits, large migrations, and cross-checked research.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0061,Create plugins,https://code.claude.com/docs/en/plugins,external,code.claude.com,ok,200,https://code.claude.com/docs/en/plugins,text/html; charset=utf-8,Create plugins - Claude Code Docs,"Create custom plugins to extend Claude Code with skills, agents, hooks, and MCP servers.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0062,Model Context Protocol,https://modelcontextprotocol.io/docs/getting-started/intro,external,modelcontextprotocol.io,ok,200,https://modelcontextprotocol.io/docs/getting-started/intro,text/html; charset=utf-8,What is the Model Context Protocol (MCP)? - Model Context Protocol,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0063,Allowing GitHub Copilot CLI to work autonomously,https://docs.github.com/en/copilot/concepts/agents/copilot-cli/autopilot,external,docs.github.com,ok,200,https://docs.github.com/en/copilot/concepts/agents/copilot-cli/autopilot,text/html; charset=utf-8,Allowing GitHub Copilot CLI to work autonomously - GitHub Docs,"The CLI's autopilot mode lets Copilot CLI work autonomously on a task, carrying out multiple steps until the task is complete.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0064,opencode-scheduler,https://github.com/different-ai/opencode-scheduler,external,github.com,ok,200,https://github.com/different-ai/opencode-scheduler,text/html; charset=utf-8,GitHub - different-ai/opencode-scheduler: OpenCode plugin for scheduling recurring jobs using launchd (Mac) or systemd (Linux) Ā· GitHub,OpenCode plugin for scheduling recurring jobs using launchd (Mac) or systemd (Linux) - different-ai/opencode-scheduler,different-ai/opencode-scheduler,431,29,14,OpenCode plugin for scheduling recurring jobs using launchd (Mac) or systemd (Linux),MIT,2026-07-10T17:19:10Z,,,2026-07-10T17:33:26+00:00 -ale-0065,Agent-Loop-Skills,https://github.com/gaasher/Agent-Loop-Skills,external,github.com,ok,200,https://github.com/gaasher/Agent-Loop-Skills,text/html; charset=utf-8,"GitHub - gaasher/Agent-Loop-Skills: Loop until it's better ā€” drop-in agentic loops (autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, red-teaming) as open-standard Agent Skills. Verification-gated; native on Claude Code, portable across Codex, Cursor & other Skills hosts. Ā· GitHub","Loop until it's better ā€” drop-in agentic loops (autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, red-teaming) as open-standard Agent Skills. Verification-gated; native on Claude Code, portable across Codex, Cursor & other Skills hosts. - gaasher/Agent-Loop-Skills",gaasher/Agent-Loop-Skills,126,14,1,"Loop until it's better ā€” drop-in agentic loops (autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, red-teaming) as open-standard Agent Skills. Verification-gated; native on Claude Code, portable across Codex, Cursor & other Skills hosts.",MIT,2026-07-09T06:21:24Z,,,2026-07-10T17:33:26+00:00 -ale-0066,launch-your-agent,https://github.com/anthropics/launch-your-agent,external,github.com,ok,200,https://github.com/anthropics/launch-your-agent,text/html; charset=utf-8,"GitHub - anthropics/launch-your-agent: Claude Code skills that take a founder from idea to a live Claude Managed Agent: interview, scope a v0, launch in their own account, grade it, iterate, and schedule it Ā· GitHub","Claude Code skills that take a founder from idea to a live Claude Managed Agent: interview, scope a v0, launch in their own account, grade it, iterate, and schedule it - anthropics/launch-your-agent",anthropics/launch-your-agent,772,143,2,"Claude Code skills that take a founder from idea to a live Claude Managed Agent: interview, scope a v0, launch in their own account, grade it, iterate, and schedule it",Apache-2.0,2026-07-10T13:42:33Z,,,2026-07-10T17:33:26+00:00 -ale-0067,Run long horizon tasks with Codex,https://developers.openai.com/blog/run-long-horizon-tasks-with-codex,external,developers.openai.com,ok,200,https://developers.openai.com/blog/run-long-horizon-tasks-with-codex,text/html; charset=utf-8,Run long horizon tasks with Codex | OpenAI Developers,OpenAI Developer Blog,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0068,Best practices - Codex,https://developers.openai.com/codex/learn/best-practices,external,developers.openai.com,ok,200,https://learn.chatgpt.com/guides/best-practices,text/html; charset=utf-8,Best practices | ChatGPT Learn,Getting started with Codex and proven practices for better results,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0069,Agents SDK,https://developers.openai.com/api/docs/guides/agents,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents,text/html; charset=utf-8,Agents SDK | OpenAI API,Learn how the OpenAI Agents SDK fits together and which docs to read next.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0070,Agents - OpenAI Agents SDK,https://openai.github.io/openai-agents-python/agents/,external,openai.github.io,ok,200,https://openai.github.io/openai-agents-python/agents/,text/html; charset=utf-8,Agents - OpenAI Agents SDK,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0071,Running agents,https://developers.openai.com/api/docs/guides/agents/running-agents,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents/running-agents,text/html; charset=utf-8,Running agents | OpenAI API,"Learn how to run agents, stream output, and choose the right conversation-state strategy in the OpenAI Agents SDK.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0072,Integrations and observability,https://developers.openai.com/api/docs/guides/agents/integrations-observability,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents/integrations-observability,text/html; charset=utf-8,Integrations and observability | OpenAI API,Learn how to integrate MCP into Agents SDK workflows and how to trace and debug runs.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0073,Sandbox Agents,https://developers.openai.com/api/docs/guides/agents/sandboxes,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents/sandboxes,text/html; charset=utf-8,Sandbox Agents | OpenAI API,"Learn how sandboxes fit into Agents SDK workflows, when to use them, and how orchestration stays separate from execution.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0074,Guardrails and human review,https://developers.openai.com/api/docs/guides/agents/guardrails-approvals,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents/guardrails-approvals,text/html; charset=utf-8,Guardrails and human review | OpenAI API,"Learn how to use guardrails and human review in the OpenAI Agents SDK for safer, more controlled workflows.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0075,Building agents with the Claude Agent SDK,https://code.claude.com/docs/en/agent-sdk/overview.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/agent-sdk/overview.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0076,How the agent loop works,https://code.claude.com/docs/en/agent-sdk/agent-loop,external,code.claude.com,ok,200,https://code.claude.com/docs/en/agent-sdk/agent-loop,text/html; charset=utf-8,How the agent loop works - Claude Code Docs,"Understand the message lifecycle, tool execution, context window, and architecture that power your SDK agents.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0077,Extend Claude with skills,https://code.claude.com/docs/en/skills,external,code.claude.com,ok,200,https://code.claude.com/docs/en/skills,text/html; charset=utf-8,Extend Claude with skills - Claude Code Docs,"Create, manage, and share skills to extend Claude's capabilities in Claude Code. Includes custom commands and bundled skills.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0078,Create custom subagents,https://code.claude.com/docs/en/sub-agents,external,code.claude.com,ok,200,https://code.claude.com/docs/en/sub-agents,text/html; charset=utf-8,Create custom subagents - Claude Code Docs,Create and use specialized AI subagents in Claude Code for task-specific workflows and improved context management.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0079,GitHub Agentic Workflows,https://github.github.com/gh-aw/,external,github.github.com,ok,200,https://github.github.com/gh-aw/,text/html; charset=utf-8,Home | GitHub Agentic Workflows,Write repository automation workflows in natural language using markdown files and run them as GitHub Actions. Use AI agents with strong guardrails to automate your development workflow.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0080,GitHub Agentic Workflows technical preview,https://github.blog/changelog/2026-02-13-github-agentic-workflows-are-now-in-technical-preview/,external,github.blog,ok,200,https://github.blog/changelog/2026-02-13-github-agentic-workflows-are-now-in-technical-preview/,text/html; charset=UTF-8,GitHub Agentic Workflows are now in technical preview - GitHub Changelog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"GitHub Agentic Workflows let you automate repository tasks using AI agents that run within GitHub Actions. Write workflows in plain Markdown instead of complex YAML, and let AI handle intelligentā€¦",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0081,Continuous AI,https://githubnext.com/projects/continuous-ai/,external,githubnext.com,ok,200,https://githubnext.com/projects/continuous-ai/,text/html; charset=utf-8,Continuous AI,Exploring LLM-powered automation in platform-based software collaboration,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0082,Automate repository tasks with GitHub Agentic Workflows,https://github.blog/ai-and-ml/automate-repository-tasks-with-github-agentic-workflows/,external,github.blog,ok,200,https://github.blog/ai-and-ml/automate-repository-tasks-with-github-agentic-workflows/,text/html; charset=UTF-8,Automate repository tasks with GitHub Agentic Workflows - The GitHub Blog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"Build automations using coding agents in GitHub Actions to handle triage, documentation, code quality, and more.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0083,Continuous AI in practice: What developers can automate today with agentic CI,https://github.blog/ai-and-ml/generative-ai/continuous-ai-in-practice-what-developers-can-automate-today-with-agentic-ci/,external,github.blog,ok,200,https://github.blog/ai-and-ml/generative-ai/continuous-ai-in-practice-what-developers-can-automate-today-with-agentic-ci/,text/html; charset=UTF-8,Continuous AI in practice: What developers can automate today with agentic CI - The GitHub Blog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,Think of Continuous AI as background agents that operate in your repository for tasks that require reasoning.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0084,About GitHub Copilot coding agent,https://docs.github.com/en/copilot/concepts/agents/coding-agent/about-coding-agent,external,docs.github.com,ok,200,https://docs.github.com/en/copilot/concepts/agents/cloud-agent/about-cloud-agent,text/html; charset=utf-8,About GitHub Copilot cloud agent - GitHub Docs,"Copilot can research a repository, create an implementation plan, and make code changes on a branch. You can review the diff, iterate, and create a pull request when you're ready.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0085,GitHub Copilot: Meet the new coding agent,https://github.blog/news-insights/product-news/github-copilot-meet-the-new-coding-agent/,external,github.blog,ok,200,https://github.blog/news-insights/product-news/github-copilot-meet-the-new-coding-agent/,text/html; charset=UTF-8,GitHub Copilot: Meet the new coding agent - The GitHub Blog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"GitHub Copilot has a new feature: a coding agent that can implement a task or issue, run in the background with GitHub Actions, and more.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0086,Jules,https://jules.google/docs,external,jules.google,ok,200,https://jules.google/docs,text/html,Getting started | Jules,Set up and run your first task with Jules,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0087,Cursor cloud agents,https://cursor.com/docs/cloud-agent,external,cursor.com,ok,200,https://cursor.com/docs/cloud-agent,text/html; charset=utf-8,Cloud Agents | Cursor Docs,Run Agent in the cloud for continuous coding assistance.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0088,Devin Docs,https://docs.devin.ai/get-started/devin-intro,external,docs.devin.ai,ok,200,https://docs.devin.ai/get-started/devin-intro,text/html; charset=utf-8,Introducing Devin - Devin Docs,"Devin is the AI software engineer, built to help ambitious engineering teams crush their backlogs.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0089,Writing effective tools for AI agents,https://www.anthropic.com/engineering/writing-tools-for-agents,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/writing-tools-for-agents,text/html; charset=utf-8,Writing effective tools for AI agentsā€”using AI agents \ Anthropic,Writing effective tools for AI agentsā€”using AI agents,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0090,Introducing advanced tool use on the Claude Developer Platform,https://www.anthropic.com/engineering/advanced-tool-use?e45d281a_page=3,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/advanced-tool-use?e45d281a_page=3,text/html; charset=utf-8,Introducing advanced tool use on the Claude Developer Platform \ Anthropic,"Claude can now discover, learn, and execute tools dynamically to enable agents that take action in the real world. Hereā€™s how.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0091,Effective harnesses for long-running agents,https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents,text/html; charset=utf-8,Effective harnesses for long-running agents \ Anthropic,"Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0092,Claude Code best practices,https://code.claude.com/docs/en/best-practices,external,code.claude.com,ok,200,https://code.claude.com/docs/en/best-practices,text/html; charset=utf-8,Best practices for Claude Code - Claude Code Docs,"Tips and patterns for getting the most out of Claude Code, from configuring your environment to scaling across parallel sessions.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0093,Cursor 3.8: Improvements to Cursor Automations,https://cursor.com/changelog/06-18-26,external,cursor.com,ok,200,https://cursor.com/changelog/06-18-26,text/html; charset=utf-8,Improvements to Cursor Automations Ā· Cursor,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0094,GitHub Copilot for Jira Is Now Generally Available,https://github.blog/changelog/2026-06-25-github-copilot-for-jira-is-now-generally-available/,external,github.blog,ok,200,https://github.blog/changelog/2026-06-25-github-copilot-for-jira-is-now-generally-available/,text/html; charset=UTF-8,GitHub Copilot for Jira is now generally available - GitHub Changelog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"GitHub Copilot for Jira is now generally available. Since launching the public preview in March 2026, we have shipped a series of enhancements based on your feedback, including model selection,ā€¦",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0095,Claude Managed Agents: Scheduled Deployments and Vaults,https://claude.com/blog/whats-new-in-claude-managed-agents,external,claude.com,ok,200,https://claude.com/blog/whats-new-in-claude-managed-agents,text/html; charset=utf-8,New in Claude Managed Agents: run agents on a schedule and store environment variables in vaults | Claude by Anthropic,Claude Managed Agents can now run on a schedule and securely access CLI tools and other authenticated services.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0096,Copilot Agent Session Streaming (Public Preview),https://github.blog/changelog/2026-07-02-copilot-agent-session-streaming-is-now-in-public-preview/,external,github.blog,ok,200,https://github.blog/changelog/2026-07-02-copilot-agent-session-streaming-is-now-in-public-preview/,text/html; charset=UTF-8,Copilot agent session streaming is now in public preview - GitHub Changelog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"GitHub Enterprise Cloud customers with enterprise managed users can now access GitHub Copilot agent session data across all Copilot clients, including: Cloud agents operating on github.com and data resident deploymentsā€¦",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0097,Expanding Our Long-Running Agents Research Preview,https://cursor.com/blog/long-running-agents,external,cursor.com,ok,200,https://cursor.com/blog/long-running-agents,text/html; charset=utf-8,Expanding our long-running agents research preview Ā· Cursor,"Long-running agents are now available in the Cursor web app for Ultra, Teams, and Enterprise users.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0098,ChatGPT Work and the Codex Desktop App,https://openai.com/index/chatgpt-for-your-most-ambitious-work/,external,openai.com,ok,200,https://openai.com/index/chatgpt-for-your-most-ambitious-work/,text/html; charset=utf-8,ChatGPT is now a partner for your most ambitious work | OpenAI,"ChatGPT Work is an agent that can take action across your apps and files, stay with a project for hours if needed, and turn a goal into finished work.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0099,Getting Started with Loops,https://claude.com/blog/getting-started-with-loops,external,claude.com,ok,200,https://claude.com/blog/getting-started-with-loops,text/html; charset=utf-8,Loop engineering: Getting started with loops | Claude by Anthropic,"Loop engineering with Claude Code: design turn-based, goal, time, and proactive agent loopsā€”including Ralph loops and /loopā€”that run to a stop condition.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0100,ReAct: Synergizing Reasoning and Acting in Language Models,https://arxiv.org/abs/2210.03629,external,arxiv.org,ok,200,https://arxiv.org/abs/2210.03629,text/html; charset=utf-8,[2210.03629] ReAct: Synergizing Reasoning and Acting in Language Models,Abstract page for arXiv paper 2210.03629: ReAct: Synergizing Reasoning and Acting in Language Models,,,,,,,,2210.03629,,2026-07-10T17:33:26+00:00 -ale-0101,Reflexion: Language Agents with Verbal Reinforcement Learning,https://arxiv.org/abs/2303.11366,external,arxiv.org,ok,200,https://arxiv.org/abs/2303.11366,text/html; charset=utf-8,[2303.11366] Reflexion: Language Agents with Verbal Reinforcement Learning,Abstract page for arXiv paper 2303.11366: Reflexion: Language Agents with Verbal Reinforcement Learning,,,,,,,,2303.11366,,2026-07-10T17:33:26+00:00 -ale-0102,Self-Refine: Iterative Refinement with Self-Feedback,https://arxiv.org/abs/2303.17651,external,arxiv.org,ok,200,https://arxiv.org/abs/2303.17651,text/html; charset=utf-8,[2303.17651] Self-Refine: Iterative Refinement with Self-Feedback,Abstract page for arXiv paper 2303.17651: Self-Refine: Iterative Refinement with Self-Feedback,,,,,,,,2303.17651,,2026-07-10T17:33:26+00:00 -ale-0103,CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing,https://arxiv.org/abs/2305.11738,external,arxiv.org,ok,200,https://arxiv.org/abs/2305.11738,text/html; charset=utf-8,[2305.11738] CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing,Abstract page for arXiv paper 2305.11738: CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing,,,,,,,,2305.11738,,2026-07-10T17:33:26+00:00 -ale-0104,Tree of Thoughts,https://arxiv.org/abs/2305.10601,external,arxiv.org,ok,200,https://arxiv.org/abs/2305.10601,text/html; charset=utf-8,[2305.10601] Tree of Thoughts: Deliberate Problem Solving with Large Language Models,Abstract page for arXiv paper 2305.10601: Tree of Thoughts: Deliberate Problem Solving with Large Language Models,,,,,,,,2305.10601,,2026-07-10T17:33:26+00:00 -ale-0105,Graph of Thoughts,https://arxiv.org/abs/2308.09687,external,arxiv.org,ok,200,https://arxiv.org/abs/2308.09687,text/html; charset=utf-8,[2308.09687] Graph of Thoughts: Solving Elaborate Problems with Large Language Models,Abstract page for arXiv paper 2308.09687: Graph of Thoughts: Solving Elaborate Problems with Large Language Models,,,,,,,,2308.09687,,2026-07-10T17:33:26+00:00 -ale-0106,Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models,https://arxiv.org/abs/2310.04406,external,arxiv.org,ok,200,https://arxiv.org/abs/2310.04406,text/html; charset=utf-8,[2310.04406] Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models,Abstract page for arXiv paper 2310.04406: Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models,,,,,,,,2310.04406,,2026-07-10T17:33:26+00:00 -ale-0107,Voyager: An Open-Ended Embodied Agent with Large Language Models,https://arxiv.org/abs/2305.16291,external,arxiv.org,ok,200,https://arxiv.org/abs/2305.16291,text/html; charset=utf-8,[2305.16291] Voyager: An Open-Ended Embodied Agent with Large Language Models,Abstract page for arXiv paper 2305.16291: Voyager: An Open-Ended Embodied Agent with Large Language Models,,,,,,,,2305.16291,,2026-07-10T17:33:26+00:00 -ale-0108,Generative Agents: Interactive Simulacra of Human Behavior,https://arxiv.org/abs/2304.03442,external,arxiv.org,ok,200,https://arxiv.org/abs/2304.03442,text/html; charset=utf-8,[2304.03442] Generative Agents: Interactive Simulacra of Human Behavior,Abstract page for arXiv paper 2304.03442: Generative Agents: Interactive Simulacra of Human Behavior,,,,,,,,2304.03442,,2026-07-10T17:33:26+00:00 -ale-0109,Measuring AI Ability to Complete Long Software Tasks,https://arxiv.org/abs/2503.14499,external,arxiv.org,ok,200,https://arxiv.org/abs/2503.14499,text/html; charset=utf-8,[2503.14499] Measuring AI Ability to Complete Long Software Tasks,Abstract page for arXiv paper 2503.14499: Measuring AI Ability to Complete Long Software Tasks,,,,,,,,2503.14499,,2026-07-10T17:33:26+00:00 -ale-0110,Measuring AI Ability to Complete Long Tasks,https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/,external,metr.org,ok,200,https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/,text/html; charset=UTF-8,Measuring AI Ability to Complete Long Tasks - METR Substack twitter Bluesky,"We propose measuring AI performance in terms of the *length* of tasks AI agents can complete. We show that this metric has been consistently exponentially increasing over the past 6 years, with a doubling time of around 7 months. Extrapolating this trend predicts that, in under a decade, we will see AI agents that can independently complete a large fraction of software tasks that currently take humans days or weeks.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0111,Reflection-Driven Control for Trustworthy Code Agents,https://arxiv.org/abs/2512.21354,external,arxiv.org,ok,200,https://arxiv.org/abs/2512.21354,text/html; charset=utf-8,[2512.21354] Reflection-Driven Control for Trustworthy Code Agents,Abstract page for arXiv paper 2512.21354: Reflection-Driven Control for Trustworthy Code Agents,,,,,,,,2512.21354,,2026-07-10T17:33:26+00:00 -ale-0112,Hyperagents,https://arxiv.org/abs/2603.19461,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.19461,text/html; charset=utf-8,[2603.19461] Hyperagents,Abstract page for arXiv paper 2603.19461: Hyperagents,,,,,,,,2603.19461,,2026-07-10T17:33:26+00:00 -ale-0113,PARC: An Autonomous Self-Reflective Coding Agent for Robust Execution of Long-Horizon Tasks,https://arxiv.org/abs/2512.03549,external,arxiv.org,ok,200,https://arxiv.org/abs/2512.03549,text/html; charset=utf-8,[2512.03549] PARC: An Autonomous Self-Reflective Coding Agent for Robust Execution of Long-Horizon Tasks,Abstract page for arXiv paper 2512.03549: PARC: An Autonomous Self-Reflective Coding Agent for Robust Execution of Long-Horizon Tasks,,,,,,,,2512.03549,,2026-07-10T17:33:26+00:00 -ale-0114,When the Specification Emerges: Benchmarking Faithfulness Loss in Long-Horizon Coding Agents,https://arxiv.org/abs/2603.17104,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.17104,text/html; charset=utf-8,[2603.17104] When the Specification Emerges: Benchmarking Faithfulness Loss in Long-Horizon Coding Agents,Abstract page for arXiv paper 2603.17104: When the Specification Emerges: Benchmarking Faithfulness Loss in Long-Horizon Coding Agents,,,,,,,,2603.17104,,2026-07-10T17:33:26+00:00 -ale-0115,Reflexion code,https://github.com/noahshinn/reflexion,external,github.com,ok,200,https://github.com/noahshinn/reflexion,text/html; charset=utf-8,GitHub - noahshinn/reflexion: [NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning Ā· GitHub,[NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning - noahshinn/reflexion,noahshinn/reflexion,3200,310,23,[NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning,MIT,2026-07-10T13:42:15Z,,,2026-07-10T17:33:26+00:00 -ale-0116,Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting,https://arxiv.org/abs/2607.00038,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.00038,text/html; charset=utf-8,[2607.00038] Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting,Abstract page for arXiv paper 2607.00038: Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting,,,,,,,,2607.00038,,2026-07-10T17:33:26+00:00 -ale-0117,From Question Answering to Task Completion: A Survey on Agent System and Harness Design,https://arxiv.org/abs/2606.20683,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.20683,text/html; charset=utf-8,[2606.20683] From Question Answering to Task Completion: A Survey on Agent System and Harness Design,Abstract page for arXiv paper 2606.20683: From Question Answering to Task Completion: A Survey on Agent System and Harness Design,,,,,,,,2606.20683,,2026-07-10T17:33:26+00:00 -ale-0118,MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems,https://arxiv.org/abs/2605.22794,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.22794,text/html; charset=utf-8,[2605.22794] MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems,Abstract page for arXiv paper 2605.22794: MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems,,,,,,,,2605.22794,,2026-07-10T17:33:26+00:00 -ale-0119,METR Time Horizon 1.1,https://metr.org/blog/2026-1-29-time-horizon-1-1/,external,metr.org,ok,200,https://metr.org/blog/2026-1-29-time-horizon-1-1/,text/html; charset=UTF-8,Time Horizon 1.1 - METR Substack twitter Bluesky,"Weā€™re releasing a new version of our time horizon estimates (TH1.1), using more tasks and a new eval infrastructure.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0120,MetaSkill-Evolve: Recursive Self-Improvement via Two-Timescale Meta-Skill Evolution,https://arxiv.org/abs/2607.05297,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05297,text/html; charset=utf-8,[2607.05297] MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution,Abstract page for arXiv paper 2607.05297: MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution,,,,,,,,2607.05297,,2026-07-10T17:33:26+00:00 -ale-0121,SkillOpt-Lite: Better and Faster Agent Self-Evolution via One Line of Vibe,https://arxiv.org/abs/2607.03451,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.03451,text/html; charset=utf-8,[2607.03451] SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe,Abstract page for arXiv paper 2607.03451: SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe,,,,,,,,2607.03451,,2026-07-10T17:33:26+00:00 -ale-0122,Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops,https://arxiv.org/abs/2607.07663,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07663,text/html; charset=utf-8,[2607.07663] Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops,Abstract page for arXiv paper 2607.07663: Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops,,,,,,,,2607.07663,,2026-07-10T17:33:26+00:00 -ale-0123,From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents,https://arxiv.org/abs/2607.07321,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07321,text/html; charset=utf-8,[2607.07321] From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents,Abstract page for arXiv paper 2607.07321: From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents,,,,,,,,2607.07321,,2026-07-10T17:33:26+00:00 -ale-0124,TTHE: Test-Time Harness Evolution,https://arxiv.org/abs/2607.08124,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08124,text/html; charset=utf-8,[2607.08124] TTHE: Test-Time Harness Evolution,Abstract page for arXiv paper 2607.08124: TTHE: Test-Time Harness Evolution,,,,,,,,2607.08124,,2026-07-10T17:33:26+00:00 -ale-0125,DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment,https://arxiv.org/abs/2607.07820,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07820,text/html; charset=utf-8,[2607.07820] DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment,Abstract page for arXiv paper 2607.07820: DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment,,,,,,,,2607.07820,,2026-07-10T17:33:26+00:00 -ale-0126,What Makes a Good Bug Report for an AI Agent?,https://arxiv.org/abs/2607.07593,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07593,text/html; charset=utf-8,[2607.07593] What Makes a Good Bug Report for an AI Agent?,Abstract page for arXiv paper 2607.07593: What Makes a Good Bug Report for an AI Agent?,,,,,,,,2607.07593,,2026-07-10T17:33:26+00:00 -ale-0127,Building Effective Agents,https://www.anthropic.com/engineering/building-effective-agents,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/building-effective-agents,text/html; charset=utf-8,Building Effective AI Agents \ Anthropic,"Discover how Anthropic approaches the development of reliable AI agents. Learn about our research on agent capabilities, safety considerations, and technical framework for building trustworthy AI.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0128,How we built our multi-agent research system,https://www.anthropic.com/engineering/multi-agent-research-system,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/multi-agent-research-system,text/html; charset=utf-8,How we built our multi-agent research system \ Anthropic,On the the engineering challenges and lessons learned from building Claude's Research system,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0129,Building Effective AI Agents: Architecture Patterns and Implementation Frameworks,https://resources.anthropic.com/hubfs/Building%20Effective%20AI%20Agents-%20Architecture%20Patterns%20and%20Implementation%20Frameworks.pdf,external,resources.anthropic.com,ok,200,https://resources.anthropic.com/hubfs/Building%20Effective%20AI%20Agents-%20Architecture%20Patterns%20and%20Implementation%20Frameworks.pdf,application/pdf,,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0130,AI Agent Architectures,https://hld.handbook.academy/curriculum/ai-ml-system-design/ai-agent-architectures/,external,hld.handbook.academy,ok,200,https://hld.handbook.academy/curriculum/ai-ml-system-design/ai-agent-architectures/,text/html; charset=utf-8,"AI Agent Architectures (ReAct, Reflection, Planning, Tool Use, Memory) - The HLD Handbook","The canonical patterns for turning an LLM into an agent: ReAct's think-act-observe loop, reflection and self-critique, planner-executor decomposition, tool use and function calling, and how agents manage short- and long-term memory.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0131,What Are Agentic Workflows?,https://weaviate.io/blog/what-are-agentic-workflows,external,weaviate.io,ok,200,https://weaviate.io/blog/what-are-agentic-workflows,text/html; charset=UTF-8,"What Are Agentic Workflows? Patterns, Memory, Use Cases, and Examples | Weaviate","Agentic workflows combine AI agents, tools, and agent memory to create adaptive systems. Learn the core patterns, use cases, and real-world examples.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0132,Agent Planning & Reflection Patterns,https://learnaivisually.com/tracks/ai-agents/planning-reflection,external,learnaivisually.com,ok,200,https://learnaivisually.com/tracks/ai-agents/planning-reflection,text/html; charset=utf-8,Agent Planning & Reflection Patterns | Learn AI Visually LAV LAV,"When agents should plan, retry, pause, or stop. Reasoning budget, ReAct, Reflexion, and termination logic ā€” each tied to a 'when' decision.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0133,Agentic Design Patterns,https://addyosmani.com/agents/04-agentic-design-patterns/,external,addyosmani.com,ok,200,https://addyosmani.com/agents/04-agentic-design-patterns/,text/html; charset=UTF-8,AddyOsmani.com - Lesson 4: agentic design patterns,"Addy Osmani is an engineering and evangelism leader who spent over 14 years at Google leading developer experience across Chrome and, in recent years, AI (Gemini, coding agents, and agentic engineering), most recently as a Director at Google Cloud AI.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0134,12 Factor Agents,https://github.com/humanlayer/12-factor-agents,external,github.com,ok,200,https://github.com/humanlayer/12-factor-agents,text/html; charset=utf-8,GitHub - humanlayer/12-factor-agents: What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? Ā· GitHub,What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? - humanlayer/12-factor-agents,humanlayer/12-factor-agents,24027,1834,26,What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?,NOASSERTION,2026-07-10T17:03:13Z,,,2026-07-10T17:33:26+00:00 -ale-0135,Durable Execution for Agentic Workflows,https://arizenai.com/durable-execution/,external,arizenai.com,ok,200,https://arizenai.com/durable-execution/,text/html; charset=utf-8,Durable Execution for Agentic Workflows | Arizen,A while loop is at-most-once across process boundaries. Production agents need exactly-once. The architecture must encode the guarantee.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0136,Code as Agent Harness,https://arxiv.org/abs/2605.18747,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.18747,text/html; charset=utf-8,[2605.18747] Code as Agent Harness,Abstract page for arXiv paper 2605.18747: Code as Agent Harness,,,,,,,,2605.18747,,2026-07-10T17:33:26+00:00 -ale-0137,Agentic Agile-V: From Vibe Coding to Verified Engineering,https://arxiv.org/abs/2605.20456,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.20456,text/html; charset=utf-8,[2605.20456] Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development,Abstract page for arXiv paper 2605.20456: Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development,,,,,,,,2605.20456,,2026-07-10T17:33:26+00:00 -ale-0138,"Harness Engineering for Language Agents: The Harness Layer as Control, Agency, and Runtime",https://www.preprints.org/manuscript/202603.1756,external,www.preprints.org,restricted,403,https://www.preprints.org/manuscript/202603.1756,text/html,,,,,,,,,,,restricted_or_rate_limited,2026-07-10T17:33:26+00:00 -ale-0139,Agentic Software Engineering: Foundational Pillars and a Research Roadmap,https://arxiv.org/abs/2509.06216,external,arxiv.org,ok,200,https://arxiv.org/abs/2509.06216,text/html; charset=utf-8,[2509.06216] Agentic Software Engineering: Foundational Pillars and a Research Roadmap,Abstract page for arXiv paper 2509.06216: Agentic Software Engineering: Foundational Pillars and a Research Roadmap,,,,,,,,2509.06216,,2026-07-10T17:33:26+00:00 -ale-0140,The Art of Loop Engineering,https://www.langchain.com/blog/the-art-of-loop-engineering,external,www.langchain.com,ok,200,https://www.langchain.com/blog/the-art-of-loop-engineering,text/html; charset=utf-8,The Art of Loop Engineering,"Agents automate real-world work, but reliable performance requires more than a good model, it requires a carefully designed harness built for specific tasks. This post explores the core agent loop, how stacking and extending loops builds more effective agents, and how to instrument each level with LangChain primitives.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0141,Loopy,https://github.com/Forward-Future/loopy,external,github.com,ok,200,https://github.com/Forward-Future/loopy,text/html; charset=utf-8,"GitHub - Forward-Future/loopy: A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows. Ā· GitHub","A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows. - Forward-Future/loopy",Forward-Future/loopy,2627,224,1,"A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows.",MIT,2026-07-10T16:42:56Z,,,2026-07-10T17:33:26+00:00 -ale-0142,The Factory Model: How Coding Agents Changed Software Engineering,https://addyosmani.com/blog/factory-model/,external,addyosmani.com,ok,200,https://addyosmani.com/blog/factory-model/,text/html; charset=UTF-8,AddyOsmani.com - The Factory Model: How Coding Agents Changed Software Engineering,Software engineering is not about writing code anymore. It is about building the factory that builds your software.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0143,2026 Agentic Coding Trends Report,https://resources.anthropic.com/2026-agentic-coding-trends-report,external,resources.anthropic.com,ok,200,https://resources.anthropic.com/2026-agentic-coding-trends-report,text/html; charset=UTF-8,2026 Agentic Coding Trends Report,"How coding agents are transforming software development - and what it means for engineering teams in 2026. Insights on multi-agent systems, human-AI collaboration, and scaling agentic coding across organizations. Includes case studies from Rakuten, TELUS, Zapier, and more.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0144,SWE-agent,https://github.com/SWE-agent/SWE-agent,external,github.com,ok,200,https://github.com/SWE-agent/SWE-agent,text/html; charset=utf-8,"GitHub - SWE-agent/SWE-agent: SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024] Ā· GitHub","SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024] - GitHub - SWE-agent/SWE-agent: SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]",SWE-agent/SWE-agent,19762,2159,28,"SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]",MIT,2026-07-10T17:09:10Z,,,2026-07-10T17:33:26+00:00 -ale-0145,SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering,https://arxiv.org/abs/2405.15793,external,arxiv.org,ok,200,https://arxiv.org/abs/2405.15793,text/html; charset=utf-8,[2405.15793] SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering,Abstract page for arXiv paper 2405.15793: SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering,,,,,,,,2405.15793,,2026-07-10T17:33:26+00:00 -ale-0146,mini-SWE-agent,https://mini-swe-agent.com/latest/,external,mini-swe-agent.com,ok,200,https://mini-swe-agent.com/latest/,text/html; charset=utf-8,Overview - mini-SWE-agent documentation,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0147,OpenHands,https://github.com/All-Hands-AI/OpenHands,external,github.com,ok,200,https://github.com/OpenHands/OpenHands,text/html; charset=utf-8,GitHub - OpenHands/OpenHands: šŸ™Œ OpenHands: AI-Driven Development Ā· GitHub,šŸ™Œ OpenHands: AI-Driven Development. Contribute to OpenHands/OpenHands development by creating an account on GitHub.,All-Hands-AI/OpenHands,80349,10253,358,šŸ™Œ OpenHands: AI-Driven Development,NOASSERTION,2026-07-10T17:27:21Z,,,2026-07-10T17:33:26+00:00 -ale-0148,OpenHands: An Open Platform for AI Software Developers as Generalist Agents,https://arxiv.org/abs/2407.16741,external,arxiv.org,ok,200,https://arxiv.org/abs/2407.16741,text/html; charset=utf-8,[2407.16741] OpenHands: An Open Platform for AI Software Developers as Generalist Agents,Abstract page for arXiv paper 2407.16741: OpenHands: An Open Platform for AI Software Developers as Generalist Agents,,,,,,,,2407.16741,,2026-07-10T17:33:26+00:00 -ale-0149,Agentless,https://github.com/OpenAutoCoder/Agentless,external,github.com,ok,200,https://github.com/OpenAutoCoder/Agentless,text/html; charset=utf-8,GitHub - OpenAutoCoder/Agentless: AgentlessšŸ±: an agentless approach to automatically solve software development problems Ā· GitHub,AgentlessšŸ±: an agentless approach to automatically solve software development problems - OpenAutoCoder/Agentless,OpenAutoCoder/Agentless,2080,235,54,AgentlessšŸ±: an agentless approach to automatically solve software development problems,MIT,2026-07-09T09:26:11Z,,,2026-07-10T17:33:26+00:00 -ale-0150,Agentless: Demystifying LLM-based Software Engineering Agents,https://arxiv.org/abs/2407.01489,external,arxiv.org,ok,200,https://arxiv.org/abs/2407.01489,text/html; charset=utf-8,[2407.01489] Agentless: Demystifying LLM-based Software Engineering Agents,Abstract page for arXiv paper 2407.01489: Agentless: Demystifying LLM-based Software Engineering Agents,,,,,,,,2407.01489,,2026-07-10T17:33:26+00:00 -ale-0151,AutoCodeRover,https://github.com/AutoCodeRoverSG/auto-code-rover,external,github.com,ok,200,https://github.com/AutoCodeRoverSG/auto-code-rover,text/html; charset=utf-8,GitHub - AutoCodeRoverSG/auto-code-rover: A project structure aware autonomous software engineer aiming for autonomous program improvement. Resolved 37.3% tasks (pass@1) in SWE-bench lite and 46.2% tasks (pass@1) in SWE-bench verified with each task costs less than $0.7. Ā· GitHub,A project structure aware autonomous software engineer aiming for autonomous program improvement. Resolved 37.3% tasks (pass@1) in SWE-bench lite and 46.2% tasks (pass@1) in SWE-bench verified with each task costs less than $0.7. - AutoCodeRoverSG/auto-code-rover,AutoCodeRoverSG/auto-code-rover,3095,332,20,A project structure aware autonomous software engineer aiming for autonomous program improvement. Resolved 37.3% tasks (pass@1) in SWE-bench lite and 46.2% tasks (pass@1) in SWE-bench verified with each task costs less than $0.7.,NOASSERTION,2026-07-08T21:43:44Z,,,2026-07-10T17:33:26+00:00 -ale-0152,AutoCodeRover: Autonomous Program Improvement,https://arxiv.org/abs/2404.05427,external,arxiv.org,ok,200,https://arxiv.org/abs/2404.05427,text/html; charset=utf-8,[2404.05427] AutoCodeRover: Autonomous Program Improvement,Abstract page for arXiv paper 2404.05427: AutoCodeRover: Autonomous Program Improvement,,,,,,,,2404.05427,,2026-07-10T17:33:26+00:00 -ale-0153,Ralph,https://ghuntley.com/ralph/,external,ghuntley.com,ok,200,https://ghuntley.com/ralph/,text/html; charset=utf-8,"Ralph Wiggum as a ""software engineer""","How Ralph Wiggum went from 'The Simpsons' to the biggest name in AI right now - Venture Beat šŸ˜ŽHere's a cool little field report from a Y Combinator hackathon event where they put Ralph Wiggum to the test. ""We Put a Coding Agent in a While Loop and It Shipped",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0154,everything is a ralph loop,https://ghuntley.com/loop/,external,ghuntley.com,ok,200,https://ghuntley.com/loop/,text/html; charset=utf-8,everything is a ralph loop,"Iā€™ve been thinking about how I build software is so very very different how I used to do it three years ago. No, Iā€™m not talking about acceleration through usage of AI but instead at a more fundamental level of approach, techniques and best practices. Standard software practices",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0155,how-to-ralph-wiggum,https://github.com/ghuntley/how-to-ralph-wiggum,external,github.com,ok,200,https://github.com/ghuntley/how-to-ralph-wiggum,text/html; charset=utf-8,GitHub - ghuntley/how-to-ralph-wiggum: The Ralph Wiggum Techniqueā€”the AI development methodology that reduces software costs to less than a fast food worker's wage. Ā· GitHub,The Ralph Wiggum Techniqueā€”the AI development methodology that reduces software costs to less than a fast food worker's wage. - ghuntley/how-to-ralph-wiggum,ghuntley/how-to-ralph-wiggum,1716,144,1,The Ralph Wiggum Techniqueā€”the AI development methodology that reduces software costs to less than a fast food worker's wage.,,2026-07-10T16:27:52Z,,,2026-07-10T17:33:26+00:00 -ale-0156,A Brief History of Ralph,https://www.humanlayer.dev/blog/brief-history-of-ralph,external,www.humanlayer.dev,ok,200,https://www.humanlayer.dev/blog/brief-history-of-ralph,text/html; charset=utf-8,A Brief History of Ralph | HumanLayer Blog,The Ralph Wiggum Technique went viral in the last week of 2025. Here's the story of ralph since the first time I met Geoff in June of 2025.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0157,Ralph Copilot,https://github.com/giocaizzi/ralph-copilot/tree/e5b2813cc876c73a8c9d3398c0115da0d15f63cf,external,github.com,ok,200,https://github.com/giocaizzi/ralph-copilot/tree/e5b2813cc876c73a8c9d3398c0115da0d15f63cf,text/html; charset=utf-8,GitHub - giocaizzi/ralph-copilot at e5b2813cc876c73a8c9d3398c0115da0d15f63cf Ā· GitHub,Copilot implementation of Ralph loop. Contribute to giocaizzi/ralph-copilot development by creating an account on GitHub.,giocaizzi/ralph-copilot,136,16,0,Copilot implementation of Ralph loop,,2026-06-28T06:41:40Z,,,2026-07-10T17:33:26+00:00 -ale-0158,Compound Engineering,https://every.to/guides/compound-engineering,external,every.to,ok,200,https://every.to/guides/compound-engineering,text/html; charset=utf-8,Compound Engineering - Every,The AI-native engineering philosophy,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0159,Gas Town,https://github.com/steveyegge/gastown,external,github.com,ok,200,https://github.com/gastownhall/gastown,text/html; charset=utf-8,GitHub - gastownhall/gastown: Gas Town - multi-agent workspace manager Ā· GitHub,Gas Town - multi-agent workspace manager. Contribute to gastownhall/gastown development by creating an account on GitHub.,steveyegge/gastown,16950,1553,257,Gas Town - multi-agent workspace manager,MIT,2026-07-10T17:16:43Z,,,2026-07-10T17:33:26+00:00 -ale-0160,Amp,https://ampcode.com/,external,ampcode.com,ok,200,https://ampcode.com/,text/html,Amp,Amp is a frontier coding agent that lets you wield the full power of leading models.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0161,karl,https://github.com/kayoslab/karl,external,github.com,ok,200,https://github.com/kayoslab/karl,text/html; charset=utf-8,GitHub - kayoslab/karl: Autonomous multi-agent development loop Ā· GitHub,Autonomous multi-agent development loop. Contribute to kayoslab/karl development by creating an account on GitHub.,kayoslab/karl,0,0,0,Autonomous multi-agent development loop,MIT,2026-04-08T07:56:55Z,,,2026-07-10T17:33:26+00:00 -ale-0162,joelclaw agent-loop skill,https://github.com/joelhooks/joelclaw/blob/main/skills/agent-loop/SKILL.md,external,github.com,ok,200,https://github.com/joelhooks/joelclaw/blob/main/skills/agent-loop/SKILL.md,text/html; charset=utf-8,joelclaw/skills/agent-loop/SKILL.md at main Ā· joelhooks/joelclaw Ā· GitHub,"Personal AI operating system ā€” blog, architecture decisions, and the journey from zero to a composable agent system. - joelclaw/skills/agent-loop/SKILL.md at main Ā· joelhooks/joelclaw",joelhooks/joelclaw,60,3,14,"Personal AI operating system ā€” blog, architecture decisions, and the journey from zero to a composable agent system.",,2026-07-09T16:55:39Z,,,2026-07-10T17:33:26+00:00 -ale-0163,SWE-bench reading list,https://github.com/SWE-bench/reading-list,external,github.com,ok,200,https://github.com/SWE-bench/reading-list,text/html; charset=utf-8,GitHub - SWE-bench/reading-list: Academic papers and works related to SWE-bench and SWE-agents Ā· GitHub,Academic papers and works related to SWE-bench and SWE-agents - SWE-bench/reading-list,SWE-bench/reading-list,15,4,0,Academic papers and works related to SWE-bench and SWE-agents,,2026-06-30T13:06:47Z,,,2026-07-10T17:33:26+00:00 -ale-0164,TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code,https://arxiv.org/abs/2602.06875,external,arxiv.org,ok,200,https://arxiv.org/abs/2602.06875,text/html; charset=utf-8,[2602.06875] TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code,Abstract page for arXiv paper 2602.06875: TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code,,,,,,,,2602.06875,,2026-07-10T17:33:26+00:00 -ale-0165,The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase,https://arxiv.org/abs/2603.25697,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.25697,text/html; charset=utf-8,[2603.25697] The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase,Abstract page for arXiv paper 2603.25697: The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase,,,,,,,,2603.25697,,2026-07-10T17:33:26+00:00 -ale-0166,Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures,https://arxiv.org/abs/2604.03515,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.03515,text/html; charset=utf-8,[2604.03515] Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures,Abstract page for arXiv paper 2604.03515: Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures,,,,,,,,2604.03515,,2026-07-10T17:33:26+00:00 -ale-0167,A Self-Improving Coding Agent,https://arxiv.org/abs/2504.15228,external,arxiv.org,ok,200,https://arxiv.org/abs/2504.15228,text/html; charset=utf-8,[2504.15228] A Self-Improving Coding Agent,Abstract page for arXiv paper 2504.15228: A Self-Improving Coding Agent,,,,,,,,2504.15228,,2026-07-10T17:33:26+00:00 -ale-0168,Factory 2.0: From Coding Agents to Software Factories,https://factory.ai/news/software-factory,external,factory.ai,ok,200,https://factory.ai/news/software-factory,text/html; charset=utf-8,Factory 2.0: From coding agents to software factories | Factory.ai Factory.ai Logo Arrow Right Icon,"In 2023, we launched Factory with the mission to bring autonomy to software engineering. While others were using models...",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0169,Ralph (snarktank),https://github.com/snarktank/ralph,external,github.com,ok,200,https://github.com/snarktank/ralph,text/html; charset=utf-8,GitHub - snarktank/ralph: Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete. Ā· GitHub,Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete. - GitHub - snarktank/ralph: Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete.,snarktank/ralph,20985,2041,76,Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete.,MIT,2026-07-10T16:28:32Z,,,2026-07-10T17:33:26+00:00 -ale-0170,ARIS (Auto-Research-In-Sleep),https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep,external,github.com,ok,200,https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep,text/html; charset=utf-8,"GitHub - wanshuiyin/Auto-claude-code-research-in-sleep: ARIS āš”ļø (Auto-Research-In-Sleep) ā€” Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in ā€” works with Claude Code, Codex, OpenClaw, or any LLM agent. Ā· GitHub","ARIS āš”ļø (Auto-Research-In-Sleep) ā€” Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in ā€” works with Claude Code, Codex, OpenClaw, or any LLM agent. - wanshuiyin/Auto-claude-code-research-in-sleep",wanshuiyin/Auto-claude-code-research-in-sleep,13233,1191,53,"ARIS āš”ļø (Auto-Research-In-Sleep) ā€” Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in ā€” works with Claude Code, Codex, OpenClaw, or any LLM agent.",MIT,2026-07-10T16:24:56Z,,,2026-07-10T17:33:26+00:00 -ale-0171,ralph-claude-code,https://github.com/frankbria/ralph-claude-code,external,github.com,ok,200,https://github.com/frankbria/ralph-claude-code,text/html; charset=utf-8,GitHub - frankbria/ralph-claude-code: Autonomous AI development loop for Claude Code with intelligent exit detection Ā· GitHub,Autonomous AI development loop for Claude Code with intelligent exit detection - frankbria/ralph-claude-code,frankbria/ralph-claude-code,9523,726,26,Autonomous AI development loop for Claude Code with intelligent exit detection,MIT,2026-07-10T13:03:40Z,,,2026-07-10T17:33:26+00:00 -ale-0172,AutoAgent,https://github.com/kevinrgu/autoagent,external,github.com,ok,200,https://github.com/kevinrgu/autoagent,text/html; charset=utf-8,GitHub - kevinrgu/autoagent: autonomous harness engineering Ā· GitHub,autonomous harness engineering. Contribute to kevinrgu/autoagent development by creating an account on GitHub.,kevinrgu/autoagent,4531,501,8,autonomous harness engineering,,2026-07-09T20:44:27Z,,,2026-07-10T17:33:26+00:00 -ale-0173,ralph-orchestrator,https://github.com/mikeyobrien/ralph-orchestrator,external,github.com,ok,200,https://github.com/mikeyobrien/ralph-orchestrator,text/html; charset=utf-8,GitHub - mikeyobrien/ralph-orchestrator: An improved implementation of the Ralph Wiggum technique for autonomous AI agent orchestration Ā· GitHub,An improved implementation of the Ralph Wiggum technique for autonomous AI agent orchestration - mikeyobrien/ralph-orchestrator,mikeyobrien/ralph-orchestrator,2994,279,9,An improved implementation of the Ralph Wiggum technique for autonomous AI agent orchestration,MIT,2026-07-10T16:29:52Z,,,2026-07-10T17:33:26+00:00 -ale-0174,zeroshot,https://github.com/the-open-engine/zeroshot,external,github.com,ok,200,https://github.com/the-open-engine/zeroshot,text/html; charset=utf-8,"GitHub - the-open-engine/zeroshot: Your autonomous engineering team in a CLI. The agent loop produces senior-level code that you can actually trust in prod because of non-negotiable feedback from independent reviewers. Supports Claude Code, OpenAI Codex, OpenCode, and Gemini CLI with trivial setup. Ā· GitHub","Your autonomous engineering team in a CLI. The agent loop produces senior-level code that you can actually trust in prod because of non-negotiable feedback from independent reviewers. Supports Claude Code, OpenAI Codex, OpenCode, and Gemini CLI with trivial setup. - the-open-engine/zeroshot",the-open-engine/zeroshot,1634,140,55,"Your autonomous engineering team in a CLI. The agent loop produces senior-level code that you can actually trust in prod because of non-negotiable feedback from independent reviewers. Supports Claude Code, OpenAI Codex, OpenCode, and Gemini CLI with trivial setup.",MIT,2026-07-10T08:02:14Z,,,2026-07-10T17:33:26+00:00 -ale-0175,ralphex,https://github.com/umputun/ralphex,external,github.com,ok,200,https://github.com/umputun/ralphex,text/html; charset=utf-8,GitHub - umputun/ralphex: Extended Ralph loop for autonomous AI-driven plan execution Ā· GitHub,Extended Ralph loop for autonomous AI-driven plan execution - umputun/ralphex,umputun/ralphex,1358,108,11,Extended Ralph loop for autonomous AI-driven plan execution,MIT,2026-07-10T14:36:54Z,,,2026-07-10T17:33:26+00:00 -ale-0176,Loki Mode,https://github.com/asklokesh/loki-mode,external,github.com,ok,200,https://github.com/asklokesh/loki-mode,text/html; charset=utf-8,"GitHub - asklokesh/loki-mode: Multi-agent autonomous SDLC framework. Spec to deployed app. PRD, GitHub issue, OpenAPI/JSON/YAML, or one-line brief. 5 AI providers, 11 quality gates. Ā· GitHub","Multi-agent autonomous SDLC framework. Spec to deployed app. PRD, GitHub issue, OpenAPI/JSON/YAML, or one-line brief. 5 AI providers, 11 quality gates. - asklokesh/loki-mode",asklokesh/loki-mode,1013,197,3,"Multi-agent autonomous SDLC framework. Spec to deployed app. PRD, GitHub issue, OpenAPI/JSON/YAML, or one-line brief. 5 AI providers, 11 quality gates.",NOASSERTION,2026-07-10T07:43:17Z,,,2026-07-10T17:33:26+00:00 -ale-0177,ralph (iannuttall),https://github.com/iannuttall/ralph,external,github.com,ok,200,https://github.com/iannuttall/ralph,text/html; charset=utf-8,"GitHub - iannuttall/ralph: A minimal, fileā€‘based agent loop for autonomous coding. Ā· GitHub","A minimal, fileā€‘based agent loop for autonomous coding. - iannuttall/ralph",iannuttall/ralph,933,90,9,"A minimal, fileā€‘based agent loop for autonomous coding.",,2026-07-08T20:46:37Z,,,2026-07-10T17:33:26+00:00 -ale-0178,ralph-loop-agent,https://github.com/vercel-labs/ralph-loop-agent,external,github.com,ok,200,https://github.com/vercel-labs/ralph-loop-agent,text/html; charset=utf-8,GitHub - vercel-labs/ralph-loop-agent: Continuous Autonomy for the AI SDK Ā· GitHub,Continuous Autonomy for the AI SDK. Contribute to vercel-labs/ralph-loop-agent development by creating an account on GitHub.,vercel-labs/ralph-loop-agent,814,83,2,Continuous Autonomy for the AI SDK,Apache-2.0,2026-07-10T14:19:30Z,,,2026-07-10T17:33:26+00:00 -ale-0179,Open Ralph Wiggum,https://github.com/Th0rgal/open-ralph-wiggum,external,github.com,ok,200,https://github.com/Th0rgal/open-ralph-wiggum,text/html; charset=utf-8,"GitHub - Th0rgal/open-ralph-wiggum: Type `ralph ""prompt""` to start open code in a ralph loop. Also supports a prompt file & status check. Open Code, Claude Code, Codex, Copilot Ā· GitHub","Type `ralph ""prompt""` to start open code in a ralph loop. Also supports a prompt file & status check. Open Code, Claude Code, Codex, Copilot - Th0rgal/open-ralph-wiggum",Th0rgal/open-ralph-wiggum,1841,142,8,"Type `ralph ""prompt""` to start open code in a ralph loop. Also supports a prompt file & status check. Open Code, Claude Code, Codex, Copilot",MIT,2026-07-10T01:24:18Z,,,2026-07-10T17:33:26+00:00 -ale-0180,Superpowers 6,https://blog.fsck.com/2026/06/15/Superpowers-6/,external,blog.fsck.com,ok,200,https://blog.fsck.com/2026/06/15/Superpowers-6/,text/html; charset=utf-8,Superpowers 6 ā€” Massively Parallel Procrastination,"I'm Jesse. I make stuff. Software, hardware. Very occasionally, trouble.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0181,Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality,https://arxiv.org/abs/2607.03691,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.03691,text/html; charset=utf-8,[2607.03691] Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality,Abstract page for arXiv paper 2607.03691: Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality,,,,,,,,2607.03691,,2026-07-10T17:33:26+00:00 -ale-0182,Introducing Devin Security Swarm,https://cognition.com/blog/introducing-devin-security-swarm,external,cognition.com,ok,200,https://cognition.com/blog/introducing-devin-security-swarm,text/html; charset=utf-8,Introducing Devin Security Swarm | Cognition,"Devin Security Swarm finds vulnerabilities across the codebase, validates exploitability at runtime, and ships remediation PRs.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0183,Towards Self-Driving Codebases,https://cursor.com/blog/self-driving-codebases,external,cursor.com,ok,200,https://cursor.com/blog/self-driving-codebases,text/html; charset=utf-8,Towards self-driving codebases Ā· Cursor,We're making a part of our multi-agent research harness available to try today in preview.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0184,Looper,https://github.com/ksimback/looper,external,github.com,ok,200,https://github.com/ksimback/looper,text/html; charset=utf-8,"GitHub - ksimback/looper: Design visual, review-gated agent loops for Claude Code before you run them. Ā· GitHub","Design visual, review-gated agent loops for Claude Code before you run them. - ksimback/looper",ksimback/looper,655,57,0,"Design visual, review-gated agent loops for Claude Code before you run them.",MIT,2026-07-10T13:30:17Z,,,2026-07-10T17:33:26+00:00 -ale-0185,Agent Apprenticeship,https://github.com/Forsy-AI/agent-apprenticeship,external,github.com,ok,200,https://github.com/Forsy-AI/agent-apprenticeship,text/html; charset=utf-8,"GitHub - Forsy-AI/agent-apprenticeship: The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents. Ā· GitHub","The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents. - Forsy-AI/agent-apprenticeship",Forsy-AI/agent-apprenticeship,1311,53,0,"The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents.",MIT,2026-07-09T16:18:42Z,,,2026-07-10T17:33:26+00:00 -ale-0186,Scholar Loop,https://github.com/renee-jia/scholar-loop,external,github.com,ok,200,https://github.com/renee-jia/scholar-loop,text/html; charset=utf-8,"GitHub - renee-jia/scholar-loop: An autonomous AI scientist: a multi-agent loop over literature, experiments, self-critique and write-up, with deterministic guards against reward-hacking and hallucination. Ā· GitHub","An autonomous AI scientist: a multi-agent loop over literature, experiments, self-critique and write-up, with deterministic guards against reward-hacking and hallucination. - renee-jia/scholar-loop",renee-jia/scholar-loop,461,35,0,"An autonomous AI scientist: a multi-agent loop over literature, experiments, self-critique and write-up, with deterministic guards against reward-hacking and hallucination.",MIT,2026-07-08T05:18:54Z,,,2026-07-10T17:33:26+00:00 -ale-0187,Factory: Incident Response Automation,https://factory.ai/news/incident-response,external,factory.ai,ok,200,https://factory.ai/news/incident-response,text/html; charset=utf-8,Incident Response | Factory.ai Factory.ai Logo Arrow Right Icon,"On-call alerts have always been stomach-dropping moments. Someone's dinner, weekend, or launch review gets hijacked for ...",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0188,loop-engineering (Cobus Greyling),https://github.com/cobusgreyling/loop-engineering,external,github.com,ok,200,https://github.com/cobusgreyling/loop-engineering,text/html; charset=utf-8,"GitHub - cobusgreyling/loop-engineering: Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audit, loop-init, loop-cost. Ā· GitHub","Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audit, loop-init, loop-cost. - cobusgreyling/loop-engineering",cobusgreyling/loop-engineering,6935,878,26,"Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audit, loop-init, loop-cost.",MIT,2026-07-10T17:19:28Z,,,2026-07-10T17:33:26+00:00 -ale-0189,AutoCVE,https://github.com/larlarua/AutoCVE,external,github.com,ok,200,https://github.com/larlarua/AutoCVE,text/html; charset=utf-8,"GitHub - larlarua/AutoCVE: Agent-driven automated CVE discovery platform for source code auditing, vulnerability verification, and report generation. Ā· GitHub","Agent-driven automated CVE discovery platform for source code auditing, vulnerability verification, and report generation. - larlarua/AutoCVE",larlarua/AutoCVE,1166,76,19,"Agent-driven automated CVE discovery platform for source code auditing, vulnerability verification, and report generation.",AGPL-3.0,2026-07-10T17:11:12Z,,,2026-07-10T17:33:26+00:00 -ale-0190,LoongFlow (Baidu),https://github.com/baidu-baige/LoongFlow,external,github.com,ok,200,https://github.com/baidu-baige/LoongFlow,text/html; charset=utf-8,"GitHub - baidu-baige/LoongFlow: LoongFlow is an expert-grade Agent framework for Loop Engineering. Through a Plan-Execute-Summary loop and structured experiential memory, it enables AI to continuously think, execute, reflect, and evolve across complex software engineering, mathematical, and machine learning tasks. Ā· GitHub","LoongFlow is an expert-grade Agent framework for Loop Engineering. Through a Plan-Execute-Summary loop and structured experiential memory, it enables AI to continuously think, execute, reflect, and evolve across complex software engineering, mathematical, and machine learning tasks. - baidu-baige/LoongFlow",baidu-baige/LoongFlow,446,52,0,"LoongFlow is an expert-grade Agent framework for Loop Engineering. Through a Plan-Execute-Summary loop and structured experiential memory, it enables AI to continuously think, execute, reflect, and evolve across complex software engineering, mathematical, and machine learning tasks.",Apache-2.0,2026-07-10T16:19:04Z,,,2026-07-10T17:33:26+00:00 -ale-0191,cc10x,https://github.com/romiluz13/cc10x,external,github.com,ok,200,https://github.com/romiluz13/cc10x,text/html; charset=utf-8,"GitHub - romiluz13/cc10x: The Loop Engine for Claude Code ā€” engineer the loop, not the prompt. 1 router Ā· 9 agents Ā· 16 skills Ā· 4 workflows. Fail-closed gates, test honesty, anti-anchored review. Ā· GitHub","The Loop Engine for Claude Code ā€” engineer the loop, not the prompt. 1 router Ā· 9 agents Ā· 16 skills Ā· 4 workflows. Fail-closed gates, test honesty, anti-anchored review. - romiluz13/cc10x",romiluz13/cc10x,150,24,1,"The Loop Engine for Claude Code ā€” engineer the loop, not the prompt. 1 router Ā· 9 agents Ā· 16 skills Ā· 4 workflows. Fail-closed gates, test honesty, anti-anchored review.",MIT,2026-07-06T11:15:54Z,,,2026-07-10T17:33:26+00:00 -ale-0192,Why Agentic Systems Must Produce Deterministic Outputs to Scale,https://streamzero.com/blog/posts/deep-dives-tools-technologies-architectures/agentic-patterns/why-agentic-systems-must-produce-deterministic-outputs-to-scale,external,streamzero.com,ok,200,https://streamzero.com/blog/posts/deep-dives-tools-technologies-architectures/agentic-patterns/why-agentic-systems-must-produce-deterministic-outputs-to-scale,text/html; charset=UTF-8,Why Agentic Systems Must Produce Deterministic Outputs to Scale,"Agentic systems are gaining traction, but their inherent non-determinism poses a significant challenge for production environments. This document argues that deterministic outputs are essential for scaling agentic systems, enabling validation, security, and compliance in critical applications.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0193,Stop Babysitting Your Coding Agent. Give It Backpressure.,https://generativeprogrammer.com/p/stop-babysitting-your-coding-agent,external,generativeprogrammer.com,ok,200,https://generativeprogrammer.com/p/stop-babysitting-your-coding-agent,text/html; charset=utf-8,Stop Babysitting Your Coding Agent. Give It Backpressure.,Backpressure is feedback that reaches the agent before the agent reaches the human.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0194,How to Build a Self-Verification Loop in Claude Code,https://dev.to/shipwithaiio/how-to-build-a-self-verification-loop-in-claude-code-3-layers-20-minutes-m1p,external,dev.to,ok,200,https://dev.to/shipwithaiio/how-to-build-a-self-verification-loop-in-claude-code-3-layers-20-minutes-m1p,text/html; charset=utf-8,"How to Build a Self-Verification Loop in Claude Code (3 Layers, 20 Minutes) - DEV Community Navigation menu Search Search Close More... Copy link Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode","Claude Code's Stop hook blocks the agent from finishing until verification passes. Combine it with... Tagged with ai, programming, productivity, claude.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0195,How to build a better agent harness with traces and evals,https://arize.com/blog/improve-ai-agents-traces-evals-harness/,external,arize.com,ok,200,https://arize.com/blog/improve-ai-agents-traces-evals-harness/,text/html; charset=UTF-8,How to build a better agent harness with traces and evals - Arize AI,"Agents are easy to prototype and hard to improve. A repeatable loop of traces, evals, failed-span inspection, and targeted harness changes makes agent behavior easier to debug and improve.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0196,Better Harness: A Recipe for Harness Hill-Climbing with Evals,https://www.langchain.com/blog/better-harness-a-recipe-for-harness-hill-climbing-with-evals,external,www.langchain.com,ok,200,https://www.langchain.com/blog/better-harness-a-recipe-for-harness-hill-climbing-with-evals,text/html; charset=utf-8,Better Harness: A Recipe for Harness Hill-Climbing with Evals,"We can build better agents by building better harnesses. But to autonomously build a ā€œbetterā€ harness, we need a strong learning signal to ā€œhill-climbā€ on. We share how we use evals as that signal, plus design decisions that help our agent generalize instead of overfit. Better-Harness is a system for iteratively sourcing and improving your harness with evals.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0197,Improving Deep Agents with harness engineering,https://www.langchain.com/blog/improving-deep-agents-with-harness-engineering,external,www.langchain.com,ok,200,https://www.langchain.com/blog/improving-deep-agents-with-harness-engineering,text/html; charset=utf-8,Improving Deep Agents with harness engineering,"Harness engineering improved LangChain's coding agent from Top 30 to Top 5 on Terminal Bench using self-verification, tracing, and context optimization.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0198,OpenAI agent evals,https://developers.openai.com/api/docs/guides/agent-evals,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agent-evals,text/html; charset=utf-8,Evaluate agent workflows | OpenAI API,"Learn how to evaluate agent workflows with traces, graders, datasets, and evaluation runs on the OpenAI platform.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0199,Promptfoo OpenAI Agents provider,https://www.promptfoo.dev/docs/providers/openai-agents/,external,www.promptfoo.dev,ok,200,https://www.promptfoo.dev/docs/providers/openai-agents/,text/html; charset=utf-8,OpenAI Agents | Promptfoo,"Test OpenAI Agents with tools, handoffs, sessions, sandbox workflows, and tracing in promptfoo.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0200,Inspect AI,https://github.com/UKGovernmentBEIS/inspect_ai,external,github.com,ok,200,https://github.com/UKGovernmentBEIS/inspect_ai,text/html; charset=utf-8,GitHub - UKGovernmentBEIS/inspect_ai: Inspect: A framework for large language model evaluations Ā· GitHub,Inspect: A framework for large language model evaluations - UKGovernmentBEIS/inspect_ai,UKGovernmentBEIS/inspect_ai,2328,596,230,Inspect: A framework for large language model evaluations,MIT,2026-07-10T17:06:54Z,,,2026-07-10T17:33:26+00:00 -ale-0201,OpenTelemetry Semantic Conventions for Generative AI Systems,https://opentelemetry.io/docs/specs/semconv/gen-ai/,external,opentelemetry.io,ok,200,https://opentelemetry.io/docs/specs/semconv/gen-ai/,text/html; charset=UTF-8,Moved: Generative AI semantic conventions | OpenTelemetry The OpenTelemetry Logo,Important GenAI semantic conventions have moved to the OpenTelemetry GenAI semantic conventions repository. This page has moved and is no longer maintained in this repository.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0202,AgentOps,https://github.com/AgentOps-AI/agentops,external,github.com,ok,200,https://github.com/AgentOps-AI/agentops,text/html; charset=utf-8,"GitHub - AgentOps-AI/agentops: Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI Ā· GitHub","Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI - AgentOps-AI/agentops",AgentOps-AI/agentops,5693,604,170,"Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI",MIT,2026-07-10T15:21:21Z,,,2026-07-10T17:33:26+00:00 -ale-0203,Langfuse,https://github.com/langfuse/langfuse,external,github.com,ok,200,https://github.com/langfuse/langfuse,text/html; charset=utf-8,"GitHub - langfuse/langfuse: šŸŖ¢ Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. šŸŠYC W23 Ā· GitHub","šŸŖ¢ Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. šŸŠYC W23 - GitHub - langfuse/langfuse: šŸŖ¢ Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. šŸŠYC W23",langfuse/langfuse,30889,3251,705,"šŸŖ¢ Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. šŸŠYC W23",NOASSERTION,2026-07-10T16:55:11Z,,,2026-07-10T17:33:26+00:00 -ale-0204,LangSmith,https://www.langchain.com/langsmith,external,www.langchain.com,ok,200,https://www.langchain.com/langsmith/observability,text/html; charset=utf-8,LangSmith: Agent & LLM Observability Platform,"Complete AI agent and LLM observability platform with tracing and real-time monitoring. Debug agents, find failures fast, and track costs and latency.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0205,Arize Phoenix,https://github.com/Arize-ai/phoenix,external,github.com,ok,200,https://github.com/Arize-ai/phoenix,text/html; charset=utf-8,GitHub - Arize-ai/phoenix: AI Observability & Evaluation Ā· GitHub,AI Observability & Evaluation. Contribute to Arize-ai/phoenix development by creating an account on GitHub.,Arize-ai/phoenix,10499,976,665,AI Observability & Evaluation,NOASSERTION,2026-07-10T16:29:19Z,,,2026-07-10T17:33:26+00:00 -ale-0206,Braintrust,https://www.braintrust.dev/,external,www.braintrust.dev,ok,200,https://www.braintrust.dev/,text/html; charset=utf-8,Braintrust - The AI observability platform for building quality AI products,"Ship quality AI at scale. Braintrust is the AI observability platform for tracing production, running evals, and catching regressions before they reach users.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0207,Weave,https://docs.wandb.ai/weave,external,docs.wandb.ai,ok,200,https://docs.wandb.ai/weave,text/html; charset=utf-8,W&B Weave - Weights & Biases Documentation,"Track, test, and improve language model apps with W&B Weave",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0208,Agentic Verification of Software Systems,https://arxiv.org/abs/2511.17330,external,arxiv.org,ok,200,https://arxiv.org/abs/2511.17330,text/html; charset=utf-8,[2511.17330] Agentic Verification of Software Systems,Abstract page for arXiv paper 2511.17330: Agentic Verification of Software Systems,,,,,,,,2511.17330,,2026-07-10T17:33:26+00:00 -ale-0209,Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses,https://arxiv.org/abs/2604.25850,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.25850,text/html; charset=utf-8,[2604.25850] Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses,Abstract page for arXiv paper 2604.25850: Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses,,,,,,,,2604.25850,,2026-07-10T17:33:26+00:00 -ale-0210,"A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance",https://arxiv.org/abs/2603.18096,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.18096,text/html; charset=utf-8,"[2603.18096] A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance","Abstract page for arXiv paper 2603.18096: A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance",,,,,,,,2603.18096,,2026-07-10T17:33:26+00:00 -ale-0211,Meta-Harness: End-to-End Optimization of Model Harnesses,https://arxiv.org/abs/2603.28052,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.28052,text/html; charset=utf-8,[2603.28052] Meta-Harness: End-to-End Optimization of Model Harnesses,Abstract page for arXiv paper 2603.28052: Meta-Harness: End-to-End Optimization of Model Harnesses,,,,,,,,2603.28052,,2026-07-10T17:33:26+00:00 -ale-0212,Self-Evolving Agents with Anytime-Valid Certificates,https://arxiv.org/abs/2607.00871,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.00871,text/html; charset=utf-8,[2607.00871] Self-Evolving Agents with Anytime-Valid Certificates,Abstract page for arXiv paper 2607.00871: Self-Evolving Agents with Anytime-Valid Certificates,,,,,,,,2607.00871,,2026-07-10T17:33:26+00:00 -ale-0213,Delayed Verification Destabilizes Multi-Agent LLM Belief,https://arxiv.org/abs/2606.27409,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.27409,text/html; charset=utf-8,[2606.27409] Delayed Verification Destabilizes Multi-Agent LLM Belief: Instability Thresholds and Optimal Corrector Placement,Abstract page for arXiv paper 2606.27409: Delayed Verification Destabilizes Multi-Agent LLM Belief: Instability Thresholds and Optimal Corrector Placement,,,,,,,,2606.27409,,2026-07-10T17:33:26+00:00 -ale-0214,Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory,https://arxiv.org/abs/2606.06523,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.06523,text/html; charset=utf-8,[2606.06523] Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory,Abstract page for arXiv paper 2606.06523: Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory,,,,,,,,2606.06523,,2026-07-10T17:33:26+00:00 -ale-0215,"Regimes: An Auditable, Held-Out-Gated Improvement Loop",https://arxiv.org/abs/2606.10241,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.10241,text/html; charset=utf-8,"[2606.10241] Regimes: An Auditable, Held-Out-Gated Improvement Loop Demonstrated on LongMemEval with ActiveGraph","Abstract page for arXiv paper 2606.10241: Regimes: An Auditable, Held-Out-Gated Improvement Loop Demonstrated on LongMemEval with ActiveGraph",,,,,,,,2606.10241,,2026-07-10T17:33:26+00:00 -ale-0216,Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents,https://arxiv.org/abs/2605.22608,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.22608,text/html; charset=utf-8,[2605.22608] Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents,Abstract page for arXiv paper 2605.22608: Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents,,,,,,,,2605.22608,,2026-07-10T17:33:26+00:00 -ale-0217,Agentic Code Review,https://addyosmani.com/blog/agentic-code-review/,external,addyosmani.com,ok,200,https://addyosmani.com/blog/agentic-code-review/,text/html; charset=UTF-8,AddyOsmani.com - Agentic Code Review,"Coding agents are extraordinarily good now, and getting better fast. The interesting consequence is that the hard part of engineering moved from writing code...",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0218,Using DSPy to Evaluate and Improve Datasette Agent's SQL System Prompts,https://simonwillison.net/2026/Jul/2/dspy-datasette-agent-prompts/,external,simonwillison.net,ok,200,https://simonwillison.net/2026/Jul/2/dspy-datasette-agent-prompts/,text/html; charset=utf-8,Research: Using DSPy to evaluate and improve Datasette Agent's SQL system prompts,"Leveraging the DSPy framework, this project evaluates and refines the core production system prompts used by Datasette Agentā€™s read-only SQL question answerer. The methodology involves a harness where DSPy agents ā€¦",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0219,agentops (boshu2),https://github.com/boshu2/agentops,external,github.com,ok,200,https://github.com/boshu2/agentops,text/html; charset=utf-8,"GitHub - boshu2/agentops: Independent verification for coding agents. A change isn't done until a different model or a real test checks it, and the verdict is recorded in your repo. Ā· GitHub","Independent verification for coding agents. A change isn't done until a different model or a real test checks it, and the verdict is recorded in your repo. - boshu2/agentops",boshu2/agentops,408,40,4,"Independent verification for coding agents. A change isn't done until a different model or a real test checks it, and the verdict is recorded in your repo.",Apache-2.0,2026-07-10T17:00:56Z,,,2026-07-10T17:33:26+00:00 -ale-0220,HALO (Hierarchical Agent Loop Optimizer),https://github.com/context-labs/halo,external,github.com,ok,200,https://github.com/context-labs/halo,text/html; charset=utf-8,GitHub - context-labs/HALO: Hierarchal Agent Loop Optimizer Ā· GitHub,Hierarchal Agent Loop Optimizer. Contribute to context-labs/HALO development by creating an account on GitHub.,context-labs/halo,1087,76,8,Hierarchal Agent Loop Optimizer,,2026-07-10T17:19:21Z,,,2026-07-10T17:33:26+00:00 -ale-0221,"Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions",https://arxiv.org/abs/2607.03935,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.03935,text/html; charset=utf-8,"[2607.03935] Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions","Abstract page for arXiv paper 2607.03935: Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions",,,,,,,,2607.03935,,2026-07-10T17:33:26+00:00 -ale-0222,Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference,https://arxiv.org/abs/2607.02882,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.02882,text/html; charset=utf-8,[2607.02882] Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference,Abstract page for arXiv paper 2607.02882: Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference,,,,,,,,2607.02882,,2026-07-10T17:33:26+00:00 -ale-0223,SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use,https://arxiv.org/abs/2607.01874,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.01874,text/html; charset=utf-8,[2607.01874] SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use,Abstract page for arXiv paper 2607.01874: SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use,,,,,,,,2607.01874,,2026-07-10T17:33:26+00:00 -ale-0224,SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Bug Reproduction Tests,https://arxiv.org/abs/2607.00990,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.00990,text/html; charset=utf-8,[2607.00990] SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests,Abstract page for arXiv paper 2607.00990: SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests,,,,,,,,2607.00990,,2026-07-10T17:33:26+00:00 -ale-0225,Agentic coding notes,https://danluu.com/ai-coding/,external,danluu.com,ok,200,https://danluu.com/ai-coding/,text/html; charset=utf-8,"Agentic test processes, LLM benchmarks, and other notes on agentic coding from Galapagos Island",,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0226,Understanding Is the New Bottleneck,https://www.geoffreylitt.com/2026/07/02/understanding-is-the-new-bottleneck.html,external,www.geoffreylitt.com,ok,200,https://www.geoffreylitt.com/2026/07/02/understanding-is-the-new-bottleneck.html,text/html; charset=UTF-8,Understanding is the new bottleneck,"Agents can write code faster than we can absorb it. Here's why it still matters for humans to understand what they build ā€” and some techniques for doing that efficiently: explainer docs, quizzes, micro-worlds, and shared spaces.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0227,Verifying Agentic Development at Scale,https://cognition.com/blog/testing-development,external,cognition.com,ok,200,https://cognition.com/blog/testing-development,text/html; charset=utf-8,Verifying Agentic Development at Scale | Cognition,What weā€™ve learned building end-to-end testing capabilities in Devinā€™s virtual machine,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0228,Loop Engineering Without Verification Is Just Automation,https://www.sonarsource.com/blog/loop-engineering-without-verification-is-just-automation/,external,www.sonarsource.com,ok,200,https://www.sonarsource.com/blog/loop-engineering-without-verification-is-just-automation/,text/html,Loop engineering without verification is just automation | Sonar,Explore how LLM reviewers and deterministic checks work together to keep coding agent loops from shipping unfinished code.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0229,SkillSpec,https://github.com/modiqo/skillspec,external,github.com,ok,200,https://github.com/modiqo/skillspec,text/html; charset=utf-8,"GitHub - modiqo/skillspec: SkillSpec makes agent skills followable, testable, and provable with Doctor risk reports, guided imports, structured contracts, and alignment proof. Ā· GitHub","SkillSpec makes agent skills followable, testable, and provable with Doctor risk reports, guided imports, structured contracts, and alignment proof. - modiqo/skillspec",modiqo/skillspec,930,58,7,"SkillSpec makes agent skills followable, testable, and provable with Doctor risk reports, guided imports, structured contracts, and alignment proof.",Apache-2.0,2026-07-10T17:10:32Z,,,2026-07-10T17:33:26+00:00 -ale-0230,Shepherd,https://github.com/shepherd-agents/shepherd,external,github.com,ok,200,https://github.com/shepherd-agents/shepherd,text/html; charset=utf-8,"GitHub - shepherd-agents/shepherd: A runtime substrate that turns an agent's execution into a reversible, Git-like trace, so meta-agents can observe, fork, replay, and revert any run. Couples agent and environments in a copy-on-write fork ~5x faster than docker commit, with ~95% KV-cache reuse on replay. Framework built for meta-agents to supervise, optimize, and train other agents Ā· GitHub","A runtime substrate that turns an agent's execution into a reversible, Git-like trace, so meta-agents can observe, fork, replay, and revert any run. Couples agent and environments in a copy-on-write fork ~5x faster than docker commit, with ~95% KV-cache reuse on replay. Framework built for meta-agents to supervise, optimize, and train other agents - shepherd-agents/shepherd",shepherd-agents/shepherd,1290,86,6,"A runtime substrate that turns an agent's execution into a reversible, Git-like trace, so meta-agents can observe, fork, replay, and revert any run. Couples agent and environments in a copy-on-write fork ~5x faster than docker commit, with ~95% KV-cache reuse on replay. Framework built for meta-agents to supervise, optimize, and train other agents",MIT,2026-07-10T17:14:06Z,,,2026-07-10T17:33:26+00:00 -ale-0231,AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation,https://arxiv.org/abs/2607.06273,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06273,text/html; charset=utf-8,[2607.06273] AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation,Abstract page for arXiv paper 2607.06273: AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation,,,,,,,,2607.06273,,2026-07-10T17:33:26+00:00 -ale-0232,SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review,https://arxiv.org/abs/2607.06065,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06065,text/html; charset=utf-8,[2607.06065] SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review,Abstract page for arXiv paper 2607.06065: SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review,,,,,,,,2607.06065,,2026-07-10T17:33:26+00:00 -ale-0233,"Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode",https://arxiv.org/abs/2607.07405,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07405,text/html; charset=utf-8,"[2607.07405] Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents","Abstract page for arXiv paper 2607.07405: Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents",,,,,,,,2607.07405,,2026-07-10T17:33:26+00:00 -ale-0234,Harnessing Code Agents for Automatic Software Verification,https://arxiv.org/abs/2607.06341,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06341,text/html; charset=utf-8,[2607.06341] Harnessing Code Agents for Automatic Software Verification,Abstract page for arXiv paper 2607.06341: Harnessing Code Agents for Automatic Software Verification,,,,,,,,2607.06341,,2026-07-10T17:33:26+00:00 -ale-0235,LLM-as-a-Verifier: A General-Purpose Verification Framework,https://arxiv.org/abs/2607.05391,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05391,text/html; charset=utf-8,[2607.05391] LLM-as-a-Verifier: A General-Purpose Verification Framework,Abstract page for arXiv paper 2607.05391: LLM-as-a-Verifier: A General-Purpose Verification Framework,,,,,,,,2607.05391,,2026-07-10T17:33:26+00:00 -ale-0236,From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents,https://arxiv.org/abs/2607.08028,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08028,text/html; charset=utf-8,[2607.08028] From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents,Abstract page for arXiv paper 2607.08028: From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents,,,,,,,,2607.08028,,2026-07-10T17:33:26+00:00 -ale-0237,From Noisy Traces to Root Causes: Structural Trajectory Analysis and Causal Extraction for Agent Optimization,https://arxiv.org/abs/2607.07702,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07702,text/html; charset=utf-8,[2607.07702] From Noisy Traces to Root Causes: Structural Trajectory Analysis and Causal Extraction for Agent Optimization,Abstract page for arXiv paper 2607.07702: From Noisy Traces to Root Causes: Structural Trajectory Analysis and Causal Extraction for Agent Optimization,,,,,,,,2607.07702,,2026-07-10T17:33:26+00:00 -ale-0238,Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems,https://arxiv.org/abs/2607.07989,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07989,text/html; charset=utf-8,[2607.07989] Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems,Abstract page for arXiv paper 2607.07989: Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems,,,,,,,,2607.07989,,2026-07-10T17:33:26+00:00 -ale-0239,3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse,https://arxiv.org/abs/2607.07980,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07980,text/html; charset=utf-8,[2607.07980] 3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse,Abstract page for arXiv paper 2607.07980: 3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse,,,,,,,,2607.07980,,2026-07-10T17:33:26+00:00 -ale-0240,grill-for-unknowns,https://github.com/nicobailon/grill-for-unknowns,external,github.com,ok,200,https://github.com/nicobailon/grill-for-unknowns,text/html; charset=utf-8,"GitHub - nicobailon/grill-for-unknowns: Agent skill for finding unknowns, grilling plans, and reaching shared understanding before implementation Ā· GitHub","Agent skill for finding unknowns, grilling plans, and reaching shared understanding before implementation - nicobailon/grill-for-unknowns",nicobailon/grill-for-unknowns,107,2,0,"Agent skill for finding unknowns, grilling plans, and reaching shared understanding before implementation",MIT,2026-07-10T17:33:41Z,,,2026-07-10T17:33:26+00:00 -ale-0241,The lethal trifecta for AI agents,https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/,external,simonwillison.net,ok,200,https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/,text/html; charset=utf-8,,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0242,Prompt injection series,https://simonwillison.net/series/prompt-injection/,external,simonwillison.net,ok,200,https://simonwillison.net/series/prompt-injection/,text/html; charset=utf-8,Simon Willison: Prompt injection,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0243,Agentic AI - Threats and Mitigations,https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/,external,genai.owasp.org,ok,200,https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/,text/html; charset=UTF-8,Agentic AI - OWASP Lists Threats and Mitigations,"Explore key threats and mitigation strategies for agentic AI, focusing on security measures to address vulnerabilities in AI applications and their potential risks.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0244,Designing AI agents to resist prompt injection,https://openai.com/index/designing-agents-to-resist-prompt-injection/,external,openai.com,restricted,403,https://openai.com/index/designing-agents-to-resist-prompt-injection/,text/html; charset=UTF-8,,,,,,,,,,,restricted_or_rate_limited,2026-07-10T17:33:26+00:00 -ale-0245,sandbox-runtime,https://github.com/anthropic-experimental/sandbox-runtime,external,github.com,ok,200,https://github.com/anthropic-experimental/sandbox-runtime,text/html; charset=utf-8,"GitHub - anthropic-experimental/sandbox-runtime: A lightweight sandboxing tool for enforcing filesystem and network restrictions on arbitrary processes at the OS level, without requiring a container. Ā· GitHub","A lightweight sandboxing tool for enforcing filesystem and network restrictions on arbitrary processes at the OS level, without requiring a container. - anthropic-experimental/sandbox-runtime",anthropic-experimental/sandbox-runtime,4624,357,126,"A lightweight sandboxing tool for enforcing filesystem and network restrictions on arbitrary processes at the OS level, without requiring a container.",Apache-2.0,2026-07-10T16:45:59Z,,,2026-07-10T17:33:26+00:00 -ale-0246,E2B,https://github.com/e2b-dev/E2B,external,github.com,ok,200,https://github.com/e2b-dev/E2B,text/html; charset=utf-8,"GitHub - e2b-dev/E2B: Open-source, secure environment with real-world tools for enterprise-grade agents. Ā· GitHub","Open-source, secure environment with real-world tools for enterprise-grade agents. - e2b-dev/E2B",e2b-dev/E2B,12923,963,61,"Open-source, secure environment with real-world tools for enterprise-grade agents.",Apache-2.0,2026-07-10T15:10:26Z,,,2026-07-10T17:33:26+00:00 -ale-0247,Modal Sandboxes,https://modal.com/docs/guide/sandboxes,external,modal.com,ok,200,https://modal.com/docs/guide/sandboxes,text/html,Sandboxes | Modal Docs,"This page is a high-level guide to Sandboxes, secure containers for executing untrusted user or agent code on Modal.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0248,Daytona,https://www.daytona.io/,external,www.daytona.io,ok,200,https://www.daytona.io/,text/html,Daytona - Secure Infrastructure for Running AI-Generated Code,"Deploy Al code with confidence using Daytona's lightning-fast infrastructure. 90ms environment creation, stateful operations, and enterprise-grade security.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0249,peerd,https://github.com/NotASithLord/peerd,external,github.com,ok,200,https://github.com/NotASithLord/peerd,text/html; charset=utf-8,"GitHub - NotASithLord/peerd: The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds peer-to-peer. BYOK, no backend, no telemetry. Ā· GitHub","The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds peer-to-peer. BYOK, no backend, no telemetry. - NotASithLord/peerd",NotASithLord/peerd,341,36,19,"The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds peer-to-peer. BYOK, no backend, no telemetry.",Apache-2.0,2026-07-10T16:42:42Z,,,2026-07-10T17:33:26+00:00 -ale-0250,When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents,https://arxiv.org/abs/2607.05189,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05189,text/html; charset=utf-8,[2607.05189] When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents,Abstract page for arXiv paper 2607.05189: When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents,,,,,,,,2607.05189,,2026-07-10T17:33:26+00:00 -ale-0251,Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses,https://arxiv.org/abs/2607.05029,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05029,text/html; charset=utf-8,[2607.05029] Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses,Abstract page for arXiv paper 2607.05029: Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses,,,,,,,,2607.05029,,2026-07-10T17:33:26+00:00 -ale-0252,Distributed Attacks in Persistent-State AI Control,https://arxiv.org/abs/2607.02514,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.02514,text/html; charset=utf-8,[2607.02514] Distributed Attacks in Persistent-State AI Control,Abstract page for arXiv paper 2607.02514: Distributed Attacks in Persistent-State AI Control,,,,,,,,2607.02514,,2026-07-10T17:33:26+00:00 -ale-0253,ElephantAgent: Contextual State Continuity in Agentic Systems,https://arxiv.org/abs/2607.01919,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.01919,text/html; charset=utf-8,[2607.01919] ElephantAgent: Contextual State Continuity in Agentic Systems,Abstract page for arXiv paper 2607.01919: ElephantAgent: Contextual State Continuity in Agentic Systems,,,,,,,,2607.01919,,2026-07-10T17:33:26+00:00 -ale-0254,Cloudflare security-audit-skill,https://github.com/cloudflare/security-audit-skill,external,github.com,ok,200,https://github.com/cloudflare/security-audit-skill,text/html; charset=utf-8,"GitHub - cloudflare/security-audit-skill: A coding-agent skill for multi-phase security audits with independently verified, machine-readable findings Ā· GitHub","A coding-agent skill for multi-phase security audits with independently verified, machine-readable findings - cloudflare/security-audit-skill",cloudflare/security-audit-skill,2413,176,1,"A coding-agent skill for multi-phase security audits with independently verified, machine-readable findings",MIT,2026-07-10T17:33:08Z,,,2026-07-10T17:33:26+00:00 -ale-0255,The Balkanization of Execution-Security Research for AI Coding Agents,https://arxiv.org/abs/2607.05743,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05743,text/html; charset=utf-8,"[2607.05743] The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities","Abstract page for arXiv paper 2607.05743: The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities",,,,,,,,2607.05743,,2026-07-10T17:33:26+00:00 -ale-0256,Context-to-Execution Integrity for LLM Agents,https://arxiv.org/abs/2607.06000,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06000,text/html; charset=utf-8,[2607.06000] Context-to-Execution Integrity for LLM Agents,Abstract page for arXiv paper 2607.06000: Context-to-Execution Integrity for LLM Agents,,,,,,,,2607.06000,,2026-07-10T17:33:26+00:00 -ale-0257,When Agents Remember Too Much: Memory Poisoning Attacks on Large Language Model Agents,https://arxiv.org/abs/2607.06595,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06595,text/html; charset=utf-8,[2607.06595] When Agents Remember Too Much: Memory Poisoning Attacks on Large Language Model Agents,Abstract page for arXiv paper 2607.06595: When Agents Remember Too Much: Memory Poisoning Attacks on Large Language Model Agents,,,,,,,,2607.06595,,2026-07-10T17:33:26+00:00 -ale-0258,Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents,https://arxiv.org/abs/2607.08395,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08395,text/html; charset=utf-8,[2607.08395] Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents,Abstract page for arXiv paper 2607.08395: Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents,,,,,,,,2607.08395,,2026-07-10T17:33:26+00:00 -ale-0259,Prismata: Confining Cross-Site Prompt Injection in Web Agents,https://arxiv.org/abs/2607.08147,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08147,text/html; charset=utf-8,[2607.08147] Prismata: Confining Cross-Site Prompt Injection in Web Agents,Abstract page for arXiv paper 2607.08147: Prismata: Confining Cross-Site Prompt Injection in Web Agents,,,,,,,,2607.08147,,2026-07-10T17:33:26+00:00 -ale-0260,TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories,https://arxiv.org/abs/2607.08400,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08400,text/html; charset=utf-8,[2607.08400] TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories,Abstract page for arXiv paper 2607.08400: TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories,,,,,,,,2607.08400,,2026-07-10T17:33:26+00:00 -ale-0261,Beyond Attack-Success Rate: Action-Graded Severity Scale for Tool-Using AI Agents,https://arxiv.org/abs/2607.07474,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07474,text/html; charset=utf-8,[2607.07474] Beyond Attack-Success Rate: Action-Graded Severity Scale for Tool-Using AI Agents,Abstract page for arXiv paper 2607.07474: Beyond Attack-Success Rate: Action-Graded Severity Scale for Tool-Using AI Agents,,,,,,,,2607.07474,,2026-07-10T17:33:26+00:00 -ale-0262,Beware of Agentic Botnets: Scalable Untargeted Promptware Attacks via Universal and Transferable Adversarial HalluSquatting,https://arxiv.org/abs/2607.07433,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07433,text/html; charset=utf-8,[2607.07433] Beware of Agentic Botnets: Scalable Untargeted Promptware Attacks via Universal and Transferable Adversarial HalluSquatting,Abstract page for arXiv paper 2607.07433: Beware of Agentic Botnets: Scalable Untargeted Promptware Attacks via Universal and Transferable Adversarial HalluSquatting,,,,,,,,2607.07433,,2026-07-10T17:33:26+00:00 -ale-0263,GitLost: How We Tricked GitHub's AI Agent into Leaking Private Repos,https://noma.security/blog/gitlost-how-we-tricked-githubs-ai-agent-into-leaking-private-repos/,external,noma.security,ok,200,https://noma.security/blog/gitlost-how-we-tricked-githubs-ai-agent-into-leaking-private-repos/,text/html; charset=UTF-8,GitLost: How We Tricked GitHubā€™s AI Agent into Leaking Private Repos - Noma Security,"TL;DR: Noma Labs discovered a critical prompt injection vulnerability within GitHubā€™s new Agentic Workflows, allowing an unauthenticated attacker to silently pull data from private repositories by posting a crafted GitHub Issue in a public repository belonging to the same organization as the private repositories. Noma Labs named the vulnerability GitLost. Introduction GitHub recently launched [ā€¦]",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0264,Effective Context Engineering for AI Agents,https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents,text/html; charset=utf-8,Effective context engineering for AI agents \ Anthropic,"Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0265,Agent Harnesses: the Infrastructure Layer Your LLM Agent Actually Needs,https://ninadpathak.com/blog/agent-harnesses/,external,ninadpathak.com,ok,200,https://ninadpathak.com/blog/agent-harnesses/,text/html; charset=utf-8,Agent Harnesses: the Infrastructure Layer Your Llm Agent Actually Needs | Ninad Pathak,"Every production AI agent needs a harness. Here is what one contains, why frameworks often are not enough, and how to build the layer that actually determines reliability.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0266,The Agent Loop Is the New OS,https://www.harness.io/blog/agent-loop-new-os,external,www.harness.io,ok,200,https://www.harness.io/blog/agent-loop-new-os,text/html; charset=utf-8,The Agent Loop Is the New OS | Harness Blog | Harness Share in X Share in Facebook Share in LinkedIn Search in ChatGpt Github icon LinkedIn icon Facebook icon Instagram icon Twitter icon,"The Harness MCP server treats the AI agent loop as an operating system, mapping the LLM to the CPU and the Context Window to RAM. Learn how this design uses 10 generic, composable tools to abstract complexity and keep the context window clean for higher-quality, cost-efficient AI agent reasoning. | Blog",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0267,Harness engineering for coding agent users,https://martinfowler.com/articles/harness-engineering.html,external,martinfowler.com,ok,200,https://martinfowler.com/articles/harness-engineering.html,text/html,Harness engineering for coding agent users,"A mental model for building trust in coding agents through feedforward guides, feedback sensors, and iterative harness engineering.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0268,Context Engineering,https://simonwillison.net/2025/Jun/27/context-engineering/,external,simonwillison.net,ok,200,https://simonwillison.net/2025/Jun/27/context-engineering/,text/html; charset=utf-8,Context engineering,The term context engineering has recently started to gain traction as a better alternative to prompt engineering. I like it. I think this one may have sticking power. Here's an ā€¦,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0269,Agentic Coding in 2026,https://sourcegraph.com/blog/agentic-coding,external,sourcegraph.com,ok,200,https://sourcegraph.com/blog/agentic-coding,text/html,Agentic Coding in 2026: A Practical Guide for Big Code | Sourcegraph,"Learn what agentic coding is, how AI coding agents work in real engineering orgs, and how to give them the codebase context they need to ship safely.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0270,Agentic AI State Management with ScyllaDB and LangGraph,https://www.scylladb.com/2026/04/08/agentic-ai-state-management-with-scylladb-and-langgraph/,external,www.scylladb.com,ok,200,https://www.scylladb.com/2026/04/08/agentic-ai-state-management-with-scylladb-and-langgraph/,text/html; charset=UTF-8,Agentic AI State Management with ScyllaDB and LangGraph - ScyllaDB,"How to combine LangGraph and ScyllaDB for durable state management, crash recovery, and a highly available backend for your agentic AI applications.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0271,Mem0,https://github.com/mem0ai/mem0,external,github.com,ok,200,https://github.com/mem0ai/mem0,text/html; charset=utf-8,GitHub - mem0ai/mem0: Universal memory layer for AI Agents Ā· GitHub,Universal memory layer for AI Agents. Contribute to mem0ai/mem0 development by creating an account on GitHub.,mem0ai/mem0,60558,7036,523,Universal memory layer for AI Agents,Apache-2.0,2026-07-10T17:22:31Z,,,2026-07-10T17:33:26+00:00 -ale-0272,Letta,https://github.com/letta-ai/letta,external,github.com,ok,200,https://github.com/letta-ai/letta,text/html; charset=utf-8,GitHub - letta-ai/letta: Platform for stateful agents: AI with advanced memory that can learn and self-improve over time. Ā· GitHub,Platform for stateful agents: AI with advanced memory that can learn and self-improve over time. - letta-ai/letta,letta-ai/letta,23731,2511,49,Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.,Apache-2.0,2026-07-10T11:49:56Z,,,2026-07-10T17:33:26+00:00 -ale-0273,Zep,https://github.com/getzep/zep,external,github.com,ok,200,https://github.com/getzep/zep,text/html; charset=utf-8,"GitHub - getzep/zep: Zep | Examples, Integrations, & More Ā· GitHub","Zep | Examples, Integrations, & More. Contribute to getzep/zep development by creating an account on GitHub.",getzep/zep,4739,637,14,"Zep | Examples, Integrations, & More",Apache-2.0,2026-07-10T12:26:44Z,,,2026-07-10T17:33:26+00:00 -ale-0274,LangMem,https://github.com/langchain-ai/langmem,external,github.com,ok,200,https://github.com/langchain-ai/langmem,text/html; charset=utf-8,GitHub - langchain-ai/langmem Ā· GitHub,Contribute to langchain-ai/langmem development by creating an account on GitHub.,langchain-ai/langmem,1549,175,57,,MIT,2026-07-10T07:57:50Z,,,2026-07-10T17:33:26+00:00 -ale-0275,Beads,https://github.com/steveyegge/beads,external,github.com,ok,200,https://github.com/gastownhall/beads,text/html; charset=utf-8,GitHub - gastownhall/beads: Beads - A memory upgrade for your coding agent Ā· GitHub,Beads - A memory upgrade for your coding agent. Contribute to gastownhall/beads development by creating an account on GitHub.,steveyegge/beads,25212,1682,428,Beads - A memory upgrade for your coding agent,MIT,2026-07-10T16:55:04Z,,,2026-07-10T17:33:26+00:00 -ale-0276,ARC: Active and Reflection-driven Context Management for Long-Horizon Agents,https://arxiv.org/abs/2601.12030,external,arxiv.org,ok,200,https://arxiv.org/abs/2601.12030,text/html; charset=utf-8,[2601.12030] ARC: Active and Reflection-driven Context Management for Long-Horizon Information Seeking Agents,Abstract page for arXiv paper 2601.12030: ARC: Active and Reflection-driven Context Management for Long-Horizon Information Seeking Agents,,,,,,,,2601.12030,,2026-07-10T17:33:26+00:00 -ale-0277,"Memory for Autonomous LLM Agents: Mechanisms, Evaluation, and Emerging Frontiers",https://arxiv.org/abs/2603.07670,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.07670,text/html; charset=utf-8,"[2603.07670] Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontiers","Abstract page for arXiv paper 2603.07670: Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontiers",,,,,,,,2603.07670,,2026-07-10T17:33:26+00:00 -ale-0278,"Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering",https://arxiv.org/abs/2604.08224,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.08224,text/html; charset=utf-8,"[2604.08224] Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering","Abstract page for arXiv paper 2604.08224: Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering",,,,,,,,2604.08224,,2026-07-10T17:33:26+00:00 -ale-0279,Meta Context Engineering via Agentic Skill Evolution,https://arxiv.org/abs/2601.21557,external,arxiv.org,ok,200,https://arxiv.org/abs/2601.21557,text/html; charset=utf-8,[2601.21557] Meta Context Engineering via Agentic Skill Evolution,Abstract page for arXiv paper 2601.21557: Meta Context Engineering via Agentic Skill Evolution,,,,,,,,2601.21557,,2026-07-10T17:33:26+00:00 -ale-0280,Are We Ready for an Agent-Native Memory System?,https://arxiv.org/abs/2606.24775,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.24775,text/html; charset=utf-8,[2606.24775] Are We Ready For An Agent-Native Memory System?,Abstract page for arXiv paper 2606.24775: Are We Ready For An Agent-Native Memory System?,,,,,,,,2606.24775,,2026-07-10T17:33:26+00:00 -ale-0281,Self-Evolving World Models for LLM Agent Planning,https://arxiv.org/abs/2606.30639,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.30639,text/html; charset=utf-8,[2606.30639] Self-Evolving World Models for LLM Agent Planning,Abstract page for arXiv paper 2606.30639: Self-Evolving World Models for LLM Agent Planning,,,,,,,,2606.30639,,2026-07-10T17:33:26+00:00 -ale-0282,Rethinking Continual Experience Internalization for Self-Evolving LLM Agents,https://arxiv.org/abs/2606.04703,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.04703,text/html; charset=utf-8,[2606.04703] Rethinking Continual Experience Internalization for Self-Evolving LLM Agents,Abstract page for arXiv paper 2606.04703: Rethinking Continual Experience Internalization for Self-Evolving LLM Agents,,,,,,,,2606.04703,,2026-07-10T17:33:26+00:00 -ale-0283,GenericAgent,https://github.com/lsdefine/GenericAgent,external,github.com,ok,200,https://github.com/lsdefine/GenericAgent,text/html; charset=utf-8,"GitHub - lsdefine/GenericAgent: Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption Ā· GitHub","Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption - lsdefine/GenericAgent",lsdefine/GenericAgent,13357,1539,170,"Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption",MIT,2026-07-10T17:23:15Z,,,2026-07-10T17:33:26+00:00 -ale-0284,Self-GC: Self-Governing Context for Long-Horizon LLM Agents,https://arxiv.org/abs/2607.00692,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.00692,text/html; charset=utf-8,[2607.00692] Self-GC: Self-Governing Context for Long-Horizon LLM Agents,Abstract page for arXiv paper 2607.00692: Self-GC: Self-Governing Context for Long-Horizon LLM Agents,,,,,,,,2607.00692,,2026-07-10T17:33:26+00:00 -ale-0285,CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents,https://arxiv.org/abs/2607.05378,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05378,text/html; charset=utf-8,[2607.05378] CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents,Abstract page for arXiv paper 2607.05378: CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents,,,,,,,,2607.05378,,2026-07-10T17:33:26+00:00 -ale-0286,SelfMem: Self-Optimizing Memory for AI Agents,https://arxiv.org/abs/2607.03726,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.03726,text/html; charset=utf-8,[2607.03726] SelfMem: Self-Optimizing Memory for AI Agents,Abstract page for arXiv paper 2607.03726: SelfMem: Self-Optimizing Memory for AI Agents,,,,,,,,2607.03726,,2026-07-10T17:33:26+00:00 -ale-0287,Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture,https://arxiv.org/abs/2607.04391,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.04391,text/html; charset=utf-8,[2607.04391] Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture,Abstract page for arXiv paper 2607.04391: Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture,,,,,,,,2607.04391,,2026-07-10T17:33:26+00:00 -ale-0288,"The Log Is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems",https://arxiv.org/abs/2605.21997,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.21997,text/html; charset=utf-8,"[2605.21997] The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems","Abstract page for arXiv paper 2605.21997: The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems",,,,,,,,2605.21997,,2026-07-10T17:33:26+00:00 -ale-0289,Agentics: Memorizing Session Transcripts Isn't Useful,https://12gramsofcarbon.com/p/agentics-memorizing-session-transcripts,external,12gramsofcarbon.com,ok,200,https://12gramsofcarbon.com/p/agentics-memorizing-session-transcripts,text/html; charset=utf-8,Agentics: Memorizing Session Transcripts Isn't Useful,"Keep track of artifacts, not scratch. Alt title: Claude, please stop trying to memorize random crap",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0290,Long-Running Agents,https://addyo.substack.com/p/long-running-agents,external,addyo.substack.com,ok,200,https://addyo.substack.com/p/long-running-agents,text/html; charset=utf-8,Long-running Agents - by Addy Osmani - Elevate,"A long-running AI agent can keep making progress over hours, days, or weeks.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0291,StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems,https://arxiv.org/abs/2607.05844,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05844,text/html; charset=utf-8,[2607.05844] StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems,Abstract page for arXiv paper 2607.05844: StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems,,,,,,,,2607.05844,,2026-07-10T17:33:26+00:00 -ale-0292,Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents,https://arxiv.org/abs/2607.08716,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08716,text/html; charset=utf-8,[2607.08716] Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents,Abstract page for arXiv paper 2607.08716: Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents,,,,,,,,2607.08716,,2026-07-10T17:33:26+00:00 -ale-0293,"What to Keep, What to Forget: A Rate-Distortion View of Memory Compaction",https://arxiv.org/abs/2607.08032,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08032,text/html; charset=utf-8,"[2607.08032] What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents","Abstract page for arXiv paper 2607.08032: What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents",,,,,,,,2607.08032,,2026-07-10T17:33:26+00:00 -ale-0294,A Hierarchical Memory Architecture Overcomes Context Limits in Long-Horizon Multi-Agent Modeling,https://arxiv.org/abs/2607.07666,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07666,text/html; charset=utf-8,[2607.07666] A hierarchical memory architecture overcomes context limits in long-horizon multi-agent computational modeling,Abstract page for arXiv paper 2607.07666: A hierarchical memory architecture overcomes context limits in long-horizon multi-agent computational modeling,,,,,,,,2607.07666,,2026-07-10T17:33:26+00:00 -ale-0295,SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents,https://arxiv.org/abs/2607.07676,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07676,text/html; charset=utf-8,[2607.07676] SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents,Abstract page for arXiv paper 2607.07676: SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents,,,,,,,,2607.07676,,2026-07-10T17:33:26+00:00 -ale-0296,How version control will evolve for the agent boom,https://entire.io/blog/how-version-control-will-evolve-for-the-agent-boom,external,entire.io,ok,200,https://entire.io/blog/how-version-control-will-evolve-for-the-agent-boom,text/html; charset=utf-8,How Version Control Will Evolve for the Agent Boom Ā· Entire,"To meet the demand of the agent boom, Git hosting must return to its original promise: a distributed network of many hosts.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0297,self-learning-skills,https://github.com/Kulaxyz/self-learning-skills,external,github.com,ok,200,https://github.com/Kulaxyz/self-learning-skills,text/html; charset=utf-8,"GitHub - Kulaxyz/self-learning-skills: A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won golden path in a session and harvest it into a reusable skill/rule for next time. Ā· GitHub","A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won golden path in a session and harvest it into a reusable skill/rule for next time. - Kulaxyz/self-learning-skills",Kulaxyz/self-learning-skills,834,28,2,"A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won golden path in a session and harvest it into a reusable skill/rule for next time.",MIT,2026-07-10T17:27:14Z,,,2026-07-10T17:33:26+00:00 -ale-0298,AutoGen,https://github.com/microsoft/autogen,external,github.com,ok,200,https://github.com/microsoft/autogen,text/html; charset=utf-8,GitHub - microsoft/autogen: A programming framework for agentic AI Ā· GitHub,A programming framework for agentic AI. Contribute to microsoft/autogen development by creating an account on GitHub.,microsoft/autogen,59640,8975,942,A programming framework for agentic AI,CC-BY-4.0,2026-07-10T17:27:16Z,,,2026-07-10T17:33:26+00:00 -ale-0299,Microsoft Agent Framework,https://github.com/microsoft/agent-framework,external,github.com,ok,200,https://github.com/microsoft/agent-framework,text/html; charset=utf-8,"GitHub - microsoft/agent-framework: A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET. Ā· GitHub","A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET. - microsoft/agent-framework",microsoft/agent-framework,12011,2019,657,"A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.",MIT,2026-07-10T17:19:30Z,,,2026-07-10T17:33:26+00:00 -ale-0300,LangGraph,https://github.com/langchain-ai/langgraph,external,github.com,ok,200,https://github.com/langchain-ai/langgraph,text/html; charset=utf-8,GitHub - langchain-ai/langgraph: Build resilient agents. Ā· GitHub,Build resilient agents. Contribute to langchain-ai/langgraph development by creating an account on GitHub.,langchain-ai/langgraph,36978,6206,616,Build resilient agents.,MIT,2026-07-10T17:25:06Z,,,2026-07-10T17:33:26+00:00 -ale-0301,CrewAI,https://github.com/crewAIInc/crewAI,external,github.com,ok,200,https://github.com/crewAIInc/crewAI,text/html; charset=utf-8,"GitHub - crewAIInc/crewAI: Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. Ā· GitHub","Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. - crewAIInc/crewAI",crewAIInc/crewAI,55299,7788,638,"Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.",MIT,2026-07-10T17:15:11Z,,,2026-07-10T17:33:26+00:00 -ale-0302,LlamaIndex Workflows,https://developers.llamaindex.ai/python/llamaagents/workflows/,external,developers.llamaindex.ai,ok,200,https://developers.llamaindex.ai/python/llamaagents/workflows/,text/html; charset=utf-8,Introduction | Developer Documentation,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0303,OpenAI Agents SDK handoffs,https://openai.github.io/openai-agents-python/handoffs/,external,openai.github.io,ok,200,https://openai.github.io/openai-agents-python/handoffs/,text/html; charset=utf-8,Handoffs - OpenAI Agents SDK,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0304,Agent Protocol,https://agentprotocol.ai/,external,agentprotocol.ai,ok,200,https://agentprotocol.ai/,text/html; charset=utf-8,AgentProtocol.ai ā€” A practical guide to AI agent communication standards.,"AgentProtocol.ai is an independent, vendor-neutral guide to AI agent communication standards ā€” MCP, A2A, Agent Protocol, AI agent APIs and agent interoperability.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0305,AgentKit,https://github.com/inngest/agent-kit,external,github.com,ok,200,https://github.com/inngest/agent-kit,text/html; charset=utf-8,GitHub - inngest/agent-kit: AgentKit: Build multi-agent networks in TypeScript with deterministic routing and rich tooling via MCP. Ā· GitHub,AgentKit: Build multi-agent networks in TypeScript with deterministic routing and rich tooling via MCP. - inngest/agent-kit,inngest/agent-kit,910,135,45,AgentKit: Build multi-agent networks in TypeScript with deterministic routing and rich tooling via MCP.,Apache-2.0,2026-07-08T12:34:37Z,,,2026-07-10T17:33:26+00:00 -ale-0306,deepagents,https://github.com/langchain-ai/deepagents,external,github.com,ok,200,https://github.com/langchain-ai/deepagents,text/html; charset=utf-8,GitHub - langchain-ai/deepagents: The batteries-included agent harness. Ā· GitHub,The batteries-included agent harness. Contribute to langchain-ai/deepagents development by creating an account on GitHub.,langchain-ai/deepagents,26060,3651,183,The batteries-included agent harness.,MIT,2026-07-10T16:53:54Z,,,2026-07-10T17:33:26+00:00 -ale-0307,Temporal for AI,https://temporal.io/solutions/ai,external,temporal.io,ok,200,https://temporal.io/solutions/ai,text/html; charset=utf-8,Temporal for AI | Temporal,"Temporal is a durable workflow platform that ensures AI applications run reliably, every time. Build faster, prevent failures, and stand out from the crowd.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0308,Restate,https://restate.dev/,external,restate.dev,ok,200,https://www.restate.dev/,text/html; charset=utf-8,Restate - Build innately resilient distributed apps,Restate is a lightweight runtime that lets developers build innately resilient distributed apps without the complexity tax.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0309,DBOS,https://www.dbos.dev/,external,www.dbos.dev,ok,200,https://www.dbos.dev/,text/html; charset=utf-8,DBOS | Durable Workflow Orchestration,"DBOS is an open source durable execution and workflow orchestration system that radically simplifies the development and operation of reliable, observable workflows.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0310,Composio Agent Orchestrator,https://github.com/ComposioHQ/agent-orchestrator,external,github.com,ok,200,https://github.com/AgentWrapper/agent-orchestrator,text/html; charset=utf-8,"GitHub - AgentWrapper/agent-orchestrator: Agentic orchestrator for parallel coding agents ā€” plans tasks, spawns agents, and autonomously handles CI fixes, merge conflicts, and code reviews. Ā· GitHub","Agentic orchestrator for parallel coding agents ā€” plans tasks, spawns agents, and autonomously handles CI fixes, merge conflicts, and code reviews. - AgentWrapper/agent-orchestrator",ComposioHQ/agent-orchestrator,8176,1163,440,"Agentic orchestrator for parallel coding agents ā€” plans tasks, spawns agents, and autonomously handles CI fixes, merge conflicts, and code reviews.",Apache-2.0,2026-07-10T17:30:43Z,,,2026-07-10T17:33:26+00:00 -ale-0311,Omnigent,https://github.com/omnigent-ai/omnigent,external,github.com,ok,200,https://github.com/omnigent-ai/omnigent,text/html; charset=utf-8,"GitHub - omnigent-ai/omnigent: Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents ā€” swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device. Ā· GitHub","Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents ā€” swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device. - omnigent-ai/omnigent",omnigent-ai/omnigent,6983,943,543,"Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents ā€” swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device.",Apache-2.0,2026-07-10T17:37:38Z,,,2026-07-10T17:33:26+00:00 -ale-0312,From Agent Loops to Structured Graphs: A Scheduler-Theoretic Framework for LLM Agent Execution,https://arxiv.org/abs/2604.11378,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.11378,text/html; charset=utf-8,[2604.11378] From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution,Abstract page for arXiv paper 2604.11378: From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution,,,,,,,,2604.11378,,2026-07-10T17:33:26+00:00 -ale-0313,Eve,https://github.com/vercel/eve,external,github.com,ok,200,https://github.com/vercel/eve,text/html; charset=utf-8,GitHub - vercel/eve: The Framework for Building Agents Ā· GitHub,The Framework for Building Agents. Contribute to vercel/eve development by creating an account on GitHub.,vercel/eve,3393,286,230,The Framework for Building Agents,Apache-2.0,2026-07-10T16:47:31Z,,,2026-07-10T17:33:26+00:00 -ale-0314,Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework,https://arxiv.org/abs/2603.11445,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.11445,text/html; charset=utf-8,[2603.11445] Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution,Abstract page for arXiv paper 2603.11445: Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution,,,,,,,,2603.11445,,2026-07-10T17:33:26+00:00 -ale-0315,From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents,https://arxiv.org/abs/2603.22386,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.22386,text/html; charset=utf-8,[2603.22386] From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents,Abstract page for arXiv paper 2603.22386: From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents,,,,,,,,2603.22386,,2026-07-10T17:33:26+00:00 -ale-0316,Agent-as-a-Router,https://github.com/LanceZPF/agent-as-a-router,external,github.com,ok,200,https://github.com/LanceZPF/agent-as-a-router,text/html; charset=utf-8,GitHub - LanceZPF/agent-as-a-router: The official implementations of Agent-as-a-Router: Agentic Model Routing for Coding Tasks. Ā· GitHub,The official implementations of Agent-as-a-Router: Agentic Model Routing for Coding Tasks. - LanceZPF/agent-as-a-router,LanceZPF/agent-as-a-router,395,14,0,The official implementations of Agent-as-a-Router: Agentic Model Routing for Coding Tasks.,MIT,2026-07-10T17:20:52Z,,,2026-07-10T17:33:26+00:00 -ale-0317,Amp: Custom Agents,https://ampcode.com/news/custom-agents,external,ampcode.com,ok,200,https://ampcode.com/news/custom-agents,text/html,Amp,"Plugins can now create agents, run them once, and keep talking to their threads.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0318,AgentsMesh,https://github.com/AgentsMesh/AgentsMesh,external,github.com,ok,200,https://github.com/AgentsMesh/AgentsMesh,text/html; charset=utf-8,"GitHub - AgentsMesh/AgentsMesh: The AI Agent Workforce Platform. Run a hundred AI coding agents across your own machines ā€” schedule, isolate, and steer them all from one console. Ā· GitHub","The AI Agent Workforce Platform. Run a hundred AI coding agents across your own machines ā€” schedule, isolate, and steer them all from one console. - AgentsMesh/AgentsMesh",AgentsMesh/AgentsMesh,2265,229,18,"The AI Agent Workforce Platform. Run a hundred AI coding agents across your own machines ā€” schedule, isolate, and steer them all from one console.",NOASSERTION,2026-07-10T09:51:31Z,,,2026-07-10T17:33:26+00:00 -ale-0319,Bernstein,https://github.com/sipyourdrink-ltd/bernstein,external,github.com,ok,200,https://github.com/sipyourdrink-ltd/bernstein,text/html; charset=utf-8,"GitHub - sipyourdrink-ltd/bernstein: Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run Ā· GitHub","Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run - sipyourdrink-ltd/bernstein",sipyourdrink-ltd/bernstein,653,59,20,"Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run",Apache-2.0,2026-07-10T14:47:00Z,,,2026-07-10T17:33:26+00:00 -ale-0320,Aeon,https://github.com/aaronjmars/aeon,external,github.com,ok,200,https://github.com/aaronjmars/aeon,text/html; charset=utf-8,"GitHub - aaronjmars/aeon: The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever. Ā· GitHub","The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever. - aaronjmars/aeon",aaronjmars/aeon,573,210,0,"The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever.",MIT,2026-07-09T19:35:02Z,,,2026-07-10T17:33:26+00:00 -ale-0321,h5i,https://github.com/h5i-dev/h5i,external,github.com,ok,200,https://github.com/h5i-dev/h5i,text/html; charset=utf-8,"GitHub - h5i-dev/h5i: Auditable workspaces for AI coding agents: sandboxed worktrees, conflict-free multi-agent orchestra, 95% lower token waste, and persistent memory. Ā· GitHub","Auditable workspaces for AI coding agents: sandboxed worktrees, conflict-free multi-agent orchestra, 95% lower token waste, and persistent memory. - h5i-dev/h5i",h5i-dev/h5i,458,34,30,"Auditable workspaces for AI coding agents: sandboxed worktrees, conflict-free multi-agent orchestra, 95% lower token waste, and persistent memory.",Apache-2.0,2026-07-10T15:52:54Z,,,2026-07-10T17:33:26+00:00 -ale-0322,SwarmResearch: Orchestrating Coding Agents for Open-Ended Discovery,https://arxiv.org/abs/2607.02807,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.02807,text/html; charset=utf-8,[2607.02807] SwarmResearch: Orchestrating Coding Agents for Open-Ended Discovery,Abstract page for arXiv paper 2607.02807: SwarmResearch: Orchestrating Coding Agents for Open-Ended Discovery,,,,,,,,2607.02807,,2026-07-10T17:33:26+00:00 -ale-0323,Scaling Long-Running Autonomous Coding,https://cursor.com/blog/scaling-agents,external,cursor.com,ok,200,https://cursor.com/blog/scaling-agents,text/html; charset=utf-8,Scaling long-running autonomous coding Ā· Cursor,We've been experimenting with running coding agents autonomously for weeks at a time.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0324,babysitter,https://github.com/a5c-ai/babysitter,external,github.com,ok,200,https://github.com/a5c-ai/babysitter,text/html; charset=utf-8,"GitHub - a5c-ai/babysitter: Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration Ā· GitHub","Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration - a5c-ai/babysitter",a5c-ai/babysitter,1509,86,97,"Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration",MIT,2026-07-10T17:25:20Z,,,2026-07-10T17:33:26+00:00 -ale-0325,claude-code-merge-queue,https://github.com/funador/claude-code-merge-queue,external,github.com,ok,200,https://github.com/funador/claude-code-merge-queue,text/html; charset=utf-8,GitHub - funador/claude-code-merge-queue: The local merge queue for parallel Claude Code agents. Ā· GitHub,The local merge queue for parallel Claude Code agents. - GitHub - funador/claude-code-merge-queue: The local merge queue for parallel Claude Code agents.,funador/claude-code-merge-queue,300,0,0,The local merge queue for parallel Claude Code agents.,MIT,2026-07-10T08:26:37Z,,,2026-07-10T17:33:26+00:00 -ale-0326,Devin can now manage Devins,https://cognition.com/blog/devin-can-now-manage-devins,external,cognition.com,ok,200,https://cognition.com/blog/devin-can-now-manage-devins,text/html; charset=utf-8,Devin can now Manage Devins | Cognition,"Devin can now break down large tasks and delegate them to a team of managed Devins, with each running in its own isolated VM in parallel.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0327,pilotfish,https://github.com/Nanako0129/pilotfish,external,github.com,ok,200,https://github.com/Nanako0129/pilotfish,text/html; charset=utf-8,"GitHub - Nanako0129/pilotfish: Multi-model orchestration layer for Claude Code ā€” the frontier model plans, cheaper models execute, verification guards quality. One-prompt install. Ā· GitHub","Multi-model orchestration layer for Claude Code ā€” the frontier model plans, cheaper models execute, verification guards quality. One-prompt install. - Nanako0129/pilotfish",Nanako0129/pilotfish,316,24,0,"Multi-model orchestration layer for Claude Code ā€” the frontier model plans, cheaper models execute, verification guards quality. One-prompt install.",MIT,2026-07-10T17:06:06Z,,,2026-07-10T17:33:26+00:00 -ale-0328,fable-advisor,https://github.com/DannyMac180/fable-advisor,external,github.com,ok,200,https://github.com/DannyMac180/fable-advisor,text/html; charset=utf-8,"GitHub - DannyMac180/fable-advisor: Claude Fable as an orchestrator for Opus, GPT and Grok Ā· GitHub","Claude Fable as an orchestrator for Opus, GPT and Grok - DannyMac180/fable-advisor",DannyMac180/fable-advisor,341,23,0,"Claude Fable as an orchestrator for Opus, GPT and Grok",MIT,2026-07-10T17:19:00Z,,,2026-07-10T17:33:26+00:00 -ale-0329,SWE-bench,https://www.swebench.com/,external,www.swebench.com,ok,200,https://www.swebench.com/,text/html; charset=utf-8,SWE-bench Leaderboards,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0330,SWE-bench: Can Language Models Resolve Real-World GitHub Issues?,https://arxiv.org/abs/2310.06770,external,arxiv.org,ok,200,https://arxiv.org/abs/2310.06770,text/html; charset=utf-8,[2310.06770] SWE-bench: Can Language Models Resolve Real-World GitHub Issues?,Abstract page for arXiv paper 2310.06770: SWE-bench: Can Language Models Resolve Real-World GitHub Issues?,,,,,,,,2310.06770,,2026-07-10T17:33:26+00:00 -ale-0331,SWE-bench Goes Live,https://arxiv.org/abs/2505.23419,external,arxiv.org,ok,200,https://arxiv.org/abs/2505.23419,text/html; charset=utf-8,[2505.23419] SWE-bench Goes Live!,Abstract page for arXiv paper 2505.23419: SWE-bench Goes Live!,,,,,,,,2505.23419,,2026-07-10T17:33:26+00:00 -ale-0332,Terminal-Bench,https://www.tbench.ai/,external,www.tbench.ai,ok,200,https://www.tbench.ai/,text/html; charset=utf-8,Terminal-Bench,A benchmark for terminal agents,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0333,Terminal-Bench repository,https://github.com/harbor-framework/terminal-bench,external,github.com,ok,200,https://github.com/harbor-framework/terminal-bench,text/html; charset=utf-8,GitHub - harbor-framework/terminal-bench: A benchmark for LLMs on complicated tasks in the terminal Ā· GitHub,A benchmark for LLMs on complicated tasks in the terminal - harbor-framework/terminal-bench,harbor-framework/terminal-bench,2436,554,317,A benchmark for LLMs on complicated tasks in the terminal,Apache-2.0,2026-07-10T15:22:35Z,,,2026-07-10T17:33:26+00:00 -ale-0334,AgentBench,https://arxiv.org/abs/2308.03688,external,arxiv.org,ok,200,https://arxiv.org/abs/2308.03688,text/html; charset=utf-8,[2308.03688] AgentBench: Evaluating LLMs as Agents,Abstract page for arXiv paper 2308.03688: AgentBench: Evaluating LLMs as Agents,,,,,,,,2308.03688,,2026-07-10T17:33:26+00:00 -ale-0335,WebArena,https://arxiv.org/abs/2307.13854,external,arxiv.org,ok,200,https://arxiv.org/abs/2307.13854,text/html; charset=utf-8,[2307.13854] WebArena: A Realistic Web Environment for Building Autonomous Agents,Abstract page for arXiv paper 2307.13854: WebArena: A Realistic Web Environment for Building Autonomous Agents,,,,,,,,2307.13854,,2026-07-10T17:33:26+00:00 -ale-0336,OSWorld,https://arxiv.org/abs/2404.07972,external,arxiv.org,ok,200,https://arxiv.org/abs/2404.07972,text/html; charset=utf-8,[2404.07972] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments,Abstract page for arXiv paper 2404.07972: OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments,,,,,,,,2404.07972,,2026-07-10T17:33:26+00:00 -ale-0337,ToolBench,https://arxiv.org/abs/2307.16789,external,arxiv.org,ok,200,https://arxiv.org/abs/2307.16789,text/html; charset=utf-8,[2307.16789] ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs,Abstract page for arXiv paper 2307.16789: ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs,,,,,,,,2307.16789,,2026-07-10T17:33:26+00:00 -ale-0338,GAIA,https://arxiv.org/abs/2311.12983,external,arxiv.org,ok,200,https://arxiv.org/abs/2311.12983,text/html; charset=utf-8,[2311.12983] GAIA: a benchmark for General AI Assistants,Abstract page for arXiv paper 2311.12983: GAIA: a benchmark for General AI Assistants,,,,,,,,2311.12983,,2026-07-10T17:33:26+00:00 -ale-0339,Tau-bench,https://arxiv.org/abs/2406.12045,external,arxiv.org,ok,200,https://arxiv.org/abs/2406.12045,text/html; charset=utf-8,[2406.12045] $Ļ„$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains,Abstract page for arXiv paper 2406.12045: $Ļ„$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains,,,,,,,,2406.12045,,2026-07-10T17:33:26+00:00 -ale-0340,VisualWebArena,https://arxiv.org/abs/2401.13649,external,arxiv.org,ok,200,https://arxiv.org/abs/2401.13649,text/html; charset=utf-8,[2401.13649] VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks,Abstract page for arXiv paper 2401.13649: VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks,,,,,,,,2401.13649,,2026-07-10T17:33:26+00:00 -ale-0341,AppWorld,https://arxiv.org/abs/2407.18901,external,arxiv.org,ok,200,https://arxiv.org/abs/2407.18901,text/html; charset=utf-8,[2407.18901] AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents,Abstract page for arXiv paper 2407.18901: AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents,,,,,,,,2407.18901,,2026-07-10T17:33:26+00:00 -ale-0342,Vending-Bench,https://arxiv.org/abs/2502.15840,external,arxiv.org,ok,200,https://arxiv.org/abs/2502.15840,text/html; charset=utf-8,[2502.15840] Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents,Abstract page for arXiv paper 2502.15840: Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents,,,,,,,,2502.15840,,2026-07-10T17:33:26+00:00 -ale-0343,Vending-Bench leaderboard,https://andonlabs.com/evals/vending-bench,external,andonlabs.com,ok,200,https://andonlabs.com/evals/vending-bench,text/html; charset=UTF-8,Vending-Bench: Testing long-term coherence in agents | Andon Labs,"How do agents act over very long horizons? We answer this by letting agents manage a simulated vending machine business. The agents need to handle ordering, inventory management, and pricing over long context horizons to successfully make money.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0344,SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios,https://arxiv.org/abs/2512.18470,external,arxiv.org,ok,200,https://arxiv.org/abs/2512.18470,text/html; charset=utf-8,[2512.18470] SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios,Abstract page for arXiv paper 2512.18470: SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios,,,,,,,,2512.18470,,2026-07-10T17:33:26+00:00 -ale-0345,EvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification,https://arxiv.org/abs/2604.01687,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.01687,text/html; charset=utf-8,[2604.01687] CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification,Abstract page for arXiv paper 2604.01687: CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification,,,,,,,,2604.01687,,2026-07-10T17:33:26+00:00 -ale-0346,SaaSBench: Coding Agents in Long-Horizon Enterprise SaaS Engineering,https://arxiv.org/abs/2605.17526,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.17526,text/html; charset=utf-8,[2605.17526] SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering,Abstract page for arXiv paper 2605.17526: SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering,,,,,,,,2605.17526,,2026-07-10T17:33:26+00:00 -ale-0347,RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades,https://arxiv.org/abs/2605.15846,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.15846,text/html; charset=utf-8,[2605.15846] RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades,Abstract page for arXiv paper 2605.15846: RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades,,,,,,,,2605.15846,,2026-07-10T17:33:26+00:00 -ale-0348,RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code,https://arxiv.org/abs/2503.07832,external,arxiv.org,ok,200,https://arxiv.org/abs/2503.07832,text/html; charset=utf-8,[2503.07832] RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code,Abstract page for arXiv paper 2503.07832: RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code,,,,,,,,2503.07832,,2026-07-10T17:33:26+00:00 -ale-0349,RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents,https://arxiv.org/abs/2606.22678,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.22678,text/html; charset=utf-8,[2606.22678] RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents,Abstract page for arXiv paper 2606.22678: RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents,,,,,,,,2606.22678,,2026-07-10T17:33:26+00:00 -ale-0350,SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks,https://arxiv.org/abs/2603.24755,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.24755,text/html; charset=utf-8,[2603.24755] SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks,Abstract page for arXiv paper 2603.24755: SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks,,,,,,,,2603.24755,,2026-07-10T17:33:26+00:00 -ale-0351,LongCLI-Bench: A Preliminary Benchmark for Long-horizon Agentic Programming in Command-Line Interfaces,https://arxiv.org/abs/2602.14337,external,arxiv.org,ok,200,https://arxiv.org/abs/2602.14337,text/html; charset=utf-8,[2602.14337] LongCLI-Bench: A Preliminary Benchmark and Study for Long-horizon Agentic Programming in Command-Line Interfaces,Abstract page for arXiv paper 2602.14337: LongCLI-Bench: A Preliminary Benchmark and Study for Long-horizon Agentic Programming in Command-Line Interfaces,,,,,,,,2602.14337,,2026-07-10T17:33:26+00:00 -ale-0352,Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?,https://arxiv.org/abs/2606.29920,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.29920,text/html; charset=utf-8,[2606.29920] Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?,Abstract page for arXiv paper 2606.29920: Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?,,,,,,,,2606.29920,,2026-07-10T17:33:26+00:00 -ale-0353,SentinelBench: A Benchmark for Long-Running Monitoring Agents,https://arxiv.org/abs/2606.05342,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.05342,text/html; charset=utf-8,[2606.05342] SentinelBench: A Benchmark for Long-Running Monitoring Agents,Abstract page for arXiv paper 2606.05342: SentinelBench: A Benchmark for Long-Running Monitoring Agents,,,,,,,,2606.05342,,2026-07-10T17:33:26+00:00 -ale-0354,SWE-Together: Evaluating Coding Agents in Interactive User Sessions,https://arxiv.org/abs/2606.29957,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.29957,text/html; charset=utf-8,[2606.29957] SWE-Together: Evaluating Coding Agents in Interactive User Sessions,Abstract page for arXiv paper 2606.29957: SWE-Together: Evaluating Coding Agents in Interactive User Sessions,,,,,,,,2606.29957,,2026-07-10T17:33:26+00:00 -ale-0355,The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break,https://arxiv.org/abs/2604.11978,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.11978,text/html; charset=utf-8,[2604.11978] The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break,Abstract page for arXiv paper 2604.11978: The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break,,,,,,,,2604.11978,,2026-07-10T17:33:26+00:00 -ale-0356,Beyond pass@1: A Reliability Science Framework for Long-Horizon LLM Agents,https://arxiv.org/abs/2603.29231,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.29231,text/html; charset=utf-8,[2603.29231] Beyond pass@1: A Reliability Science Framework for Long-Horizon LLM Agents,Abstract page for arXiv paper 2603.29231: Beyond pass@1: A Reliability Science Framework for Long-Horizon LLM Agents,,,,,,,,2603.29231,,2026-07-10T17:33:26+00:00 -ale-0357,SEAGym: An Evaluation Environment for Self-Evolving LLM Agents,https://arxiv.org/abs/2606.17546,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.17546,text/html; charset=utf-8,[2606.17546] SEAGym: An Evaluation Environment for Self-Evolving LLM Agents,Abstract page for arXiv paper 2606.17546: SEAGym: An Evaluation Environment for Self-Evolving LLM Agents,,,,,,,,2606.17546,,2026-07-10T17:33:26+00:00 -ale-0358,EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions,https://arxiv.org/abs/2605.24110,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.24110,text/html; charset=utf-8,[2605.24110] EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions,Abstract page for arXiv paper 2605.24110: EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions,,,,,,,,2605.24110,,2026-07-10T17:33:26+00:00 -ale-0359,On the Reliability of Computer Use Agents,https://arxiv.org/abs/2604.17849,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.17849,text/html; charset=utf-8,[2604.17849] On the Reliability of Computer Use Agents,Abstract page for arXiv paper 2604.17849: On the Reliability of Computer Use Agents,,,,,,,,2604.17849,,2026-07-10T17:33:26+00:00 -ale-0360,AgentLens: Revealing the Lucky Pass Problem in SWE-Agent Evaluation,https://arxiv.org/abs/2605.12925,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.12925,text/html; charset=utf-8,[2605.12925] AgentLens: Revealing The Lucky Pass Problem in SWE-Agent Evaluation,Abstract page for arXiv paper 2605.12925: AgentLens: Revealing The Lucky Pass Problem in SWE-Agent Evaluation,,,,,,,,2605.12925,,2026-07-10T17:33:26+00:00 -ale-0361,ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction,https://arxiv.org/abs/2601.21008,external,arxiv.org,ok,200,https://arxiv.org/abs/2601.21008,text/html; charset=utf-8,[2601.21008] ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction and Behavioral Rationality in Operations Research,Abstract page for arXiv paper 2601.21008: ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction and Behavioral Rationality in Operations Research,,,,,,,,2601.21008,,2026-07-10T17:33:26+00:00 -ale-0362,LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis,https://arxiv.org/abs/2605.30434,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.30434,text/html; charset=utf-8,[2605.30434] LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis,Abstract page for arXiv paper 2605.30434: LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis,,,,,,,,2605.30434,,2026-07-10T17:33:26+00:00 -ale-0363,MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks,https://arxiv.org/abs/2602.16313,external,arxiv.org,ok,200,https://arxiv.org/abs/2602.16313,text/html; charset=utf-8,[2602.16313] MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks,Abstract page for arXiv paper 2602.16313: MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks,,,,,,,,2602.16313,,2026-07-10T17:33:26+00:00 -ale-0364,Momento: Evaluating Persistent Memory and Reasoning with Multi-Session Agentic Conversations,https://arxiv.org/abs/2606.00832,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.00832,text/html; charset=utf-8,[2606.00832] Momento: Evaluating Persistent Memory and Reasoning with Multi-Session Agentic Conversations,Abstract page for arXiv paper 2606.00832: Momento: Evaluating Persistent Memory and Reasoning with Multi-Session Agentic Conversations,,,,,,,,2606.00832,,2026-07-10T17:33:26+00:00 -ale-0365,Ļ€-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows,https://arxiv.org/abs/2605.14678,external,arxiv.org,restricted,429,https://arxiv.org/abs/2605.14678,text/html,,,,,,,,,,2605.14678,restricted_or_rate_limited,2026-07-10T17:33:26+00:00 -ale-0366,Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation,https://arxiv.org/abs/2603.23638,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.23638,text/html; charset=utf-8,[2603.23638] Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment,Abstract page for arXiv paper 2603.23638: Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment,,,,,,,,2603.23638,,2026-07-10T17:33:26+00:00 -ale-0367,EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer,https://arxiv.org/abs/2607.05202,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05202,text/html; charset=utf-8,[2607.05202] EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer,Abstract page for arXiv paper 2607.05202: EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer,,,,,,,,2607.05202,,2026-07-10T17:33:26+00:00 -ale-0368,AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents,https://arxiv.org/abs/2607.02255,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.02255,text/html; charset=utf-8,[2607.02255] AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents,Abstract page for arXiv paper 2607.02255: AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents,,,,,,,,2607.02255,,2026-07-10T17:33:26+00:00 -ale-0369,Is Three the Magic Number? An Empirical Evaluation of LLM-Based Repair Loops,https://arxiv.org/abs/2607.05197,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05197,text/html; charset=utf-8,[2607.05197] Is Three the Magic Number? An Empirical Evaluation of LLM-Based Repair Loops,Abstract page for arXiv paper 2607.05197: Is Three the Magic Number? An Empirical Evaluation of LLM-Based Repair Loops,,,,,,,,2607.05197,,2026-07-10T17:33:26+00:00 -ale-0370,"DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks",https://arxiv.org/abs/2607.07946,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07946,text/html; charset=utf-8,"[2607.07946] DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks","Abstract page for arXiv paper 2607.07946: DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks",,,,,,,,2607.07946,,2026-07-10T17:33:26+00:00 -ale-0371,PERFOPT-Bench: Evaluating Coding Agents on Software Performance Optimization,https://arxiv.org/abs/2607.07744,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07744,text/html; charset=utf-8,[2607.07744] PERFOPT-Bench: Evaluating Coding Agents on Software Performance Optimization,Abstract page for arXiv paper 2607.07744: PERFOPT-Bench: Evaluating Coding Agents on Software Performance Optimization,,,,,,,,2607.07744,,2026-07-10T17:33:26+00:00 -ale-0372,Benchmarking coding agents on Databricks' multi-million line codebase,https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase,external,www.databricks.com,ok,200,https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase,text/html; charset=utf-8,Benchmarking Coding Agents on Databricksā€™ Multi-Million Line Codebase | Databricks Blog,"Databricks shares results from its internal coding benchmark, evaluating coding agents on a multi-million line codebase to optimize engineering cost and performance.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0373,Agentic Engineering: The Agent Loop,https://junpingyi.com/books/agentic-engineering/agent-loop/,external,junpingyi.com,ok,200,https://junpingyi.com/books/agentic-engineering/agent-loop/,text/html,Chapter 1: The Agent Loop ā€” Agentic Engineering: How to Build AI Agents Like Claude Code,Chapter 1: The Agent Loop from Agentic Engineering: How to Build AI Agents Like Claude Code,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0374,"The agent loop: ReAct, plan-and-execute, reflection",https://www.kunwar.page/chapter/067-the-agent-loop-react-plan-and-execute-reflection,external,www.kunwar.page,ok,200,https://www.kunwar.page/chapter/067-the-agent-loop-react-plan-and-execute-reflection,text/html; charset=utf-8,"Chapter 67: The agent loop: ReAct, plan-and-execute, reflection ā€” The Holy Grail Basic agent loop: generate, check for tool calls, execute tools and loop back, or return final answer on no tool call. ReAct interleaves Thought, Action, and Observation triplets; each Thought improves the next Action choice by externalizing reasoning. Agent cost vs single-shot: one LLM call versus 5-12 interleaved LLM and tool calls, showing the 10x cost and latency multiplier.",An agent is a loop of `model.generate()` calls with tool calls in between. The loop is the entire pattern,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0375,How to Build an Agent,https://ampcode.com/how-to-build-an-agent,external,ampcode.com,ok,200,https://ampcode.com/notes/how-to-build-an-agent,text/html,Amp,"Building a fully functional, code-editing agent in less than 400 lines.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0376,Agentic Coding Recommendations,https://lucumr.pocoo.org/2025/6/12/agentic-coding/,external,lucumr.pocoo.org,ok,200,https://lucumr.pocoo.org/2025/6/12/agentic-coding/,text/html; charset=utf-8,Agentic Coding Recommendations | Armin Ronacher's Thoughts and Writings,Current recommendations of agentic coding.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0377,Coding Agents 101: The Art of Actually Getting Things Done,https://devin.ai/agents101,external,devin.ai,ok,200,https://devin.ai/agents101,text/html; charset=utf-8,Coding Agents 101: The Art of Actually Getting Things Done,Coding Agents 101: The Art of Actually Getting Things Done,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0378,How Anthropic teams use Claude Code,https://claude.com/blog/how-anthropic-teams-use-claude-code,external,claude.com,ok,200,https://claude.com/blog/how-anthropic-teams-use-claude-code,text/html; charset=utf-8,How Anthropic teams use Claude Code | Claude by Anthropic,Teams across Anthropic use Claude Code for everything from debugging production issues and navigating unfamiliar codebases to building custom automation tools. Here's how. ā€,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0379,How Boris Uses Claude Code,https://howborisusesclaudecode.com/,external,howborisusesclaudecode.com,ok,200,https://howborisusesclaudecode.com/,text/html; charset=UTF-8,Boris Cherny's Claude Code Tips ā€” How He Actually Uses It (118+ Tips),"118+ tips from Boris Cherny, creator of Claude Code, on his daily workflow: CLAUDE.md, worktrees, plan mode, hooks, subagents, and more.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0380,Agent of the Day: Copilot Agent PR Analysis,https://github.github.com/gh-aw/blog/2026-05-26-agent-of-the-day/,external,github.github.com,ok,200,https://github.github.com/gh-aw/blog/2026-05-26-agent-of-the-day/,text/html; charset=utf-8,"Agent of the Day ā€“ May 26, 2026 | GitHub Agentic Workflows",Copilot Agent PR Analysis: a daily workflow that monitors GitHub Copilot coding agent performance across pull requests,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0381,"Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows",https://arxiv.org/abs/2607.07052,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07052,text/html; charset=utf-8,"[2607.07052] Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production","Abstract page for arXiv paper 2607.07052: Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production",,,,,,,,2607.07052,,2026-07-10T17:33:26+00:00 -ale-0382,Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems,https://arxiv.org/abs/2607.08010,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08010,text/html; charset=utf-8,[2607.08010] Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems,Abstract page for arXiv paper 2607.08010: Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems,,,,,,,,2607.08010,,2026-07-10T17:33:26+00:00 -ale-0383,AI Loop Engineering: Build Autonomous Agents with Claude Code /goal and Routines,https://www.sabrina.dev/p/loop-engineering-claude-code-goal-routines,external,www.sabrina.dev,ok,200,https://www.sabrina.dev/p/loop-engineering-claude-code-goal-routines,text/html; charset=utf-8,AI Loop Engineering: Build Autonomous Agents with Claude Code /goal + Routines,"What loop engineering means in 2026, how to use the Claude Code /goal command, and how to build your first autonomous AI agent with a routine.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0384,Resource entry template,templates/resource-entry.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/templates/resource-entry.md,,Resource entry template,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0385,Loop pattern template,templates/loop-pattern.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/templates/loop-pattern.md,,Loop pattern template,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0386,Loop contract schema,schemas/loop-contract.schema.json,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/schemas/loop-contract.schema.json,,Loop contract schema,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0387,Loop contract preview script,scripts/preview_loop_contract.py,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/scripts/preview_loop_contract.py,,Loop contract preview script,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0388,Translation guide,TRANSLATIONS.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/TRANSLATIONS.md,,Translation guide,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0389,Pattern library index,patterns/README.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/README.md,,Pattern library index,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0390,Example loop specs,examples/README.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/README.md,,Example loop specs,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0391,Loop contract library,examples/README.md#contract-library,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/README.md#contract-library,,Loop contract library,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0392,Runnable test-repair loop,examples/runnable/test-repair-loop.sh,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/runnable/test-repair-loop.sh,,Runnable test-repair loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0393,Runnable loop guide,examples/runnable/README.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/runnable/README.md,,Runnable loop guide,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0394,Loop gallery guide,gallery/README.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/README.md,,Loop gallery guide,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0395,Loop gallery template,gallery/template.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/template.md,,Loop gallery template,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0396,PR babysitter reference loop,gallery/pr-babysitter-reference.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/pr-babysitter-reference.md,,PR babysitter reference loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0397,CI repair reference loop,gallery/ci-repair-reference.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/ci-repair-reference.md,,CI repair reference loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0398,Docs drift reference loop,gallery/docs-drift-reference.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/docs-drift-reference.md,,Docs drift reference loop,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0399,Most Developers Do Not Need Agent Loops Yet,https://alphasignalai.substack.com/p/most-developers-do-not-need-agent,external,alphasignalai.substack.com,ok,200,https://alphasignalai.substack.com/p/most-developers-do-not-need-agent,text/html; charset=utf-8,Most Developers Do Not Need Agent Loops Yet,"The patterns were documented in 2024. Hereā€™s who it pays off for, and the four conditions that decide.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0400,Engineering Agentic Systems for Reliability,https://pruningmypothos.com/systems/engineering-agentic-systems-for-reliability/,external,pruningmypothos.com,ok,200,https://pruningmypothos.com/systems/engineering-agentic-systems-for-reliability/,text/html,Engineering Agentic Systems for Reliability | Sans Serif Systems,"A practical reliability model for agentic systems built around governed steps, verification, escalation, and observability.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0401,"Self-Correcting Agents: Reflexion, CRITIC, and ReAct Loops Compared",https://callsphere.ai/blog/self-correcting-agents-reflexion-critic-react-loops-compared-2026,external,callsphere.ai,ok,200,https://callsphere.ai/blog/self-correcting-agents-reflexion-critic-react-loops-compared-2026,text/html; charset=utf-8,"Self-Correcting Agents: Reflexion, CRITIC, and ReAct Loops Compared | CallSphere Blog","Three self-correction patterns dominate 2026 agent design. Side-by-side analysis of where each one wins, where each one fails, and how to combine them.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0402,How to Build an AI Agent Harness: A 2026 Complete Guide,https://atlan.com/know/how-to-build-ai-agent-harness/,external,atlan.com,ok,200,https://atlan.com/know/how-to-build-ai-agent-harness/,text/html,How to Build an AI Agent Harness: Step-by-Step Tutorial (2026),"Most agent harnesses fail at the data layer, not the loop. Build one the right way in 10 steps, with code and a done test for each. Start at Step 0.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0403,Harness Engineering vs Prompt Engineering vs Context Engineering Explained,https://medium.com/@visrow/harness-engineering-vs-prompt-engineering-vs-context-engineering-explained-0423b692c87d,external,medium.com,ok,200,https://medium.com/@visrow/harness-engineering-vs-prompt-engineering-vs-context-engineering-explained-0423b692c87d,text/html; charset=utf-8,"Medium Harness Engineering vs Prompt Engineering vs Context Engineering Explained | by Vishal Mysore | May, 2026 | Medium",Harness Engineering vs Prompt Engineering vs Context Engineering Explained Understanding the evolution from prompts and RAG to reliable AI agent runtime systems. Prompt Engineering tells the model ā€¦,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0404,Position: Coding Benchmarks Are Misaligned with Agentic Software Engineering,https://arxiv.org/abs/2606.17799,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.17799,text/html; charset=utf-8,[2606.17799] Position: Coding Benchmarks Are Misaligned with Agentic Software Engineering,Abstract page for arXiv paper 2606.17799: Position: Coding Benchmarks Are Misaligned with Agentic Software Engineering,,,,,,,,2606.17799,,2026-07-10T17:33:26+00:00 -ale-0405,Understanding the Challenges in Iterative Generative Optimization with LLMs,https://arxiv.org/abs/2603.23994,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.23994,text/html; charset=utf-8,[2603.23994] Understanding the Challenges in Iterative Generative Optimization with LLMs,Abstract page for arXiv paper 2603.23994: Understanding the Challenges in Iterative Generative Optimization with LLMs,,,,,,,,2603.23994,,2026-07-10T17:33:26+00:00 -ale-0406,The Illusion of Multi-Agent Advantage,https://arxiv.org/abs/2606.13003,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.13003,text/html; charset=utf-8,[2606.13003] The Illusion of Multi-Agent Advantage,Abstract page for arXiv paper 2606.13003: The Illusion of Multi-Agent Advantage,,,,,,,,2606.13003,,2026-07-10T17:33:26+00:00 -ale-0407,The Coming Loop,https://lucumr.pocoo.org/2026/6/23/the-coming-loop/,external,lucumr.pocoo.org,ok,200,https://lucumr.pocoo.org/2026/6/23/the-coming-loop/,text/html; charset=utf-8,The Coming Loop | Armin Ronacher's Thoughts and Writings,"Loops, harnesses, and why even loop skeptics may end up with them.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0408,"Loop Engineering, the Latest AI Buzzword, Still Needs Humans in the Loop",https://www.theregister.com/ai-and-ml/2026/06/24/loop-engineering-latest-ai-buzzword-still-needs-humans-in-the-loop/5261735,external,www.theregister.com,ok,200,https://www.theregister.com/ai-and-ml/2026/06/24/loop-engineering-latest-ai-buzzword-still-needs-humans-in-the-loop/5261735,text/html; charset=UTF-8,"Loop engineering, latest AI buzzword, still needs humans in the loop",Prompting less and automating more comes with a price,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0409,When Agents Do Not Stop: Uncovering Infinite Agentic Loops in LLM Agents,https://arxiv.org/abs/2607.01641,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.01641,text/html; charset=utf-8,[2607.01641] When Agents Do Not Stop: Uncovering Infinite Agentic Loops in LLM Agents,Abstract page for arXiv paper 2607.01641: When Agents Do Not Stop: Uncovering Infinite Agentic Loops in LLM Agents,,,,,,,,2607.01641,,2026-07-10T17:33:26+00:00 -ale-0410,The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents,https://arxiv.org/abs/2607.07436,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07436,text/html; charset=utf-8,[2607.07436] The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents,Abstract page for arXiv paper 2607.07436: The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents,,,,,,,,2607.07436,,2026-07-10T17:33:26+00:00 -ale-0411,Awesome Harness Engineering,https://github.com/ai-boost/awesome-harness-engineering,external,github.com,ok,200,https://github.com/ai-boost/awesome-harness-engineering,text/html; charset=utf-8,"GitHub - ai-boost/awesome-harness-engineering: Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration. Ā· GitHub","Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration. - ai-boost/awesome-harness-engineering",ai-boost/awesome-harness-engineering,2968,307,94,"Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.",NOASSERTION,2026-07-10T17:29:41Z,,,2026-07-10T17:33:26+00:00 -ale-0412,Awesome Harness Engineering,https://github.com/walkinglabs/awesome-harness-engineering,external,github.com,ok,200,https://github.com/walkinglabs/awesome-harness-engineering,text/html; charset=utf-8,GitHub - walkinglabs/awesome-harness-engineering: šŸ› ļø Awesome tools & guides for harness engineering. Ā· GitHub,šŸ› ļø Awesome tools & guides for harness engineering. - walkinglabs/awesome-harness-engineering,walkinglabs/awesome-harness-engineering,3566,285,24,šŸ› ļø Awesome tools & guides for harness engineering.,NOASSERTION,2026-07-10T14:19:44Z,,,2026-07-10T17:33:26+00:00 -ale-0413,Awesome Agent Harness,https://github.com/AutoJunjie/awesome-agent-harness,external,github.com,ok,200,https://github.com/AutoJunjie/awesome-agent-harness,text/html; charset=utf-8,GitHub - AutoJunjie/awesome-agent-harness Ā· GitHub,Contribute to AutoJunjie/awesome-agent-harness development by creating an account on GitHub.,AutoJunjie/awesome-agent-harness,479,43,16,,,2026-07-09T16:48:13Z,,,2026-07-10T17:33:26+00:00 -ale-0414,Awesome Context Engineering,https://github.com/Meirtz/Awesome-Context-Engineering,external,github.com,ok,200,https://github.com/Meirtz/Awesome-Context-Engineering,text/html; charset=utf-8,"GitHub - Meirtz/Awesome-Context-Engineering: šŸ”„ Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents. Ā· GitHub","šŸ”„ Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents. - Meirtz/Awesome-Context-Engineering",Meirtz/Awesome-Context-Engineering,3238,256,46,"šŸ”„ Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents.",MIT,2026-07-10T16:41:47Z,,,2026-07-10T17:33:26+00:00 -ale-0415,Awesome Prompt Engineering,https://github.com/promptslab/Awesome-Prompt-Engineering,external,github.com,ok,200,https://github.com/promptslab/Awesome-Prompt-Engineering,text/html; charset=utf-8,"GitHub - promptslab/Awesome-Prompt-Engineering: This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc Ā· GitHub","This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc - GitHub - promptslab/Awesome-Prompt-Engineering: This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc",promptslab/Awesome-Prompt-Engineering,6148,723,88,"This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc",Apache-2.0,2026-07-10T16:16:38Z,,,2026-07-10T17:33:26+00:00 -ale-0416,Awesome LLM Agents,https://github.com/kaushikb11/awesome-llm-agents,external,github.com,ok,200,https://github.com/kaushikb11/awesome-llm-agents,text/html; charset=utf-8,GitHub - kaushikb11/awesome-llm-agents: A curated list of awesome LLM agents frameworks. Ā· GitHub,A curated list of awesome LLM agents frameworks. Contribute to kaushikb11/awesome-llm-agents development by creating an account on GitHub.,kaushikb11/awesome-llm-agents,1528,328,160,A curated list of awesome LLM agents frameworks.,,2026-07-10T04:53:05Z,,,2026-07-10T17:33:26+00:00 -ale-0417,Awesome AI Agents,https://github.com/e2b-dev/awesome-ai-agents,external,github.com,ok,200,https://github.com/e2b-dev/awesome-ai-agents,text/html; charset=utf-8,GitHub - e2b-dev/awesome-ai-agents: A list of AI autonomous agents Ā· GitHub,A list of AI autonomous agents. Contribute to e2b-dev/awesome-ai-agents development by creating an account on GitHub.,e2b-dev/awesome-ai-agents,28682,3130,825,A list of AI autonomous agents,NOASSERTION,2026-07-10T16:46:08Z,,,2026-07-10T17:33:26+00:00 -ale-0418,Awesome CLI Coding Agents,https://github.com/bradAGI/awesome-cli-coding-agents,external,github.com,ok,200,https://github.com/bradAGI/awesome-cli-coding-agents,text/html; charset=utf-8,"GitHub - bradAGI/awesome-cli-coding-agents: Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure. Ā· GitHub","Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure. - GitHub - bradAGI/awesome-cli-coding-agents: Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure.",bradAGI/awesome-cli-coding-agents,785,208,39,"Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure.",,2026-07-10T17:36:59Z,,,2026-07-10T17:33:26+00:00 -ale-0419,Awesome Self-Evolving Agents,https://github.com/XMUDeepLIT/Awesome-Self-Evolving-Agents,external,github.com,ok,200,https://github.com/XMUDeepLIT/Awesome-Self-Evolving-Agents,text/html; charset=utf-8,"GitHub - XMUDeepLIT/Awesome-Self-Evolving-Agents: A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents. Ā· GitHub","A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents. - XMUDeepLIT/Awesome-Self-Evolving-Agents",XMUDeepLIT/Awesome-Self-Evolving-Agents,320,19,4,"A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents.",,2026-07-10T08:23:13Z,,,2026-07-10T17:33:26+00:00 -ale-0420,Awesome AI Agent Papers,https://github.com/VoltAgent/awesome-ai-agent-papers,external,github.com,ok,200,https://github.com/VoltAgent/awesome-ai-agent-papers,text/html; charset=utf-8,"GitHub - VoltAgent/awesome-ai-agent-papers: A curated collection of AI agent research papers released in 2026, covering agent engineering, memory, evaluation, workflows, and autonomous systems. Ā· GitHub","A curated collection of AI agent research papers released in 2026, covering agent engineering, memory, evaluation, workflows, and autonomous systems. - VoltAgent/awesome-ai-agent-papers",VoltAgent/awesome-ai-agent-papers,1555,164,0,"A curated collection of AI agent research papers released in 2026, covering agent engineering, memory, evaluation, workflows, and autonomous systems.",MIT,2026-07-10T17:33:28Z,,,2026-07-10T17:33:26+00:00 -ale-0421,awesome-ralph,https://github.com/snwfdhmp/awesome-ralph,external,github.com,ok,200,https://github.com/snwfdhmp/awesome-ralph,text/html; charset=utf-8,"GitHub - snwfdhmp/awesome-ralph: A curated list of resources about Ralph, the AI coding technique that runs AI coding agents in automated loops until specifications are fulfilled. Ā· GitHub","A curated list of resources about Ralph, the AI coding technique that runs AI coding agents in automated loops until specifications are fulfilled. - snwfdhmp/awesome-ralph",snwfdhmp/awesome-ralph,910,71,12,"A curated list of resources about Ralph, the AI coding technique that runs AI coding agents in automated loops until specifications are fulfilled.",,2026-07-07T13:04:16Z,,,2026-07-10T17:33:26+00:00 -ale-0422,Landing page,https://chaoyue0307.github.io/awesome-loop-engineering/,external,chaoyue0307.github.io,ok,200,https://chaoyue0307.github.io/awesome-loop-engineering/,text/html; charset=utf-8,Awesome Loop Engineering,"A curated field guide to Loop Engineering: patterns, loop contracts, and runnable examples for designing recurring AI agent and coding-agent systems above prompt, context, and harness engineering.",,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0423,Hugging Face dataset mirror,https://huggingface.co/datasets/cy0307/awesome-loop-engineering,external,huggingface.co,ok,200,https://huggingface.co/datasets/cy0307/awesome-loop-engineering,text/html; charset=utf-8,cy0307/awesome-loop-engineering Ā· Datasets at Hugging Face,Weā€™re on a journey to advance and democratize artificial intelligence through open source and open science.,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0424,Landing page source,docs/index.html,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/docs/index.html,,Landing page source,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0425,Sitemap,docs/sitemap.xml,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/docs/sitemap.xml,,Sitemap,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0426,Robots file,docs/robots.txt,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/docs/robots.txt,,Robots file,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0427,Roadmap,ROADMAP.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/ROADMAP.md,,Roadmap,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0428,Launch article,posts/launch.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/posts/launch.md,,Launch article,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0429,Discussion guide,meta/DISCUSSIONS.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/meta/DISCUSSIONS.md,,Discussion guide,,,,,,,,,,,2026-07-10T17:33:26+00:00 -ale-0430,Show your Loop Engineering patterns,https://github.com/ChaoYue0307/awesome-loop-engineering/discussions/2,external,github.com,ok,200,https://github.com/ChaoYue0307/awesome-loop-engineering/discussions/2,text/html; charset=utf-8,Show your Loop Engineering patterns Ā· ChaoYue0307/awesome-loop-engineering Ā· Discussion #2 Ā· GitHub,Show your Loop Engineering patterns,ChaoYue0307/awesome-loop-engineering,22,2,5,"Loop Engineering: a curated field guide to designing recurring AI agent and coding-agent loops ā€” patterns, loop contracts, runnable examples, and resources above prompt, context, and harness engineering.",CC0-1.0,2026-07-10T07:18:20Z,,,2026-07-10T17:33:26+00:00 +ale-0001,Canonical Definition,DEFINITION.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/DEFINITION.md,,Canonical Definition,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0002,Loop Engineering Manifesto,MANIFESTO.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/MANIFESTO.md,,Loop Engineering Manifesto,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0003,Loop Engineering Taxonomy,TAXONOMY.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/TAXONOMY.md,,Loop Engineering Taxonomy,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0004,Loop Engineering Anti-Patterns,ANTI-PATTERNS.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/ANTI-PATTERNS.md,,Loop Engineering Anti-Patterns,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0005,Comparison Guide,COMPARISON.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/COMPARISON.md,,Comparison Guide,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0006,Sourced Signals And Quotes,QUOTES.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/QUOTES.md,,Sourced Signals And Quotes,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0007,Outreach Kit,meta/OUTREACH.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/meta/OUTREACH.md,,Outreach Kit,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0008,Loop Engineering,https://addyosmani.com/blog/loop-engineering/,external,addyosmani.com,ok,200,https://addyosmani.com/blog/loop-engineering/,text/html; charset=UTF-8,AddyOsmani.com - Loop Engineering,You don't really need to be good at prompting anymore. The thing to get good at is the loop that does the prompting for you. It's five building blocks plus s...,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0009,Loop Engineering,https://addyo.substack.com/p/loop-engineering,external,addyo.substack.com,ok,200,https://addyo.substack.com/p/loop-engineering,text/html; charset=utf-8,Loop Engineering - by Addy Osmani - Elevate,Loop engineering is replacing yourself as the person who prompts the agent.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0010,Peter Steinberger on designing loops,https://x.com/steipete/status/2063697162748260627,external,x.com,ok,200,https://x.com/steipete/status/2063697162748260627,text/html; charset=UTF-8,"Peter Steinberger šŸ¦ž on X: ""Hereā€™s your monthly reminder that you shouldnā€™t be prompting coding agents anymore. You should be designing loops that prompt your agents."" / X",Hereā€™s your monthly reminder that you shouldnā€™t be prompting coding agents anymore. You should be designing loops that prompt your agents.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0011,Boris Cherny: five tips for running Opus autonomously for hours or days,https://x.com/bcherny/status/2063792263067754658,external,x.com,ok,200,https://x.com/bcherny/status/2063792263067754658,text/html; charset=UTF-8,"Boris Cherny on X: ""Seeing a number of benchmarks showing Opus is the best model for long-running work. Five tips for running Opus autonomously for hours/days: 1. Use auto mode for permissions, so Claude doesnā€™t ask for approval 2. Use dynamic workflows, to have Claude orchestrate"" / X","Seeing a number of benchmarks showing Opus is the best model for long-running work. Five tips for running Opus autonomously for hours/days: 1. Use auto mode for permissions, so Claude doesnā€™t ask for approval 2. Use dynamic workflows, to have Claude orchestrate",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0012,Loop Engineering,https://cobusgreyling.substack.com/p/loop-engineering,external,cobusgreyling.substack.com,ok,200,https://cobusgreyling.substack.com/p/loop-engineering,text/html; charset=utf-8,Loop Engineering,The core of Loop Engineering,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0013,Loop Engineering: The Guide for AI Agents,https://lushbinary.com/blog/loop-engineering-ai-coding-agents-guide/,external,lushbinary.com,ok,200,https://lushbinary.com/blog/loop-engineering-ai-coding-agents-guide/,text/html,Loop Engineering: The Guide for AI Agents | Lushbinary,"Loop engineering means designing the systems that prompt your AI agents, not prompting by hand. The 5 building blocks, Claude Code & Codex commands, and risks. Updated June 2026.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0014,Stop Prompting. Design the Loop.,https://www.pulumi.com/blog/stop-prompting-design-the-loop/,external,www.pulumi.com,ok,200,https://www.pulumi.com/blog/stop-prompting-design-the-loop/,text/html; charset=utf-8,Stop Prompting. Design the Loop. | Pulumi Blog,"The unit of work moved from the prompt to the loop. The five pieces of loop engineering, the memory that makes it compound, and what it won't do for you.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0015,"Writing Loops, Not Prompts, Explained",https://rico.codes/loops-not-prompts,external,rico.codes,ok,200,https://rico.codes/loops-not-prompts,text/html; charset=utf-8,"Writing Loops, Not Prompts, Explained | rico.codes","Loop engineering is not about abandoning prompts. It is about moving repeated steering work into verifiable systems so attention can stay on judgment, review, and taste.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0016,Loop Engineering: A Guide for Engineers and Practitioners,https://medium.com/@adnanmasood/loop-engineering-a-guide-for-engineers-and-practitioners-893bb65ea943,external,medium.com,ok,200,https://medium.com/@adnanmasood/loop-engineering-a-guide-for-engineers-and-practitioners-893bb65ea943,text/html; charset=utf-8,"Medium Loop Engineering: A Guide for Engineers and Practitioners | by Adnan Masood, PhD. | Jun, 2026 | Medium","Loop engineering: designing the control system that prompts, verifies, and stops AI agents in production. A field guide for engineers.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0017,"Loop Engineering: When Generation Gets Cheap, Judgment Gets Expensive",https://sderosiaux.substack.com/p/loop-engineering-cheap-generation,external,sderosiaux.substack.com,ok,200,https://sderosiaux.substack.com/p/loop-engineering-cheap-generation,text/html; charset=utf-8,"Loop Engineering: When Generation Gets Cheap, Judgment Gets Expensive","Agentic loops make code, plans, and PRs abundant. The scarce part is knowing what is right.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0018,Andrew Ng on Loop Engineering and the Three Loops of AI-Native Product Development,https://x.com/AndrewYNg/status/2071988145667928442,external,x.com,ok,200,https://x.com/AndrewYNg/status/2071988145667928442,text/html; charset=UTF-8,"Andrew Ng on X: ""ā€œLoop engineeringā€ is a hot buzzphrase after mentions of it by Boris Cherny (Claude Codeā€™s creator) and Peter Steinberger (OpenClaw's creator) went viral on social media. Loops are now a key part of how we get AI agents to iterate at length to build software. In this letter, Iā€™d https://t.co/bhuRw8lrFC"" / X","ā€œLoop engineeringā€ is a hot buzzphrase after mentions of it by Boris Cherny (Claude Codeā€™s creator) and Peter Steinberger (OpenClaw's creator) went viral on social media. Loops are now a key part of how we get AI agents to iterate at length to build software. In this letter, Iā€™d",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0019,From Prompting Agents to Loop Engineering,https://x.com/omarsar0/status/2068008743153832264,external,x.com,ok,200,https://x.com/omarsar0/status/2068008743153832264,text/html; charset=UTF-8,,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0020,I Now Just Write Loops To Prompt Claude Code: Claude Code Creator Boris Cherny,https://officechai.com/ai/i-now-just-write-loops-to-prompt-claude-code-claude-code-creator-boris-cherny/,external,officechai.com,ok,200,https://officechai.com/ai/i-now-just-write-loops-to-prompt-claude-code-claude-code-creator-boris-cherny/,text/html; charset=UTF-8,I Now Just Write Loops To Prompt Claude Code: Claude Code Creator Boris Cherny,"The definition of top tier coding is changing month-on-month in the AI era. Boris Cherny, the creator of Claude Code at Anthropic, has...",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0021,My Lord! AI Programming Undergoes Another Major Shift,https://eu.36kr.com/en/p/3844224911346184,external,eu.36kr.com,ok,200,https://eu.36kr.com/en/p/3844224911346184,text/html; charset=utf-8,My Lord! AI Programming Undergoes Another Major Shift: Claude Code Father & Lobster Founder Endorse New Paradigm - Could It Kill Prompt Engineering?,Stop writing prompts for programming agents now.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0022,The Anthropic leader who built Claude Code ditched prompting - now he writes loops,https://thenewstack.io/loop-engineering/,external,thenewstack.io,ok,200,https://thenewstack.io/loop-engineering/,text/html; charset=UTF-8,The Anthropic leader who built Claude Code says he ditched prompting ā€” now he just writes loops. - The New Stack,Loop engineering ā€” the practice of designing automated agent workflows instead of prompting manually ā€” is reshaping how developers use Claude Code and OpenAI Codex in 2026.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0023,Engineering for Agents That Never Sleep,https://nader.substack.com/p/engineering-for-agents-that-never,external,nader.substack.com,ok,200,https://nader.substack.com/p/engineering-for-agents-that-never,text/html; charset=utf-8,Engineering for Agents That Never Sleep - by Nader Dabit,Originally posted on X.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0024,Loop Engineering Orange Book,https://github.com/alchaincyf/loop-engineering-orange-book,external,github.com,ok,200,https://github.com/alchaincyf/loop-engineering-orange-book,text/html; charset=utf-8,GitHub - alchaincyf/loop-engineering-orange-book: åˆ«å†é—®ęˆ‘ä»€ä¹ˆę˜Æ Loop Engineering ā€” ę©™ēš®ä¹¦ē³»åˆ—怂A plain-language guide to loop engineering (äø­ę–‡ + English PDF). Free. Ā· GitHub,åˆ«å†é—®ęˆ‘ä»€ä¹ˆę˜Æ Loop Engineering ā€” ę©™ēš®ä¹¦ē³»åˆ—怂A plain-language guide to loop engineering (äø­ę–‡ + English PDF). Free. - alchaincyf/loop-engineering-orange-book,alchaincyf/loop-engineering-orange-book,988,97,0,åˆ«å†é—®ęˆ‘ä»€ä¹ˆę˜Æ Loop Engineering ā€” ę©™ēš®ä¹¦ē³»åˆ—怂A plain-language guide to loop engineering (äø­ę–‡ + English PDF). Free.,NOASSERTION,2026-07-12T08:30:39Z,,,2026-07-12T10:56:07+00:00 +ale-0025,How I AI: How to Write AI Agent Loops in Claude Code and Codex,https://www.lennysnewsletter.com/p/how-i-ai-how-to-write-ai-agent-loops,external,www.lennysnewsletter.com,ok,200,https://www.lennysnewsletter.com/p/how-i-ai-how-to-write-ai-agent-loops,text/html; charset=utf-8,šŸŽ™ļø How I AI: How to write AI agent loops in Claude Code and Codex + How Claude Mythos found a 15-year-old bug in Mozilla Firefox | Brian Grinstead,"Your weekly listens from How I AI, part of the Lennyā€™s Podcast Network",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0026,PR babysitter,patterns/pr-babysitter.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/pr-babysitter.md,,PR babysitter,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0027,CI repair loop,patterns/ci-repair-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/ci-repair-loop.md,,CI repair loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0028,Docs drift collector,patterns/docs-drift-collector.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/docs-drift-collector.md,,Docs drift collector,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0029,Deploy verifier,patterns/deploy-verifier.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/deploy-verifier.md,,Deploy verifier,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0030,Feedback clusterer,patterns/feedback-clusterer.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/feedback-clusterer.md,,Feedback clusterer,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0031,Dependency triage loop,patterns/dependency-triage-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/dependency-triage-loop.md,,Dependency triage loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0032,Evaluation regression loop,patterns/evaluation-regression-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/evaluation-regression-loop.md,,Evaluation regression loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0033,Security review loop,patterns/security-review-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/security-review-loop.md,,Security review loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0034,Cost-control loop,patterns/cost-control-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/cost-control-loop.md,,Cost-control loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0035,Bug hunting loop,patterns/bug-hunting-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/bug-hunting-loop.md,,Bug hunting loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0036,Enterprise approval loop,patterns/enterprise-approval-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/enterprise-approval-loop.md,,Enterprise approval loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0037,Incident response loop,patterns/incident-response-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/incident-response-loop.md,,Incident response loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0038,Data-quality loop,patterns/data-quality-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/data-quality-loop.md,,Data-quality loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0039,Release-note loop,patterns/release-note-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/release-note-loop.md,,Release-note loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0040,Model-routing loop,patterns/model-routing-loop.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/model-routing-loop.md,,Model-routing loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0041,Automations - Codex app,https://developers.openai.com/codex/app/automations,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/automations?surface=app,text/html; charset=utf-8,Scheduled tasks | ChatGPT Learn,Schedule recurring tasks in ChatGPT,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0042,Follow a goal - Codex use cases,https://developers.openai.com/codex/use-cases/follow-goals,external,developers.openai.com,ok,200,https://learn.chatgpt.com/use-cases/follow-goals,text/html; charset=utf-8,Follow a goal | ChatGPT use cases,Use `/goal` when a task needs Codex to keep working across turns toward a verifiable stopping condition.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0043,Worktrees - Codex app,https://developers.openai.com/codex/app/worktrees,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/environments/git-worktrees,text/html; charset=utf-8,Worktrees | ChatGPT Learn,Use Git worktrees in Codex in the ChatGPT desktop app to run tasks in parallel,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0044,Prompting - Codex,https://developers.openai.com/codex/prompting,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/prompting,text/html; charset=utf-8,Prompting | ChatGPT Learn,"Write useful prompts for Chat, ChatGPT Work, and Codex",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0045,Customization - Codex,https://developers.openai.com/codex/concepts/customization,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/customization/overview,text/html; charset=utf-8,Customization | ChatGPT Learn,"How to customize Codex with project guidance, skills, MCP, and subagents",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0046,Agent Skills - Codex,https://developers.openai.com/codex/skills,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/build-skills,text/html; charset=utf-8,Build skills | ChatGPT Learn,Give Codex new capabilities and expertise,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0047,Plugins - Codex,https://developers.openai.com/codex/plugins,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/plugins,text/html; charset=utf-8,Plugins | ChatGPT Learn,"Browse, install, and use plugins in ChatGPT and Codex clients",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0048,dotskills,https://github.com/vincentkoc/dotskills,external,github.com,ok,200,https://github.com/vincentkoc/dotskills,text/html; charset=utf-8,"GitHub - vincentkoc/dotskills: šŸ™ A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns. Ā· GitHub","šŸ™ A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns. - vincentkoc/dotskills",vincentkoc/dotskills,97,9,8,"šŸ™ A curated set of Codex and OpenClaw skills for workflow automation, technical debugging, and agent-assisted development patterns.",MIT,2026-07-11T23:54:06Z,,,2026-07-12T10:56:07+00:00 +ale-0049,Slash commands in Codex CLI,https://developers.openai.com/codex/cli/slash-commands,external,developers.openai.com,ok,200,https://learn.chatgpt.com/docs/developer-commands?surface=cli,text/html; charset=utf-8,Developer commands | ChatGPT Learn,Reference for commands and slash commands in Codex developer surfaces,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0050,Autonomous Loops,https://claudecodeguide.dev/docs/patterns/autonomous-loops,external,claudecodeguide.dev,ok,200,https://claudecodeguide.dev/docs/patterns/autonomous-loops,text/html; charset=utf-8,Claude Code Autonomous Loops | Claude Code Guide,"Point Claude Code at a problem, walk away, come back to a green build. Task templates, kill switches, and why boundaries matter more than anything else.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0051,Claude Code Glossary,https://code.claude.com/docs/en/glossary.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/glossary.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0052,Keep Claude working toward a goal,https://code.claude.com/docs/en/goal,external,code.claude.com,ok,200,https://code.claude.com/docs/en/goal,text/html; charset=utf-8,Keep Claude working toward a goal - Claude Code Docs,Set a completion condition with /goal and Claude keeps working across turns until the condition is met.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0053,Run prompts on a schedule,https://code.claude.com/docs/en/scheduled-tasks,external,code.claude.com,ok,200,https://code.claude.com/docs/en/scheduled-tasks,text/html; charset=utf-8,Run prompts on a schedule - Claude Code Docs,"Use /loop and the cron scheduling tools to run prompts repeatedly, poll for status, or set one-time reminders within a Claude Code session.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0054,Automate work with routines,https://code.claude.com/docs/en/routines,external,code.claude.com,ok,200,https://code.claude.com/docs/en/routines,text/html; charset=utf-8,Automate work with routines - Claude Code Docs,"Put Claude Code on autopilot. Define routines that run on a schedule, trigger on API calls, or react to GitHub events from Anthropic-managed cloud infrastructure.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0055,Desktop scheduled tasks,https://code.claude.com/docs/en/desktop-scheduled-tasks,external,code.claude.com,ok,200,https://code.claude.com/docs/en/desktop-scheduled-tasks,text/html; charset=utf-8,Schedule recurring tasks in Claude Code Desktop - Claude Code Docs,"Set up scheduled tasks in Claude Code Desktop to run Claude automatically on a recurring basis for daily code reviews, dependency audits, or morning briefings.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0056,Run parallel sessions with worktrees,https://code.claude.com/docs/en/worktrees,external,code.claude.com,ok,200,https://code.claude.com/docs/en/worktrees,text/html; charset=utf-8,Run parallel sessions with worktrees - Claude Code Docs,"Isolate parallel Claude Code sessions in separate git worktrees so changes don't collide. Covers the --worktree flag, subagent isolation, .worktreeinclude, cleanup, and non-git VCS hooks.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0057,Automate actions with hooks,https://code.claude.com/docs/en/hooks-guide,external,code.claude.com,ok,200,https://code.claude.com/docs/en/hooks-guide,text/html; charset=utf-8,Automate actions with hooks - Claude Code Docs,"Run shell commands automatically when Claude Code edits files, finishes tasks, or needs input. Format code, send notifications, validate commands, and enforce project rules.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0058,Hooks reference,https://code.claude.com/docs/en/hooks.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/hooks.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0059,Common workflows - Claude Code,https://code.claude.com/docs/en/common-workflows,external,code.claude.com,ok,200,https://code.claude.com/docs/en/common-workflows,text/html; charset=utf-8,Common workflows - Claude Code Docs,"Step-by-step guides for exploring codebases, fixing bugs, refactoring, testing, and other everyday tasks with Claude Code.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0060,Manage multiple agents with agent view,https://code.claude.com/docs/en/agent-view.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/agent-view.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0061,Run agents in parallel,https://code.claude.com/docs/en/agents.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/agents.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0062,Orchestrate subagents at scale with dynamic workflows,https://code.claude.com/docs/en/workflows,external,code.claude.com,ok,200,https://code.claude.com/docs/en/workflows,text/html; charset=utf-8,Orchestrate subagents at scale with dynamic workflows - Claude Code Docs,"Dynamic workflows orchestrate many subagents from a script Claude writes and you can rerun. Use them for codebase audits, large migrations, and cross-checked research.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0063,Create plugins,https://code.claude.com/docs/en/plugins,external,code.claude.com,ok,200,https://code.claude.com/docs/en/plugins,text/html; charset=utf-8,Create plugins - Claude Code Docs,"Create custom plugins to extend Claude Code with skills, agents, hooks, and MCP servers.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0064,Model Context Protocol,https://modelcontextprotocol.io/docs/getting-started/intro,external,modelcontextprotocol.io,ok,200,https://modelcontextprotocol.io/docs/getting-started/intro,text/html; charset=utf-8,What is the Model Context Protocol (MCP)? - Model Context Protocol,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0065,Allowing GitHub Copilot CLI to work autonomously,https://docs.github.com/en/copilot/concepts/agents/copilot-cli/autopilot,external,docs.github.com,ok,200,https://docs.github.com/en/copilot/concepts/agents/copilot-cli/autopilot,text/html; charset=utf-8,Allowing GitHub Copilot CLI to work autonomously - GitHub Docs,"The CLI's autopilot mode lets Copilot CLI work autonomously on a task, carrying out multiple steps until the task is complete.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0066,opencode-scheduler,https://github.com/different-ai/opencode-scheduler,external,github.com,ok,200,https://github.com/different-ai/opencode-scheduler,text/html; charset=utf-8,GitHub - different-ai/opencode-scheduler: OpenCode plugin for scheduling recurring jobs using launchd (Mac) or systemd (Linux) Ā· GitHub,OpenCode plugin for scheduling recurring jobs using launchd (Mac) or systemd (Linux) - different-ai/opencode-scheduler,different-ai/opencode-scheduler,433,29,14,OpenCode plugin for scheduling recurring jobs using launchd (Mac) or systemd (Linux),MIT,2026-07-11T08:57:35Z,,,2026-07-12T10:56:07+00:00 +ale-0067,Agent-Loop-Skills,https://github.com/gaasher/Agent-Loop-Skills,external,github.com,ok,200,https://github.com/gaasher/Agent-Loop-Skills,text/html; charset=utf-8,"GitHub - gaasher/Agent-Loop-Skills: Loop until it's better ā€” drop-in agentic loops (autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, red-teaming) as open-standard Agent Skills. Verification-gated; native on Claude Code, portable across Codex, Cursor & other Skills hosts. Ā· GitHub","Loop until it's better ā€” drop-in agentic loops (autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, red-teaming) as open-standard Agent Skills. Verification-gated; native on Claude Code, portable across Codex, Cursor & other Skills hosts. - gaasher/Agent-Loop-Skills",gaasher/Agent-Loop-Skills,126,14,1,"Loop until it's better ā€” drop-in agentic loops (autoresearch, scientific writing, data analysis, code/SQL/prompt optimization, red-teaming) as open-standard Agent Skills. Verification-gated; native on Claude Code, portable across Codex, Cursor & other Skills hosts.",MIT,2026-07-09T06:21:24Z,,,2026-07-12T10:56:07+00:00 +ale-0068,launch-your-agent,https://github.com/anthropics/launch-your-agent,external,github.com,ok,200,https://github.com/anthropics/launch-your-agent,text/html; charset=utf-8,"GitHub - anthropics/launch-your-agent: Claude Code skills that take a founder from idea to a live Claude Managed Agent: interview, scope a v0, launch in their own account, grade it, iterate, and schedule it Ā· GitHub","Claude Code skills that take a founder from idea to a live Claude Managed Agent: interview, scope a v0, launch in their own account, grade it, iterate, and schedule it - anthropics/launch-your-agent",anthropics/launch-your-agent,783,149,2,"Claude Code skills that take a founder from idea to a live Claude Managed Agent: interview, scope a v0, launch in their own account, grade it, iterate, and schedule it",Apache-2.0,2026-07-12T09:12:37Z,,,2026-07-12T10:56:07+00:00 +ale-0069,Run long horizon tasks with Codex,https://developers.openai.com/blog/run-long-horizon-tasks-with-codex,external,developers.openai.com,ok,200,https://developers.openai.com/blog/run-long-horizon-tasks-with-codex,text/html; charset=utf-8,Run long horizon tasks with Codex | OpenAI Developers,OpenAI Developer Blog,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0070,Best practices - Codex,https://developers.openai.com/codex/learn/best-practices,external,developers.openai.com,ok,200,https://learn.chatgpt.com/guides/best-practices,text/html; charset=utf-8,Best practices | ChatGPT Learn,Getting started with Codex and proven practices for better results,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0071,Agents SDK,https://developers.openai.com/api/docs/guides/agents,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents,text/html; charset=utf-8,Agents SDK | OpenAI API,Learn how the OpenAI Agents SDK fits together and which docs to read next.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0072,Agents - OpenAI Agents SDK,https://openai.github.io/openai-agents-python/agents/,external,openai.github.io,ok,200,https://openai.github.io/openai-agents-python/agents/,text/html; charset=utf-8,Agents - OpenAI Agents SDK,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0073,Running agents,https://developers.openai.com/api/docs/guides/agents/running-agents,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents/running-agents,text/html; charset=utf-8,Running agents | OpenAI API,"Learn how to run agents, stream output, and choose the right conversation-state strategy in the OpenAI Agents SDK.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0074,Integrations and observability,https://developers.openai.com/api/docs/guides/agents/integrations-observability,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents/integrations-observability,text/html; charset=utf-8,Integrations and observability | OpenAI API,Learn how to integrate MCP into Agents SDK workflows and how to trace and debug runs.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0075,Sandbox Agents,https://developers.openai.com/api/docs/guides/agents/sandboxes,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents/sandboxes,text/html; charset=utf-8,Sandbox Agents | OpenAI API,"Learn how sandboxes fit into Agents SDK workflows, when to use them, and how orchestration stays separate from execution.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0076,Guardrails and human review,https://developers.openai.com/api/docs/guides/agents/guardrails-approvals,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agents/guardrails-approvals,text/html; charset=utf-8,Guardrails and human review | OpenAI API,"Learn how to use guardrails and human review in the OpenAI Agents SDK for safer, more controlled workflows.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0077,Building agents with the Claude Agent SDK,https://code.claude.com/docs/en/agent-sdk/overview.md,external,code.claude.com,ok,200,https://code.claude.com/docs/en/agent-sdk/overview.md,text/markdown; charset=utf-8,,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0078,How the agent loop works,https://code.claude.com/docs/en/agent-sdk/agent-loop,external,code.claude.com,ok,200,https://code.claude.com/docs/en/agent-sdk/agent-loop,text/html; charset=utf-8,How the agent loop works - Claude Code Docs,"Understand the message lifecycle, tool execution, context window, and architecture that power your SDK agents.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0079,Extend Claude with skills,https://code.claude.com/docs/en/skills,external,code.claude.com,ok,200,https://code.claude.com/docs/en/skills,text/html; charset=utf-8,Extend Claude with skills - Claude Code Docs,"Create, manage, and share skills to extend Claude's capabilities in Claude Code. Includes custom commands and bundled skills.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0080,Create custom subagents,https://code.claude.com/docs/en/sub-agents,external,code.claude.com,ok,200,https://code.claude.com/docs/en/sub-agents,text/html; charset=utf-8,Create custom subagents - Claude Code Docs,Create and use specialized AI subagents in Claude Code for task-specific workflows and improved context management.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0081,GitHub Agentic Workflows,https://github.github.com/gh-aw/,external,github.github.com,ok,200,https://github.github.com/gh-aw/,text/html; charset=utf-8,Home | GitHub Agentic Workflows,Write repository automation workflows in natural language using markdown files and run them as GitHub Actions. Use AI agents with strong guardrails to automate your development workflow.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0082,GitHub Agentic Workflows technical preview,https://github.blog/changelog/2026-02-13-github-agentic-workflows-are-now-in-technical-preview/,external,github.blog,ok,200,https://github.blog/changelog/2026-02-13-github-agentic-workflows-are-now-in-technical-preview/,text/html; charset=UTF-8,GitHub Agentic Workflows are now in technical preview - GitHub Changelog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"GitHub Agentic Workflows let you automate repository tasks using AI agents that run within GitHub Actions. Write workflows in plain Markdown instead of complex YAML, and let AI handle intelligentā€¦",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0083,Continuous AI,https://githubnext.com/projects/continuous-ai/,external,githubnext.com,ok,200,https://githubnext.com/projects/continuous-ai/,text/html; charset=utf-8,Continuous AI,Exploring LLM-powered automation in platform-based software collaboration,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0084,Automate repository tasks with GitHub Agentic Workflows,https://github.blog/ai-and-ml/automate-repository-tasks-with-github-agentic-workflows/,external,github.blog,ok,200,https://github.blog/ai-and-ml/automate-repository-tasks-with-github-agentic-workflows/,text/html; charset=UTF-8,Automate repository tasks with GitHub Agentic Workflows - The GitHub Blog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"Build automations using coding agents in GitHub Actions to handle triage, documentation, code quality, and more.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0085,Continuous AI in practice: What developers can automate today with agentic CI,https://github.blog/ai-and-ml/generative-ai/continuous-ai-in-practice-what-developers-can-automate-today-with-agentic-ci/,external,github.blog,ok,200,https://github.blog/ai-and-ml/generative-ai/continuous-ai-in-practice-what-developers-can-automate-today-with-agentic-ci/,text/html; charset=UTF-8,Continuous AI in practice: What developers can automate today with agentic CI - The GitHub Blog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,Think of Continuous AI as background agents that operate in your repository for tasks that require reasoning.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0086,About GitHub Copilot coding agent,https://docs.github.com/en/copilot/concepts/agents/coding-agent/about-coding-agent,external,docs.github.com,ok,200,https://docs.github.com/en/copilot/concepts/agents/cloud-agent/about-cloud-agent,text/html; charset=utf-8,About GitHub Copilot cloud agent - GitHub Docs,"Copilot can research a repository, create an implementation plan, and make code changes on a branch. You can review the diff, iterate, and create a pull request when you're ready.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0087,GitHub Copilot: Meet the new coding agent,https://github.blog/news-insights/product-news/github-copilot-meet-the-new-coding-agent/,external,github.blog,ok,200,https://github.blog/news-insights/product-news/github-copilot-meet-the-new-coding-agent/,text/html; charset=UTF-8,GitHub Copilot: Meet the new coding agent - The GitHub Blog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"GitHub Copilot has a new feature: a coding agent that can implement a task or issue, run in the background with GitHub Actions, and more.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0088,Jules,https://jules.google/docs,external,jules.google,ok,200,https://jules.google/docs,text/html,Getting started | Jules,Set up and run your first task with Jules,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0089,Cursor cloud agents,https://cursor.com/docs/cloud-agent,external,cursor.com,ok,200,https://cursor.com/docs/cloud-agent,text/html; charset=utf-8,Cloud Agents | Cursor Docs,Run Agent in the cloud for continuous coding assistance.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0090,Devin Docs,https://docs.devin.ai/get-started/devin-intro,external,docs.devin.ai,ok,200,https://docs.devin.ai/get-started/devin-intro,text/html; charset=utf-8,Introducing Devin - Devin Docs,"Devin is the AI software engineer, built to help ambitious engineering teams crush their backlogs.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0091,Writing effective tools for AI agents,https://www.anthropic.com/engineering/writing-tools-for-agents,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/writing-tools-for-agents,text/html; charset=utf-8,Writing effective tools for AI agentsā€”using AI agents \ Anthropic,Writing effective tools for AI agentsā€”using AI agents,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0092,Introducing advanced tool use on the Claude Developer Platform,https://www.anthropic.com/engineering/advanced-tool-use?e45d281a_page=3,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/advanced-tool-use?e45d281a_page=3,text/html; charset=utf-8,Introducing advanced tool use on the Claude Developer Platform \ Anthropic,"Claude can now discover, learn, and execute tools dynamically to enable agents that take action in the real world. Hereā€™s how.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0093,Effective harnesses for long-running agents,https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/effective-harnesses-for-long-running-agents,text/html; charset=utf-8,Effective harnesses for long-running agents \ Anthropic,"Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0094,Claude Code best practices,https://code.claude.com/docs/en/best-practices,external,code.claude.com,ok,200,https://code.claude.com/docs/en/best-practices,text/html; charset=utf-8,Best practices for Claude Code - Claude Code Docs,"Tips and patterns for getting the most out of Claude Code, from configuring your environment to scaling across parallel sessions.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0095,Cursor 3.8: Improvements to Cursor Automations,https://cursor.com/changelog/06-18-26,external,cursor.com,ok,200,https://cursor.com/changelog/06-18-26,text/html; charset=utf-8,Improvements to Cursor Automations Ā· Cursor,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0096,GitHub Copilot for Jira Is Now Generally Available,https://github.blog/changelog/2026-06-25-github-copilot-for-jira-is-now-generally-available/,external,github.blog,ok,200,https://github.blog/changelog/2026-06-25-github-copilot-for-jira-is-now-generally-available/,text/html; charset=UTF-8,GitHub Copilot for Jira is now generally available - GitHub Changelog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"GitHub Copilot for Jira is now generally available. Since launching the public preview in March 2026, we have shipped a series of enhancements based on your feedback, including model selection,ā€¦",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0097,Claude Managed Agents: Scheduled Deployments and Vaults,https://claude.com/blog/whats-new-in-claude-managed-agents,external,claude.com,ok,200,https://claude.com/blog/whats-new-in-claude-managed-agents,text/html; charset=utf-8,New in Claude Managed Agents: run agents on a schedule and store environment variables in vaults | Claude by Anthropic,Claude Managed Agents now supports scheduled deployments and vaults: run agents on a cron schedule and securely authenticate CLI tools and other services.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0098,Copilot Agent Session Streaming (Public Preview),https://github.blog/changelog/2026-07-02-copilot-agent-session-streaming-is-now-in-public-preview/,external,github.blog,ok,200,https://github.blog/changelog/2026-07-02-copilot-agent-session-streaming-is-now-in-public-preview/,text/html; charset=UTF-8,Copilot agent session streaming is now in public preview - GitHub Changelog LinkedIn icon Instagram icon YouTube icon X icon TikTok icon Twitch icon GitHub icon,"GitHub Enterprise Cloud customers with enterprise managed users can now access GitHub Copilot agent session data across all Copilot clients, including: Cloud agents operating on github.com and data resident deploymentsā€¦",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0099,Expanding Our Long-Running Agents Research Preview,https://cursor.com/blog/long-running-agents,external,cursor.com,ok,200,https://cursor.com/blog/long-running-agents,text/html; charset=utf-8,Expanding our long-running agents research preview Ā· Cursor,"Long-running agents are now available in the Cursor web app for Ultra, Teams, and Enterprise users.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0100,ChatGPT Work and the Codex Desktop App,https://openai.com/index/chatgpt-for-your-most-ambitious-work/,external,openai.com,restricted,403,https://openai.com/index/chatgpt-for-your-most-ambitious-work/,text/html; charset=UTF-8,,,,,,,,,,,restricted_or_rate_limited,2026-07-12T10:56:07+00:00 +ale-0101,Getting Started with Loops,https://claude.com/blog/getting-started-with-loops,external,claude.com,ok,200,https://claude.com/blog/getting-started-with-loops,text/html; charset=utf-8,Loop engineering: Getting started with loops | Claude by Anthropic,"Loop engineering with Claude Code: design turn-based, goal, time, and proactive agent loopsā€”including Ralph loops and /loopā€”that run to a stop condition.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0102,"Cursor 3.11: Side Chats, Transcript Search, and Cloud Agent Hooks",https://cursor.com/changelog/side-chat,external,cursor.com,ok,200,https://cursor.com/changelog/side-chat,text/html; charset=utf-8,Side Chats and Conversation Search Ā· Cursor,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0103,"Amp: Agents, Anywhere",https://ampcode.com/news/agents-anywhere,external,ampcode.com,ok,200,https://ampcode.com/news/agents-anywhere,text/html,Amp,Remotely start agents anywhere you can run 'amp',,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0104,ReAct: Synergizing Reasoning and Acting in Language Models,https://arxiv.org/abs/2210.03629,external,arxiv.org,ok,200,https://arxiv.org/abs/2210.03629,text/html; charset=utf-8,[2210.03629] ReAct: Synergizing Reasoning and Acting in Language Models,Abstract page for arXiv paper 2210.03629: ReAct: Synergizing Reasoning and Acting in Language Models,,,,,,,,2210.03629,,2026-07-12T10:56:07+00:00 +ale-0105,Reflexion: Language Agents with Verbal Reinforcement Learning,https://arxiv.org/abs/2303.11366,external,arxiv.org,ok,200,https://arxiv.org/abs/2303.11366,text/html; charset=utf-8,[2303.11366] Reflexion: Language Agents with Verbal Reinforcement Learning,Abstract page for arXiv paper 2303.11366: Reflexion: Language Agents with Verbal Reinforcement Learning,,,,,,,,2303.11366,,2026-07-12T10:56:07+00:00 +ale-0106,Self-Refine: Iterative Refinement with Self-Feedback,https://arxiv.org/abs/2303.17651,external,arxiv.org,ok,200,https://arxiv.org/abs/2303.17651,text/html; charset=utf-8,[2303.17651] Self-Refine: Iterative Refinement with Self-Feedback,Abstract page for arXiv paper 2303.17651: Self-Refine: Iterative Refinement with Self-Feedback,,,,,,,,2303.17651,,2026-07-12T10:56:07+00:00 +ale-0107,CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing,https://arxiv.org/abs/2305.11738,external,arxiv.org,ok,200,https://arxiv.org/abs/2305.11738,text/html; charset=utf-8,[2305.11738] CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing,Abstract page for arXiv paper 2305.11738: CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing,,,,,,,,2305.11738,,2026-07-12T10:56:07+00:00 +ale-0108,Tree of Thoughts,https://arxiv.org/abs/2305.10601,external,arxiv.org,ok,200,https://arxiv.org/abs/2305.10601,text/html; charset=utf-8,[2305.10601] Tree of Thoughts: Deliberate Problem Solving with Large Language Models,Abstract page for arXiv paper 2305.10601: Tree of Thoughts: Deliberate Problem Solving with Large Language Models,,,,,,,,2305.10601,,2026-07-12T10:56:07+00:00 +ale-0109,Graph of Thoughts,https://arxiv.org/abs/2308.09687,external,arxiv.org,ok,200,https://arxiv.org/abs/2308.09687,text/html; charset=utf-8,[2308.09687] Graph of Thoughts: Solving Elaborate Problems with Large Language Models,Abstract page for arXiv paper 2308.09687: Graph of Thoughts: Solving Elaborate Problems with Large Language Models,,,,,,,,2308.09687,,2026-07-12T10:56:07+00:00 +ale-0110,Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models,https://arxiv.org/abs/2310.04406,external,arxiv.org,ok,200,https://arxiv.org/abs/2310.04406,text/html; charset=utf-8,[2310.04406] Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models,Abstract page for arXiv paper 2310.04406: Language Agent Tree Search Unifies Reasoning Acting and Planning in Language Models,,,,,,,,2310.04406,,2026-07-12T10:56:07+00:00 +ale-0111,Voyager: An Open-Ended Embodied Agent with Large Language Models,https://arxiv.org/abs/2305.16291,external,arxiv.org,ok,200,https://arxiv.org/abs/2305.16291,text/html; charset=utf-8,[2305.16291] Voyager: An Open-Ended Embodied Agent with Large Language Models,Abstract page for arXiv paper 2305.16291: Voyager: An Open-Ended Embodied Agent with Large Language Models,,,,,,,,2305.16291,,2026-07-12T10:56:07+00:00 +ale-0112,Generative Agents: Interactive Simulacra of Human Behavior,https://arxiv.org/abs/2304.03442,external,arxiv.org,ok,200,https://arxiv.org/abs/2304.03442,text/html; charset=utf-8,[2304.03442] Generative Agents: Interactive Simulacra of Human Behavior,Abstract page for arXiv paper 2304.03442: Generative Agents: Interactive Simulacra of Human Behavior,,,,,,,,2304.03442,,2026-07-12T10:56:07+00:00 +ale-0113,Measuring AI Ability to Complete Long Software Tasks,https://arxiv.org/abs/2503.14499,external,arxiv.org,ok,200,https://arxiv.org/abs/2503.14499,text/html; charset=utf-8,[2503.14499] Measuring AI Ability to Complete Long Software Tasks,Abstract page for arXiv paper 2503.14499: Measuring AI Ability to Complete Long Software Tasks,,,,,,,,2503.14499,,2026-07-12T10:56:07+00:00 +ale-0114,Measuring AI Ability to Complete Long Tasks,https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/,external,metr.org,ok,200,https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/,text/html; charset=UTF-8,Measuring AI Ability to Complete Long Tasks - METR Substack twitter Bluesky,"We propose measuring AI performance in terms of the *length* of tasks AI agents can complete. We show that this metric has been consistently exponentially increasing over the past 6 years, with a doubling time of around 7 months. Extrapolating this trend predicts that, in under a decade, we will see AI agents that can independently complete a large fraction of software tasks that currently take humans days or weeks.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0115,Reflection-Driven Control for Trustworthy Code Agents,https://arxiv.org/abs/2512.21354,external,arxiv.org,ok,200,https://arxiv.org/abs/2512.21354,text/html; charset=utf-8,[2512.21354] Reflection-Driven Control for Trustworthy Code Agents,Abstract page for arXiv paper 2512.21354: Reflection-Driven Control for Trustworthy Code Agents,,,,,,,,2512.21354,,2026-07-12T10:56:07+00:00 +ale-0116,Hyperagents,https://arxiv.org/abs/2603.19461,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.19461,text/html; charset=utf-8,[2603.19461] Hyperagents,Abstract page for arXiv paper 2603.19461: Hyperagents,,,,,,,,2603.19461,,2026-07-12T10:56:07+00:00 +ale-0117,PARC: An Autonomous Self-Reflective Coding Agent for Robust Execution of Long-Horizon Tasks,https://arxiv.org/abs/2512.03549,external,arxiv.org,ok,200,https://arxiv.org/abs/2512.03549,text/html; charset=utf-8,[2512.03549] PARC: An Autonomous Self-Reflective Coding Agent for Robust Execution of Long-Horizon Tasks,Abstract page for arXiv paper 2512.03549: PARC: An Autonomous Self-Reflective Coding Agent for Robust Execution of Long-Horizon Tasks,,,,,,,,2512.03549,,2026-07-12T10:56:07+00:00 +ale-0118,When the Specification Emerges: Benchmarking Faithfulness Loss in Long-Horizon Coding Agents,https://arxiv.org/abs/2603.17104,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.17104,text/html; charset=utf-8,[2603.17104] When the Specification Emerges: Benchmarking Faithfulness Loss in Long-Horizon Coding Agents,Abstract page for arXiv paper 2603.17104: When the Specification Emerges: Benchmarking Faithfulness Loss in Long-Horizon Coding Agents,,,,,,,,2603.17104,,2026-07-12T10:56:07+00:00 +ale-0119,Reflexion code,https://github.com/noahshinn/reflexion,external,github.com,ok,200,https://github.com/noahshinn/reflexion,text/html; charset=utf-8,GitHub - noahshinn/reflexion: [NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning Ā· GitHub,[NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning - noahshinn/reflexion,noahshinn/reflexion,3201,310,23,[NeurIPS 2023] Reflexion: Language Agents with Verbal Reinforcement Learning,MIT,2026-07-11T15:57:17Z,,,2026-07-12T10:56:07+00:00 +ale-0120,Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting,https://arxiv.org/abs/2607.00038,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.00038,text/html; charset=utf-8,[2607.00038] Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting,Abstract page for arXiv paper 2607.00038: Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting,,,,,,,,2607.00038,,2026-07-12T10:56:07+00:00 +ale-0121,From Question Answering to Task Completion: A Survey on Agent System and Harness Design,https://arxiv.org/abs/2606.20683,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.20683,text/html; charset=utf-8,[2606.20683] From Question Answering to Task Completion: A Survey on Agent System and Harness Design,Abstract page for arXiv paper 2606.20683: From Question Answering to Task Completion: A Survey on Agent System and Harness Design,,,,,,,,2606.20683,,2026-07-12T10:56:07+00:00 +ale-0122,MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems,https://arxiv.org/abs/2605.22794,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.22794,text/html; charset=utf-8,[2605.22794] MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems,Abstract page for arXiv paper 2605.22794: MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems,,,,,,,,2605.22794,,2026-07-12T10:56:07+00:00 +ale-0123,METR Time Horizon 1.1,https://metr.org/blog/2026-1-29-time-horizon-1-1/,external,metr.org,ok,200,https://metr.org/blog/2026-1-29-time-horizon-1-1/,text/html; charset=UTF-8,Time Horizon 1.1 - METR Substack twitter Bluesky,"Weā€™re releasing a new version of our time horizon estimates (TH1.1), using more tasks and a new eval infrastructure.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0124,MetaSkill-Evolve: Recursive Self-Improvement via Two-Timescale Meta-Skill Evolution,https://arxiv.org/abs/2607.05297,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05297,text/html; charset=utf-8,[2607.05297] MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution,Abstract page for arXiv paper 2607.05297: MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution,,,,,,,,2607.05297,,2026-07-12T10:56:07+00:00 +ale-0125,SkillOpt-Lite: Better and Faster Agent Self-Evolution via One Line of Vibe,https://arxiv.org/abs/2607.03451,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.03451,text/html; charset=utf-8,[2607.03451] SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe,Abstract page for arXiv paper 2607.03451: SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe,,,,,,,,2607.03451,,2026-07-12T10:56:07+00:00 +ale-0126,Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops,https://arxiv.org/abs/2607.07663,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07663,text/html; charset=utf-8,[2607.07663] Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops,Abstract page for arXiv paper 2607.07663: Recursive Self-Improvement in AI: From Bounded Self-Refinement to Autonomous Research Loops,,,,,,,,2607.07663,,2026-07-12T10:56:07+00:00 +ale-0127,From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents,https://arxiv.org/abs/2607.07321,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07321,text/html; charset=utf-8,[2607.07321] From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents,Abstract page for arXiv paper 2607.07321: From Atomic Actions to Standard Operating Procedures: Iterative Tool Optimization for Self-Evolving LLM Agents,,,,,,,,2607.07321,,2026-07-12T10:56:07+00:00 +ale-0128,TTHE: Test-Time Harness Evolution,https://arxiv.org/abs/2607.08124,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08124,text/html; charset=utf-8,[2607.08124] TTHE: Test-Time Harness Evolution,Abstract page for arXiv paper 2607.08124: TTHE: Test-Time Harness Evolution,,,,,,,,2607.08124,,2026-07-12T10:56:07+00:00 +ale-0129,DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment,https://arxiv.org/abs/2607.07820,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07820,text/html; charset=utf-8,[2607.07820] DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment,Abstract page for arXiv paper 2607.07820: DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment,,,,,,,,2607.07820,,2026-07-12T10:56:07+00:00 +ale-0130,What Makes a Good Bug Report for an AI Agent?,https://arxiv.org/abs/2607.07593,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07593,text/html; charset=utf-8,[2607.07593] What Makes a Good Bug Report for an AI Agent?,Abstract page for arXiv paper 2607.07593: What Makes a Good Bug Report for an AI Agent?,,,,,,,,2607.07593,,2026-07-12T10:56:07+00:00 +ale-0131,AutoPersonas: A Multi-Timescale Loop Engine for Open-Ended Persona Evolution,https://arxiv.org/abs/2607.08252,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08252,text/html; charset=utf-8,[2607.08252] AutoPersonas: A Multi-Timescale Loop Engine for Open-Ended Persona Evolution,Abstract page for arXiv paper 2607.08252: AutoPersonas: A Multi-Timescale Loop Engine for Open-Ended Persona Evolution,,,,,,,,2607.08252,,2026-07-12T10:56:07+00:00 +ale-0132,Agentic Data Environments,https://arxiv.org/abs/2607.07397,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07397,text/html; charset=utf-8,[2607.07397] Agentic Data Environments,Abstract page for arXiv paper 2607.07397: Agentic Data Environments,,,,,,,,2607.07397,,2026-07-12T10:56:07+00:00 +ale-0133,Building Effective Agents,https://www.anthropic.com/engineering/building-effective-agents,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/building-effective-agents,text/html; charset=utf-8,Building Effective AI Agents \ Anthropic,"Discover how Anthropic approaches the development of reliable AI agents. Learn about our research on agent capabilities, safety considerations, and technical framework for building trustworthy AI.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0134,How we built our multi-agent research system,https://www.anthropic.com/engineering/multi-agent-research-system,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/multi-agent-research-system,text/html; charset=utf-8,How we built our multi-agent research system \ Anthropic,On the the engineering challenges and lessons learned from building Claude's Research system,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0135,Building Effective AI Agents: Architecture Patterns and Implementation Frameworks,https://resources.anthropic.com/hubfs/Building%20Effective%20AI%20Agents-%20Architecture%20Patterns%20and%20Implementation%20Frameworks.pdf,external,resources.anthropic.com,ok,200,https://resources.anthropic.com/hubfs/Building%20Effective%20AI%20Agents-%20Architecture%20Patterns%20and%20Implementation%20Frameworks.pdf,application/pdf,,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0136,AI Agent Architectures,https://hld.handbook.academy/curriculum/ai-ml-system-design/ai-agent-architectures/,external,hld.handbook.academy,ok,200,https://hld.handbook.academy/curriculum/ai-ml-system-design/ai-agent-architectures/,text/html; charset=utf-8,"AI Agent Architectures (ReAct, Reflection, Planning, Tool Use, Memory) - The HLD Handbook","The canonical patterns for turning an LLM into an agent: ReAct's think-act-observe loop, reflection and self-critique, planner-executor decomposition, tool use and function calling, and how agents manage short- and long-term memory.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0137,What Are Agentic Workflows?,https://weaviate.io/blog/what-are-agentic-workflows,external,weaviate.io,ok,200,https://weaviate.io/blog/what-are-agentic-workflows,text/html; charset=UTF-8,"What Are Agentic Workflows? Patterns, Memory, Use Cases, and Examples | Weaviate","Agentic workflows combine AI agents, tools, and agent memory to create adaptive systems. Learn the core patterns, use cases, and real-world examples.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0138,Agent Planning & Reflection Patterns,https://learnaivisually.com/tracks/ai-agents/planning-reflection,external,learnaivisually.com,ok,200,https://learnaivisually.com/tracks/ai-agents/planning-reflection,text/html; charset=utf-8,Agent Planning & Reflection Patterns | Learn AI Visually LAV LAV,"When agents should plan, retry, pause, or stop. Reasoning budget, ReAct, Reflexion, and termination logic ā€” each tied to a 'when' decision.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0139,Agentic Design Patterns,https://addyosmani.com/agents/04-agentic-design-patterns/,external,addyosmani.com,ok,200,https://addyosmani.com/agents/04-agentic-design-patterns/,text/html; charset=UTF-8,AddyOsmani.com - Lesson 4: agentic design patterns,"Addy Osmani is an engineering and evangelism leader who spent over 14 years at Google leading developer experience across Chrome and, in recent years, AI (Gemini, coding agents, and agentic engineering), most recently as a Director at Google Cloud AI.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0140,12 Factor Agents,https://github.com/humanlayer/12-factor-agents,external,github.com,ok,200,https://github.com/humanlayer/12-factor-agents,text/html; charset=utf-8,GitHub - humanlayer/12-factor-agents: What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? Ā· GitHub,What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? - humanlayer/12-factor-agents,humanlayer/12-factor-agents,24193,1842,26,What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?,NOASSERTION,2026-07-12T10:13:38Z,,,2026-07-12T10:56:07+00:00 +ale-0141,Durable Execution for Agentic Workflows,https://arizenai.com/durable-execution/,external,arizenai.com,ok,200,https://arizenai.com/durable-execution/,text/html; charset=utf-8,Durable Execution for Agentic Workflows | Arizen,A while loop is at-most-once across process boundaries. Production agents need exactly-once. The architecture must encode the guarantee.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0142,Code as Agent Harness,https://arxiv.org/abs/2605.18747,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.18747,text/html; charset=utf-8,[2605.18747] Code as Agent Harness,Abstract page for arXiv paper 2605.18747: Code as Agent Harness,,,,,,,,2605.18747,,2026-07-12T10:56:07+00:00 +ale-0143,Agentic Agile-V: From Vibe Coding to Verified Engineering,https://arxiv.org/abs/2605.20456,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.20456,text/html; charset=utf-8,[2605.20456] Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development,Abstract page for arXiv paper 2605.20456: Agentic Agile-V: From Vibe Coding to Verified Engineering in Software and Hardware Development,,,,,,,,2605.20456,,2026-07-12T10:56:07+00:00 +ale-0144,"Harness Engineering for Language Agents: The Harness Layer as Control, Agency, and Runtime",https://www.preprints.org/manuscript/202603.1756,external,www.preprints.org,restricted,403,https://www.preprints.org/manuscript/202603.1756,text/html,,,,,,,,,,,restricted_or_rate_limited,2026-07-12T10:56:07+00:00 +ale-0145,Agentic Software Engineering: Foundational Pillars and a Research Roadmap,https://arxiv.org/abs/2509.06216,external,arxiv.org,ok,200,https://arxiv.org/abs/2509.06216,text/html; charset=utf-8,[2509.06216] Agentic Software Engineering: Foundational Pillars and a Research Roadmap,Abstract page for arXiv paper 2509.06216: Agentic Software Engineering: Foundational Pillars and a Research Roadmap,,,,,,,,2509.06216,,2026-07-12T10:56:07+00:00 +ale-0146,The Art of Loop Engineering,https://www.langchain.com/blog/the-art-of-loop-engineering,external,www.langchain.com,ok,200,https://www.langchain.com/blog/the-art-of-loop-engineering,text/html; charset=utf-8,The Art of Loop Engineering,"Agents automate real-world work, but reliable performance requires more than a good model, it requires a carefully designed harness built for specific tasks. This post explores the core agent loop, how stacking and extending loops builds more effective agents, and how to instrument each level with LangChain primitives.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0147,Loopy,https://github.com/Forward-Future/loopy,external,github.com,ok,200,https://github.com/Forward-Future/loopy,text/html; charset=utf-8,"GitHub - Forward-Future/loopy: A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows. Ā· GitHub","A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows. - Forward-Future/loopy",Forward-Future/loopy,2653,228,1,"A library of practical AI-agent loops and an installable skill for finding, adapting, and designing repeatable agent workflows.",MIT,2026-07-12T05:21:25Z,,,2026-07-12T10:56:07+00:00 +ale-0148,The Factory Model: How Coding Agents Changed Software Engineering,https://addyosmani.com/blog/factory-model/,external,addyosmani.com,ok,200,https://addyosmani.com/blog/factory-model/,text/html; charset=UTF-8,AddyOsmani.com - The Factory Model: How Coding Agents Changed Software Engineering,Software engineering is not about writing code anymore. It is about building the factory that builds your software.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0149,2026 Agentic Coding Trends Report,https://resources.anthropic.com/2026-agentic-coding-trends-report,external,resources.anthropic.com,ok,200,https://resources.anthropic.com/2026-agentic-coding-trends-report,text/html; charset=UTF-8,2026 Agentic Coding Trends Report,"How coding agents are transforming software development - and what it means for engineering teams in 2026. Insights on multi-agent systems, human-AI collaboration, and scaling agentic coding across organizations. Includes case studies from Rakuten, TELUS, Zapier, and more.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0150,HomeRail,https://github.com/xiaotianfotos/homerail,external,github.com,ok,200,https://github.com/xiaotianfotos/homerail,text/html; charset=utf-8,GitHub - xiaotianfotos/homerail: Voice-first local agent orchestration runtime for auditable DAG workflows. Ā· GitHub,Voice-first local agent orchestration runtime for auditable DAG workflows. - xiaotianfotos/homerail,xiaotianfotos/homerail,462,110,7,Voice-first local agent orchestration runtime for auditable DAG workflows.,MIT,2026-07-12T10:20:15Z,,,2026-07-12T10:56:07+00:00 +ale-0151,SWE-agent,https://github.com/SWE-agent/SWE-agent,external,github.com,ok,200,https://github.com/SWE-agent/SWE-agent,text/html; charset=utf-8,"GitHub - SWE-agent/SWE-agent: SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024] Ā· GitHub","SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024] - GitHub - SWE-agent/SWE-agent: SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]",SWE-agent/SWE-agent,19780,2164,31,"SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]",MIT,2026-07-12T10:04:29Z,,,2026-07-12T10:56:07+00:00 +ale-0152,SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering,https://arxiv.org/abs/2405.15793,external,arxiv.org,ok,200,https://arxiv.org/abs/2405.15793,text/html; charset=utf-8,[2405.15793] SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering,Abstract page for arXiv paper 2405.15793: SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering,,,,,,,,2405.15793,,2026-07-12T10:56:07+00:00 +ale-0153,mini-SWE-agent,https://mini-swe-agent.com/latest/,external,mini-swe-agent.com,ok,200,https://mini-swe-agent.com/latest/,text/html; charset=utf-8,Overview - mini-SWE-agent documentation,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0154,OpenHands,https://github.com/All-Hands-AI/OpenHands,external,github.com,ok,200,https://github.com/OpenHands/OpenHands,text/html; charset=utf-8,GitHub - OpenHands/OpenHands: šŸ™Œ OpenHands: AI-Driven Development Ā· GitHub,šŸ™Œ OpenHands: AI-Driven Development. Contribute to OpenHands/OpenHands development by creating an account on GitHub.,All-Hands-AI/OpenHands,80523,10274,360,šŸ™Œ OpenHands: AI-Driven Development,NOASSERTION,2026-07-12T10:44:46Z,,,2026-07-12T10:56:07+00:00 +ale-0155,OpenHands: An Open Platform for AI Software Developers as Generalist Agents,https://arxiv.org/abs/2407.16741,external,arxiv.org,ok,200,https://arxiv.org/abs/2407.16741,text/html; charset=utf-8,[2407.16741] OpenHands: An Open Platform for AI Software Developers as Generalist Agents,Abstract page for arXiv paper 2407.16741: OpenHands: An Open Platform for AI Software Developers as Generalist Agents,,,,,,,,2407.16741,,2026-07-12T10:56:07+00:00 +ale-0156,Agentless,https://github.com/OpenAutoCoder/Agentless,external,github.com,ok,200,https://github.com/OpenAutoCoder/Agentless,text/html; charset=utf-8,GitHub - OpenAutoCoder/Agentless: AgentlessšŸ±: an agentless approach to automatically solve software development problems Ā· GitHub,AgentlessšŸ±: an agentless approach to automatically solve software development problems - OpenAutoCoder/Agentless,OpenAutoCoder/Agentless,2080,235,54,AgentlessšŸ±: an agentless approach to automatically solve software development problems,MIT,2026-07-09T09:26:11Z,,,2026-07-12T10:56:07+00:00 +ale-0157,Agentless: Demystifying LLM-based Software Engineering Agents,https://arxiv.org/abs/2407.01489,external,arxiv.org,ok,200,https://arxiv.org/abs/2407.01489,text/html; charset=utf-8,[2407.01489] Agentless: Demystifying LLM-based Software Engineering Agents,Abstract page for arXiv paper 2407.01489: Agentless: Demystifying LLM-based Software Engineering Agents,,,,,,,,2407.01489,,2026-07-12T10:56:07+00:00 +ale-0158,AutoCodeRover,https://github.com/AutoCodeRoverSG/auto-code-rover,external,github.com,ok,200,https://github.com/AutoCodeRoverSG/auto-code-rover,text/html; charset=utf-8,GitHub - AutoCodeRoverSG/auto-code-rover: A project structure aware autonomous software engineer aiming for autonomous program improvement. Resolved 37.3% tasks (pass@1) in SWE-bench lite and 46.2% tasks (pass@1) in SWE-bench verified with each task costs less than $0.7. Ā· GitHub,A project structure aware autonomous software engineer aiming for autonomous program improvement. Resolved 37.3% tasks (pass@1) in SWE-bench lite and 46.2% tasks (pass@1) in SWE-bench verified with each task costs less than $0.7. - AutoCodeRoverSG/auto-code-rover,AutoCodeRoverSG/auto-code-rover,3095,332,20,A project structure aware autonomous software engineer aiming for autonomous program improvement. Resolved 37.3% tasks (pass@1) in SWE-bench lite and 46.2% tasks (pass@1) in SWE-bench verified with each task costs less than $0.7.,NOASSERTION,2026-07-08T21:43:44Z,,,2026-07-12T10:56:07+00:00 +ale-0159,AutoCodeRover: Autonomous Program Improvement,https://arxiv.org/abs/2404.05427,external,arxiv.org,ok,200,https://arxiv.org/abs/2404.05427,text/html; charset=utf-8,[2404.05427] AutoCodeRover: Autonomous Program Improvement,Abstract page for arXiv paper 2404.05427: AutoCodeRover: Autonomous Program Improvement,,,,,,,,2404.05427,,2026-07-12T10:56:07+00:00 +ale-0160,Ralph,https://ghuntley.com/ralph/,external,ghuntley.com,ok,200,https://ghuntley.com/ralph/,text/html; charset=utf-8,"Ralph Wiggum as a ""software engineer""","How Ralph Wiggum went from 'The Simpsons' to the biggest name in AI right now - Venture Beat šŸ˜ŽHere's a cool little field report from a Y Combinator hackathon event where they put Ralph Wiggum to the test. ""We Put a Coding Agent in a While Loop and It Shipped",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0161,everything is a ralph loop,https://ghuntley.com/loop/,external,ghuntley.com,ok,200,https://ghuntley.com/loop/,text/html; charset=utf-8,everything is a ralph loop,"Iā€™ve been thinking about how I build software is so very very different how I used to do it three years ago. No, Iā€™m not talking about acceleration through usage of AI but instead at a more fundamental level of approach, techniques and best practices. Standard software practices",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0162,how-to-ralph-wiggum,https://github.com/ghuntley/how-to-ralph-wiggum,external,github.com,ok,200,https://github.com/ghuntley/how-to-ralph-wiggum,text/html; charset=utf-8,GitHub - ghuntley/how-to-ralph-wiggum: The Ralph Wiggum Techniqueā€”the AI development methodology that reduces software costs to less than a fast food worker's wage. Ā· GitHub,The Ralph Wiggum Techniqueā€”the AI development methodology that reduces software costs to less than a fast food worker's wage. - ghuntley/how-to-ralph-wiggum,ghuntley/how-to-ralph-wiggum,1715,144,1,The Ralph Wiggum Techniqueā€”the AI development methodology that reduces software costs to less than a fast food worker's wage.,,2026-07-10T20:11:24Z,,,2026-07-12T10:56:07+00:00 +ale-0163,A Brief History of Ralph,https://www.humanlayer.dev/blog/brief-history-of-ralph,external,www.humanlayer.dev,ok,200,https://www.humanlayer.dev/blog/brief-history-of-ralph,text/html; charset=utf-8,A Brief History of Ralph | HumanLayer Blog,The Ralph Wiggum Technique went viral in the last week of 2025. Here's the story of ralph since the first time I met Geoff in June of 2025.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0164,Ralph Copilot,https://github.com/giocaizzi/ralph-copilot/tree/e5b2813cc876c73a8c9d3398c0115da0d15f63cf,external,github.com,ok,200,https://github.com/giocaizzi/ralph-copilot/tree/e5b2813cc876c73a8c9d3398c0115da0d15f63cf,text/html; charset=utf-8,GitHub - giocaizzi/ralph-copilot at e5b2813cc876c73a8c9d3398c0115da0d15f63cf Ā· GitHub,Copilot implementation of Ralph loop. Contribute to giocaizzi/ralph-copilot development by creating an account on GitHub.,giocaizzi/ralph-copilot,136,16,0,Copilot implementation of Ralph loop,,2026-06-28T06:41:40Z,,,2026-07-12T10:56:07+00:00 +ale-0165,Compound Engineering,https://every.to/guides/compound-engineering,external,every.to,ok,200,https://every.to/guides/compound-engineering,text/html; charset=utf-8,Compound Engineering - Every,The AI-native engineering philosophy,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0166,Gas Town,https://github.com/steveyegge/gastown,external,github.com,ok,200,https://github.com/gastownhall/gastown,text/html; charset=utf-8,GitHub - gastownhall/gastown: Gas Town - multi-agent workspace manager Ā· GitHub,Gas Town - multi-agent workspace manager. Contribute to gastownhall/gastown development by creating an account on GitHub.,steveyegge/gastown,16980,1556,260,Gas Town - multi-agent workspace manager,MIT,2026-07-12T10:28:34Z,,,2026-07-12T10:56:07+00:00 +ale-0167,Amp,https://ampcode.com/,external,ampcode.com,ok,200,https://ampcode.com/,text/html,Amp,Amp is a frontier coding agent that lets you wield the full power of leading models.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0168,karl,https://github.com/kayoslab/karl,external,github.com,ok,200,https://github.com/kayoslab/karl,text/html; charset=utf-8,GitHub - kayoslab/karl: Autonomous multi-agent development loop Ā· GitHub,Autonomous multi-agent development loop. Contribute to kayoslab/karl development by creating an account on GitHub.,kayoslab/karl,0,0,0,Autonomous multi-agent development loop,MIT,2026-04-08T07:56:55Z,,,2026-07-12T10:56:07+00:00 +ale-0169,joelclaw agent-loop skill,https://github.com/joelhooks/joelclaw/blob/main/skills/agent-loop/SKILL.md,external,github.com,ok,200,https://github.com/joelhooks/joelclaw/blob/main/skills/agent-loop/SKILL.md,text/html; charset=utf-8,joelclaw/skills/agent-loop/SKILL.md at main Ā· joelhooks/joelclaw Ā· GitHub,"Personal AI operating system ā€” blog, architecture decisions, and the journey from zero to a composable agent system. - joelclaw/skills/agent-loop/SKILL.md at main Ā· joelhooks/joelclaw",joelhooks/joelclaw,60,3,14,"Personal AI operating system ā€” blog, architecture decisions, and the journey from zero to a composable agent system.",,2026-07-12T01:54:48Z,,,2026-07-12T10:56:07+00:00 +ale-0170,SWE-bench reading list,https://github.com/SWE-bench/reading-list,external,github.com,ok,200,https://github.com/SWE-bench/reading-list,text/html; charset=utf-8,GitHub - SWE-bench/reading-list: Academic papers and works related to SWE-bench and SWE-agents Ā· GitHub,Academic papers and works related to SWE-bench and SWE-agents - SWE-bench/reading-list,SWE-bench/reading-list,15,4,0,Academic papers and works related to SWE-bench and SWE-agents,,2026-06-30T13:06:47Z,,,2026-07-12T10:56:07+00:00 +ale-0171,TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code,https://arxiv.org/abs/2602.06875,external,arxiv.org,ok,200,https://arxiv.org/abs/2602.06875,text/html; charset=utf-8,[2602.06875] TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code,Abstract page for arXiv paper 2602.06875: TraceCoder: A Trace-Driven Multi-Agent Framework for Automated Debugging of LLM-Generated Code,,,,,,,,2602.06875,,2026-07-12T10:56:07+00:00 +ale-0172,The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase,https://arxiv.org/abs/2603.25697,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.25697,text/html; charset=utf-8,[2603.25697] The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase,Abstract page for arXiv paper 2603.25697: The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase,,,,,,,,2603.25697,,2026-07-12T10:56:07+00:00 +ale-0173,Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures,https://arxiv.org/abs/2604.03515,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.03515,text/html; charset=utf-8,[2604.03515] Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures,Abstract page for arXiv paper 2604.03515: Inside the Scaffold: A Source-Code Taxonomy of Coding Agent Architectures,,,,,,,,2604.03515,,2026-07-12T10:56:07+00:00 +ale-0174,A Self-Improving Coding Agent,https://arxiv.org/abs/2504.15228,external,arxiv.org,ok,200,https://arxiv.org/abs/2504.15228,text/html; charset=utf-8,[2504.15228] A Self-Improving Coding Agent,Abstract page for arXiv paper 2504.15228: A Self-Improving Coding Agent,,,,,,,,2504.15228,,2026-07-12T10:56:07+00:00 +ale-0175,Factory 2.0: From Coding Agents to Software Factories,https://factory.ai/news/software-factory,external,factory.ai,ok,200,https://factory.ai/news/software-factory,text/html; charset=utf-8,Factory 2.0: From coding agents to software factories | Factory.ai Factory.ai Logo Arrow Right Icon,"In 2023, we launched Factory with the mission to bring autonomy to software engineering. While others were using models...",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0176,Ralph (snarktank),https://github.com/snarktank/ralph,external,github.com,ok,200,https://github.com/snarktank/ralph,text/html; charset=utf-8,GitHub - snarktank/ralph: Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete. Ā· GitHub,Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete. - GitHub - snarktank/ralph: Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete.,snarktank/ralph,21006,2042,76,Ralph is an autonomous AI agent loop that runs repeatedly until all PRD items are complete.,MIT,2026-07-12T10:30:45Z,,,2026-07-12T10:56:07+00:00 +ale-0177,ARIS (Auto-Research-In-Sleep),https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep,external,github.com,ok,200,https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep,text/html; charset=utf-8,"GitHub - wanshuiyin/Auto-claude-code-research-in-sleep: ARIS āš”ļø (Auto-Research-In-Sleep) ā€” Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in ā€” works with Claude Code, Codex, OpenClaw, or any LLM agent. Ā· GitHub","ARIS āš”ļø (Auto-Research-In-Sleep) ā€” Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in ā€” works with Claude Code, Codex, OpenClaw, or any LLM agent. - wanshuiyin/Auto-claude-code-research-in-sleep",wanshuiyin/Auto-claude-code-research-in-sleep,13292,1202,55,"ARIS āš”ļø (Auto-Research-In-Sleep) ā€” Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in ā€” works with Claude Code, Codex, OpenClaw, or any LLM agent.",MIT,2026-07-12T10:12:55Z,,,2026-07-12T10:56:07+00:00 +ale-0178,ralph-claude-code,https://github.com/frankbria/ralph-claude-code,external,github.com,ok,200,https://github.com/frankbria/ralph-claude-code,text/html; charset=utf-8,GitHub - frankbria/ralph-claude-code: Autonomous AI development loop for Claude Code with intelligent exit detection Ā· GitHub,Autonomous AI development loop for Claude Code with intelligent exit detection - frankbria/ralph-claude-code,frankbria/ralph-claude-code,9529,728,25,Autonomous AI development loop for Claude Code with intelligent exit detection,MIT,2026-07-12T10:11:32Z,,,2026-07-12T10:56:07+00:00 +ale-0179,AutoAgent,https://github.com/kevinrgu/autoagent,external,github.com,ok,200,https://github.com/kevinrgu/autoagent,text/html; charset=utf-8,GitHub - kevinrgu/autoagent: autonomous harness engineering Ā· GitHub,autonomous harness engineering. Contribute to kevinrgu/autoagent development by creating an account on GitHub.,kevinrgu/autoagent,4535,499,8,autonomous harness engineering,,2026-07-12T05:59:55Z,,,2026-07-12T10:56:07+00:00 +ale-0180,ralph-orchestrator,https://github.com/mikeyobrien/ralph-orchestrator,external,github.com,ok,200,https://github.com/mikeyobrien/ralph-orchestrator,text/html; charset=utf-8,GitHub - mikeyobrien/ralph-orchestrator: An improved implementation of the Ralph Wiggum technique for autonomous AI agent orchestration Ā· GitHub,An improved implementation of the Ralph Wiggum technique for autonomous AI agent orchestration - mikeyobrien/ralph-orchestrator,mikeyobrien/ralph-orchestrator,2996,280,9,An improved implementation of the Ralph Wiggum technique for autonomous AI agent orchestration,MIT,2026-07-11T22:25:11Z,,,2026-07-12T10:56:07+00:00 +ale-0181,zeroshot,https://github.com/the-open-engine/zeroshot,external,github.com,ok,200,https://github.com/the-open-engine/zeroshot,text/html; charset=utf-8,"GitHub - the-open-engine/zeroshot: Your autonomous engineering team in a CLI. The agent loop produces senior-level code that you can actually trust in prod because of non-negotiable feedback from independent reviewers. Supports Claude Code, OpenAI Codex, OpenCode, and Gemini CLI with trivial setup. Ā· GitHub","Your autonomous engineering team in a CLI. The agent loop produces senior-level code that you can actually trust in prod because of non-negotiable feedback from independent reviewers. Supports Claude Code, OpenAI Codex, OpenCode, and Gemini CLI with trivial setup. - the-open-engine/zeroshot",the-open-engine/zeroshot,1636,141,54,"Your autonomous engineering team in a CLI. The agent loop produces senior-level code that you can actually trust in prod because of non-negotiable feedback from independent reviewers. Supports Claude Code, OpenAI Codex, OpenCode, and Gemini CLI with trivial setup.",MIT,2026-07-12T07:51:18Z,,,2026-07-12T10:56:07+00:00 +ale-0182,ralphex,https://github.com/umputun/ralphex,external,github.com,ok,200,https://github.com/umputun/ralphex,text/html; charset=utf-8,GitHub - umputun/ralphex: Extended Ralph loop for autonomous AI-driven plan execution Ā· GitHub,Extended Ralph loop for autonomous AI-driven plan execution - umputun/ralphex,umputun/ralphex,1362,108,2,Extended Ralph loop for autonomous AI-driven plan execution,MIT,2026-07-12T08:16:33Z,,,2026-07-12T10:56:07+00:00 +ale-0183,Loki Mode,https://github.com/asklokesh/loki-mode,external,github.com,ok,200,https://github.com/asklokesh/loki-mode,text/html; charset=utf-8,"GitHub - asklokesh/loki-mode: Multi-agent autonomous SDLC framework. Spec to deployed app. PRD, GitHub issue, OpenAPI/JSON/YAML, or one-line brief. 5 AI providers, 11 quality gates. Ā· GitHub","Multi-agent autonomous SDLC framework. Spec to deployed app. PRD, GitHub issue, OpenAPI/JSON/YAML, or one-line brief. 5 AI providers, 11 quality gates. - asklokesh/loki-mode",asklokesh/loki-mode,1014,198,3,"Multi-agent autonomous SDLC framework. Spec to deployed app. PRD, GitHub issue, OpenAPI/JSON/YAML, or one-line brief. 5 AI providers, 11 quality gates.",NOASSERTION,2026-07-10T18:26:15Z,,,2026-07-12T10:56:07+00:00 +ale-0184,ralph (iannuttall),https://github.com/iannuttall/ralph,external,github.com,ok,200,https://github.com/iannuttall/ralph,text/html; charset=utf-8,"GitHub - iannuttall/ralph: A minimal, fileā€‘based agent loop for autonomous coding. Ā· GitHub","A minimal, fileā€‘based agent loop for autonomous coding. - iannuttall/ralph",iannuttall/ralph,932,90,9,"A minimal, fileā€‘based agent loop for autonomous coding.",,2026-07-11T16:27:54Z,,,2026-07-12T10:56:07+00:00 +ale-0185,ralph-loop-agent,https://github.com/vercel-labs/ralph-loop-agent,external,github.com,ok,200,https://github.com/vercel-labs/ralph-loop-agent,text/html; charset=utf-8,GitHub - vercel-labs/ralph-loop-agent: Continuous Autonomy for the AI SDK Ā· GitHub,Continuous Autonomy for the AI SDK. Contribute to vercel-labs/ralph-loop-agent development by creating an account on GitHub.,vercel-labs/ralph-loop-agent,815,83,2,Continuous Autonomy for the AI SDK,Apache-2.0,2026-07-10T21:31:57Z,,,2026-07-12T10:56:07+00:00 +ale-0186,Open Ralph Wiggum,https://github.com/Th0rgal/open-ralph-wiggum,external,github.com,ok,200,https://github.com/Th0rgal/open-ralph-wiggum,text/html; charset=utf-8,"GitHub - Th0rgal/open-ralph-wiggum: Type `ralph ""prompt""` to start open code in a ralph loop. Also supports a prompt file & status check. Open Code, Claude Code, Codex, Copilot Ā· GitHub","Type `ralph ""prompt""` to start open code in a ralph loop. Also supports a prompt file & status check. Open Code, Claude Code, Codex, Copilot - Th0rgal/open-ralph-wiggum",Th0rgal/open-ralph-wiggum,1841,142,8,"Type `ralph ""prompt""` to start open code in a ralph loop. Also supports a prompt file & status check. Open Code, Claude Code, Codex, Copilot",MIT,2026-07-12T01:14:55Z,,,2026-07-12T10:56:07+00:00 +ale-0187,Superpowers 6,https://blog.fsck.com/2026/06/15/Superpowers-6/,external,blog.fsck.com,ok,200,https://blog.fsck.com/2026/06/15/Superpowers-6/,text/html; charset=utf-8,Superpowers 6 ā€” Massively Parallel Procrastination,"I'm Jesse. I make stuff. Software, hardware. Very occasionally, trouble.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0188,Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality,https://arxiv.org/abs/2607.03691,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.03691,text/html; charset=utf-8,[2607.03691] Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality,Abstract page for arXiv paper 2607.03691: Don't Blame the Large Language Model: How Scaffolding Evolution Shapes Coding Agent Quality,,,,,,,,2607.03691,,2026-07-12T10:56:07+00:00 +ale-0189,Introducing Devin Security Swarm,https://cognition.com/blog/introducing-devin-security-swarm,external,cognition.com,ok,200,https://cognition.com/blog/introducing-devin-security-swarm,text/html; charset=utf-8,Introducing Devin Security Swarm | Cognition,"Devin Security Swarm finds vulnerabilities across the codebase, validates exploitability at runtime, and ships remediation PRs.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0190,Towards Self-Driving Codebases,https://cursor.com/blog/self-driving-codebases,external,cursor.com,ok,200,https://cursor.com/blog/self-driving-codebases,text/html; charset=utf-8,Towards self-driving codebases Ā· Cursor,We're making a part of our multi-agent research harness available to try today in preview.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0191,Looper,https://github.com/ksimback/looper,external,github.com,ok,200,https://github.com/ksimback/looper,text/html; charset=utf-8,"GitHub - ksimback/looper: Design visual, review-gated agent loops for Claude Code before you run them. Ā· GitHub","Design visual, review-gated agent loops for Claude Code before you run them. - ksimback/looper",ksimback/looper,665,58,0,"Design visual, review-gated agent loops for Claude Code before you run them.",MIT,2026-07-12T08:16:42Z,,,2026-07-12T10:56:07+00:00 +ale-0192,Agent Apprenticeship,https://github.com/Forsy-AI/agent-apprenticeship,external,github.com,ok,200,https://github.com/Forsy-AI/agent-apprenticeship,text/html; charset=utf-8,"GitHub - Forsy-AI/agent-apprenticeship: The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents. Ā· GitHub","The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents. - Forsy-AI/agent-apprenticeship",Forsy-AI/agent-apprenticeship,1312,54,0,"The living ecosystem where AI agents complete tasks through workflow loops, improve through iterative execution, are evaluated by mentor agents or humans in the loop, and turn completed work into reusable work experience and data to improve future agents.",MIT,2026-07-11T18:44:11Z,,,2026-07-12T10:56:07+00:00 +ale-0193,Scholar Loop,https://github.com/renee-jia/scholar-loop,external,github.com,ok,200,https://github.com/renee-jia/scholar-loop,text/html; charset=utf-8,"GitHub - renee-jia/scholar-loop: An autonomous AI scientist: a multi-agent loop over literature, experiments, self-critique and write-up, with deterministic guards against reward-hacking and hallucination. Ā· GitHub","An autonomous AI scientist: a multi-agent loop over literature, experiments, self-critique and write-up, with deterministic guards against reward-hacking and hallucination. - renee-jia/scholar-loop",renee-jia/scholar-loop,461,35,0,"An autonomous AI scientist: a multi-agent loop over literature, experiments, self-critique and write-up, with deterministic guards against reward-hacking and hallucination.",MIT,2026-07-08T05:18:54Z,,,2026-07-12T10:56:07+00:00 +ale-0194,Factory: Incident Response Automation,https://factory.ai/news/incident-response,external,factory.ai,ok,200,https://factory.ai/news/incident-response,text/html; charset=utf-8,Incident Response | Factory.ai Factory.ai Logo Arrow Right Icon,"On-call alerts have always been stomach-dropping moments. Someone's dinner, weekend, or launch review gets hijacked for ...",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0195,loop-engineering (Cobus Greyling),https://github.com/cobusgreyling/loop-engineering,external,github.com,ok,200,https://github.com/cobusgreyling/loop-engineering,text/html; charset=utf-8,"GitHub - cobusgreyling/loop-engineering: Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audit, loop-init, loop-cost. Ā· GitHub","Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audit, loop-init, loop-cost. - cobusgreyling/loop-engineering",cobusgreyling/loop-engineering,7147,901,34,"Practical patterns, starters & CLI tools for loop engineering with AI coding agents. Design systems that prompt and orchestrate agents (inspired by Addy Osmani and Boris Cherny). Includes loop-audit, loop-init, loop-cost.",MIT,2026-07-12T10:46:55Z,,,2026-07-12T10:56:07+00:00 +ale-0196,AutoCVE,https://github.com/larlarua/AutoCVE,external,github.com,ok,200,https://github.com/larlarua/AutoCVE,text/html; charset=utf-8,"GitHub - larlarua/AutoCVE: Agent-driven automated CVE discovery platform for source code auditing, vulnerability verification, and report generation. Ā· GitHub","Agent-driven automated CVE discovery platform for source code auditing, vulnerability verification, and report generation. - larlarua/AutoCVE",larlarua/AutoCVE,1200,78,20,"Agent-driven automated CVE discovery platform for source code auditing, vulnerability verification, and report generation.",AGPL-3.0,2026-07-12T09:37:20Z,,,2026-07-12T10:56:07+00:00 +ale-0197,LoongFlow (Baidu),https://github.com/baidu-baige/LoongFlow,external,github.com,ok,200,https://github.com/baidu-baige/LoongFlow,text/html; charset=utf-8,"GitHub - baidu-baige/LoongFlow: LoongFlow is an expert-grade Agent framework for Loop Engineering. Through a Plan-Execute-Summary loop and structured experiential memory, it enables AI to continuously think, execute, reflect, and evolve across complex software engineering, mathematical, and machine learning tasks. Ā· GitHub","LoongFlow is an expert-grade Agent framework for Loop Engineering. Through a Plan-Execute-Summary loop and structured experiential memory, it enables AI to continuously think, execute, reflect, and evolve across complex software engineering, mathematical, and machine learning tasks. - baidu-baige/LoongFlow",baidu-baige/LoongFlow,448,51,0,"LoongFlow is an expert-grade Agent framework for Loop Engineering. Through a Plan-Execute-Summary loop and structured experiential memory, it enables AI to continuously think, execute, reflect, and evolve across complex software engineering, mathematical, and machine learning tasks.",Apache-2.0,2026-07-12T08:17:12Z,,,2026-07-12T10:56:07+00:00 +ale-0198,cc10x,https://github.com/romiluz13/cc10x,external,github.com,ok,200,https://github.com/romiluz13/cc10x,text/html; charset=utf-8,"GitHub - romiluz13/cc10x: The Loop Engine for Claude Code ā€” engineer the loop, not the prompt. 1 router Ā· 9 agents Ā· 16 skills Ā· 4 workflows. Fail-closed gates, test honesty, anti-anchored review. Ā· GitHub","The Loop Engine for Claude Code ā€” engineer the loop, not the prompt. 1 router Ā· 9 agents Ā· 16 skills Ā· 4 workflows. Fail-closed gates, test honesty, anti-anchored review. - romiluz13/cc10x",romiluz13/cc10x,150,24,1,"The Loop Engine for Claude Code ā€” engineer the loop, not the prompt. 1 router Ā· 9 agents Ā· 16 skills Ā· 4 workflows. Fail-closed gates, test honesty, anti-anchored review.",MIT,2026-07-06T11:15:54Z,,,2026-07-12T10:56:07+00:00 +ale-0199,RigorLoop,https://github.com/ronikobrosly/RigorLoop,external,github.com,ok,200,https://github.com/ronikobrosly/RigorLoop,text/html; charset=utf-8,"GitHub - ronikobrosly/RigorLoop: A statistically-sound agentic build framework that employs agentic loops to create code artifacts (whether a script, a skill markdown file, etc). Crucially, it splits verification data into the classic data science-like dev, validation, and final test sets to avoid overfitting. Ā· GitHub","A statistically-sound agentic build framework that employs agentic loops to create code artifacts (whether a script, a skill markdown file, etc). Crucially, it splits verification data into the classic data science-like dev, validation, and final test sets to avoid overfitting. - GitHub - ronikobrosly/RigorLoop: A statistically-sound agentic build framework that employs agentic loops to create code artifacts (whether a script, a skill markdown file, etc). Crucially, it splits verification data into the classic data science-like dev, validation, and final test sets to avoid overfitting.",ronikobrosly/RigorLoop,122,0,1,"A statistically-sound agentic build framework that employs agentic loops to create code artifacts (whether a script, a skill markdown file, etc). Crucially, it splits verification data into the classic data science-like dev, validation, and final test sets to avoid overfitting.",MIT,2026-07-11T14:36:49Z,,,2026-07-12T10:56:07+00:00 +ale-0200,Open-Inspect,https://github.com/ColeMurray/background-agents,external,github.com,ok,200,https://github.com/ColeMurray/background-agents,text/html; charset=utf-8,GitHub - ColeMurray/background-agents: An open-source background agents coding system Ā· GitHub,An open-source background agents coding system. Contribute to ColeMurray/background-agents development by creating an account on GitHub.,ColeMurray/background-agents,2144,335,52,An open-source background agents coding system,MIT,2026-07-12T10:55:19Z,,,2026-07-12T10:56:07+00:00 +ale-0201,T3MP3ST,https://github.com/elder-plinius/T3MP3ST,external,github.com,ok,200,https://github.com/elder-plinius/T3MP3ST,text/html; charset=utf-8,GitHub - elder-plinius/T3MP3ST: autonomous red teaming platform; multi-agent offensive-security meta-harness Ā· GitHub,autonomous red teaming platform; multi-agent offensive-security meta-harness - elder-plinius/T3MP3ST,elder-plinius/T3MP3ST,4472,954,42,autonomous red teaming platform; multi-agent offensive-security meta-harness,AGPL-3.0,2026-07-12T10:26:19Z,,,2026-07-12T10:56:07+00:00 +ale-0202,Loom,https://github.com/valkor-ai/loom,external,github.com,ok,200,https://github.com/valkor-ai/loom,text/html; charset=utf-8,GitHub - valkor-ai/loom: Loop engineering for agentic software delivery. Ā· GitHub,Loop engineering for agentic software delivery. Contribute to valkor-ai/loom development by creating an account on GitHub.,valkor-ai/loom,534,53,0,Loop engineering for agentic software delivery.,Apache-2.0,2026-07-12T07:15:46Z,,,2026-07-12T10:56:07+00:00 +ale-0203,Inferoa,https://github.com/agentic-in/inferoa,external,github.com,ok,200,https://github.com/agentic-in/inferoa,text/html; charset=utf-8,GitHub - agentic-in/inferoa: Inference-native Tokenmaxxing Agent Harness for Loop Engineering Ā· GitHub,Inference-native Tokenmaxxing Agent Harness for Loop Engineering - agentic-in/inferoa,agentic-in/inferoa,453,77,48,Inference-native Tokenmaxxing Agent Harness for Loop Engineering,Apache-2.0,2026-07-12T09:49:08Z,,,2026-07-12T10:56:07+00:00 +ale-0204,PlanWeave,https://github.com/GaosCode/PlanWeave,external,github.com,ok,200,https://github.com/GaosCode/PlanWeave,text/html; charset=utf-8,"GitHub - GaosCode/PlanWeave: PlanWeave is a file-backed loop engineering system for long-running coding agents. It turns fuzzy plans into claimable tasks, routes them through implementation and review agents, records every run, and keeps the loop recoverable. Ā· GitHub","PlanWeave is a file-backed loop engineering system for long-running coding agents. It turns fuzzy plans into claimable tasks, routes them through implementation and review agents, records every run, and keeps the loop recoverable. - GaosCode/PlanWeave",GaosCode/PlanWeave,207,12,0,"PlanWeave is a file-backed loop engineering system for long-running coding agents. It turns fuzzy plans into claimable tasks, routes them through implementation and review agents, records every run, and keeps the loop recoverable.",MIT,2026-07-12T09:32:08Z,,,2026-07-12T10:56:07+00:00 +ale-0205,A Week-Long Autonomous Voxel Manhattan Build,https://x.com/mattshumer_/status/2075268746315268138,external,x.com,ok,200,https://x.com/mattshumer_/status/2075268746315268138,text/html; charset=UTF-8,"Matt Shumer on X: ""GPT-5.6-Sol one-shotted this voxel-based Manhattan. Just look at the precision... it's insane. It ran for almost a week, completely autonomously, to get the job done. https://t.co/LZgthaBnqL"" / X","GPT-5.6-Sol one-shotted this voxel-based Manhattan. Just look at the precision... it's insane. It ran for almost a week, completely autonomously, to get the job done.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0206,Why Agentic Systems Must Produce Deterministic Outputs to Scale,https://streamzero.com/blog/posts/deep-dives-tools-technologies-architectures/agentic-patterns/why-agentic-systems-must-produce-deterministic-outputs-to-scale,external,streamzero.com,ok,200,https://streamzero.com/blog/posts/deep-dives-tools-technologies-architectures/agentic-patterns/why-agentic-systems-must-produce-deterministic-outputs-to-scale,text/html; charset=UTF-8,Why Agentic Systems Must Produce Deterministic Outputs to Scale,"Agentic systems are gaining traction, but their inherent non-determinism poses a significant challenge for production environments. This document argues that deterministic outputs are essential for scaling agentic systems, enabling validation, security, and compliance in critical applications.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0207,Stop Babysitting Your Coding Agent. Give It Backpressure.,https://generativeprogrammer.com/p/stop-babysitting-your-coding-agent,external,generativeprogrammer.com,ok,200,https://generativeprogrammer.com/p/stop-babysitting-your-coding-agent,text/html; charset=utf-8,Stop Babysitting Your Coding Agent. Give It Backpressure.,Backpressure is feedback that reaches the agent before the agent reaches the human.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0208,How to Build a Self-Verification Loop in Claude Code,https://dev.to/shipwithaiio/how-to-build-a-self-verification-loop-in-claude-code-3-layers-20-minutes-m1p,external,dev.to,ok,200,https://dev.to/shipwithaiio/how-to-build-a-self-verification-loop-in-claude-code-3-layers-20-minutes-m1p,text/html; charset=utf-8,"How to Build a Self-Verification Loop in Claude Code (3 Layers, 20 Minutes) - DEV Community Navigation menu Search Search Close More... Copy link Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode Enter fullscreen mode Exit fullscreen mode","Claude Code's Stop hook blocks the agent from finishing until verification passes. Combine it with... Tagged with ai, programming, productivity, claude.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0209,How to build a better agent harness with traces and evals,https://arize.com/blog/improve-ai-agents-traces-evals-harness/,external,arize.com,ok,200,https://arize.com/blog/improve-ai-agents-traces-evals-harness/,text/html; charset=UTF-8,How to build a better agent harness with traces and evals - Arize AI,"Agents are easy to prototype and hard to improve. A repeatable loop of traces, evals, failed-span inspection, and targeted harness changes makes agent behavior easier to debug and improve.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0210,Better Harness: A Recipe for Harness Hill-Climbing with Evals,https://www.langchain.com/blog/better-harness-a-recipe-for-harness-hill-climbing-with-evals,external,www.langchain.com,ok,200,https://www.langchain.com/blog/better-harness-a-recipe-for-harness-hill-climbing-with-evals,text/html; charset=utf-8,Better Harness: A Recipe for Harness Hill-Climbing with Evals,"We can build better agents by building better harnesses. But to autonomously build a ā€œbetterā€ harness, we need a strong learning signal to ā€œhill-climbā€ on. We share how we use evals as that signal, plus design decisions that help our agent generalize instead of overfit. Better-Harness is a system for iteratively sourcing and improving your harness with evals.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0211,Improving Deep Agents with harness engineering,https://www.langchain.com/blog/improving-deep-agents-with-harness-engineering,external,www.langchain.com,ok,200,https://www.langchain.com/blog/improving-deep-agents-with-harness-engineering,text/html; charset=utf-8,Improving Deep Agents with harness engineering,"Harness engineering improved LangChain's coding agent from Top 30 to Top 5 on Terminal Bench using self-verification, tracing, and context optimization.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0212,OpenAI agent evals,https://developers.openai.com/api/docs/guides/agent-evals,external,developers.openai.com,ok,200,https://developers.openai.com/api/docs/guides/agent-evals,text/html; charset=utf-8,Evaluate agent workflows | OpenAI API,"Learn how to evaluate agent workflows with traces, graders, datasets, and evaluation runs on the OpenAI platform.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0213,Promptfoo OpenAI Agents provider,https://www.promptfoo.dev/docs/providers/openai-agents/,external,www.promptfoo.dev,ok,200,https://www.promptfoo.dev/docs/providers/openai-agents/,text/html; charset=utf-8,OpenAI Agents | Promptfoo,"Test OpenAI Agents with tools, handoffs, sessions, sandbox workflows, and tracing in promptfoo.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0214,Inspect AI,https://github.com/UKGovernmentBEIS/inspect_ai,external,github.com,ok,200,https://github.com/UKGovernmentBEIS/inspect_ai,text/html; charset=utf-8,GitHub - UKGovernmentBEIS/inspect_ai: Inspect: A framework for large language model evaluations Ā· GitHub,Inspect: A framework for large language model evaluations - UKGovernmentBEIS/inspect_ai,UKGovernmentBEIS/inspect_ai,2332,599,239,Inspect: A framework for large language model evaluations,MIT,2026-07-12T08:36:59Z,,,2026-07-12T10:56:07+00:00 +ale-0215,OpenTelemetry Semantic Conventions for Generative AI Systems,https://opentelemetry.io/docs/specs/semconv/gen-ai/,external,opentelemetry.io,ok,200,https://opentelemetry.io/docs/specs/semconv/gen-ai/,text/html; charset=UTF-8,Moved: Generative AI semantic conventions | OpenTelemetry The OpenTelemetry Logo,Important GenAI semantic conventions have moved to the OpenTelemetry GenAI semantic conventions repository. This page has moved and is no longer maintained in this repository.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0216,AgentOps,https://github.com/AgentOps-AI/agentops,external,github.com,ok,200,https://github.com/AgentOps-AI/agentops,text/html; charset=utf-8,"GitHub - AgentOps-AI/agentops: Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI Ā· GitHub","Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI - AgentOps-AI/agentops",AgentOps-AI/agentops,5696,606,170,"Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including CrewAI, Agno, OpenAI Agents SDK, Langchain, Autogen, AG2, and CamelAI",MIT,2026-07-11T15:47:12Z,,,2026-07-12T10:56:07+00:00 +ale-0217,Langfuse,https://github.com/langfuse/langfuse,external,github.com,ok,200,https://github.com/langfuse/langfuse,text/html; charset=utf-8,"GitHub - langfuse/langfuse: šŸŖ¢ Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. šŸŠYC W23 Ā· GitHub","šŸŖ¢ Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. šŸŠYC W23 - GitHub - langfuse/langfuse: šŸŖ¢ Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. šŸŠYC W23",langfuse/langfuse,30955,3264,714,"šŸŖ¢ Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. šŸŠYC W23",NOASSERTION,2026-07-12T10:54:59Z,,,2026-07-12T10:56:07+00:00 +ale-0218,LangSmith,https://www.langchain.com/langsmith,external,www.langchain.com,ok,200,https://www.langchain.com/langsmith/observability,text/html; charset=utf-8,LangSmith: Agent & LLM Observability Platform,"Complete AI agent and LLM observability platform with tracing and real-time monitoring. Debug agents, find failures fast, and track costs and latency.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0219,Arize Phoenix,https://github.com/Arize-ai/phoenix,external,github.com,ok,200,https://github.com/Arize-ai/phoenix,text/html; charset=utf-8,GitHub - Arize-ai/phoenix: AI Observability & Evaluation Ā· GitHub,AI Observability & Evaluation. Contribute to Arize-ai/phoenix development by creating an account on GitHub.,Arize-ai/phoenix,10513,977,722,AI Observability & Evaluation,NOASSERTION,2026-07-12T07:41:35Z,,,2026-07-12T10:56:07+00:00 +ale-0220,Braintrust,https://www.braintrust.dev/,external,www.braintrust.dev,ok,200,https://www.braintrust.dev/,text/html; charset=utf-8,Braintrust - The AI observability platform for building quality AI products,"Ship quality AI at scale. Braintrust is the AI observability platform for tracing production, running evals, and catching regressions before they reach users.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0221,Weave,https://docs.wandb.ai/weave,external,docs.wandb.ai,ok,200,https://docs.wandb.ai/weave,text/html; charset=utf-8,W&B Weave - Weights & Biases Documentation,"Track, test, and improve language model apps with W&B Weave",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0222,Agentic Verification of Software Systems,https://arxiv.org/abs/2511.17330,external,arxiv.org,ok,200,https://arxiv.org/abs/2511.17330,text/html; charset=utf-8,[2511.17330] Agentic Verification of Software Systems,Abstract page for arXiv paper 2511.17330: Agentic Verification of Software Systems,,,,,,,,2511.17330,,2026-07-12T10:56:07+00:00 +ale-0223,Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses,https://arxiv.org/abs/2604.25850,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.25850,text/html; charset=utf-8,[2604.25850] Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses,Abstract page for arXiv paper 2604.25850: Agentic Harness Engineering: Observability-Driven Automatic Evolution of Coding-Agent Harnesses,,,,,,,,2604.25850,,2026-07-12T10:56:07+00:00 +ale-0224,"A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance",https://arxiv.org/abs/2603.18096,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.18096,text/html; charset=utf-8,"[2603.18096] A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance","Abstract page for arXiv paper 2603.18096: A Trace-Based Assurance Framework for Agentic AI Orchestration: Contracts, Testing, and Governance",,,,,,,,2603.18096,,2026-07-12T10:56:07+00:00 +ale-0225,Meta-Harness: End-to-End Optimization of Model Harnesses,https://arxiv.org/abs/2603.28052,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.28052,text/html; charset=utf-8,[2603.28052] Meta-Harness: End-to-End Optimization of Model Harnesses,Abstract page for arXiv paper 2603.28052: Meta-Harness: End-to-End Optimization of Model Harnesses,,,,,,,,2603.28052,,2026-07-12T10:56:07+00:00 +ale-0226,Self-Evolving Agents with Anytime-Valid Certificates,https://arxiv.org/abs/2607.00871,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.00871,text/html; charset=utf-8,[2607.00871] Self-Evolving Agents with Anytime-Valid Certificates,Abstract page for arXiv paper 2607.00871: Self-Evolving Agents with Anytime-Valid Certificates,,,,,,,,2607.00871,,2026-07-12T10:56:07+00:00 +ale-0227,Delayed Verification Destabilizes Multi-Agent LLM Belief,https://arxiv.org/abs/2606.27409,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.27409,text/html; charset=utf-8,[2606.27409] Delayed Verification Destabilizes Multi-Agent LLM Belief: Instability Thresholds and Optimal Corrector Placement,Abstract page for arXiv paper 2606.27409: Delayed Verification Destabilizes Multi-Agent LLM Belief: Instability Thresholds and Optimal Corrector Placement,,,,,,,,2606.27409,,2026-07-12T10:56:07+00:00 +ale-0228,Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory,https://arxiv.org/abs/2606.06523,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.06523,text/html; charset=utf-8,[2606.06523] Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory,Abstract page for arXiv paper 2606.06523: Lean4Agent: Formal Modeling and Verification for Agent Workflow and Trajectory,,,,,,,,2606.06523,,2026-07-12T10:56:07+00:00 +ale-0229,"Regimes: An Auditable, Held-Out-Gated Improvement Loop",https://arxiv.org/abs/2606.10241,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.10241,text/html; charset=utf-8,"[2606.10241] Regimes: An Auditable, Held-Out-Gated Improvement Loop Demonstrated on LongMemEval with ActiveGraph","Abstract page for arXiv paper 2606.10241: Regimes: An Auditable, Held-Out-Gated Improvement Loop Demonstrated on LongMemEval with ActiveGraph",,,,,,,,2606.10241,,2026-07-12T10:56:07+00:00 +ale-0230,Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents,https://arxiv.org/abs/2605.22608,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.22608,text/html; charset=utf-8,[2605.22608] Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents,Abstract page for arXiv paper 2605.22608: Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents,,,,,,,,2605.22608,,2026-07-12T10:56:07+00:00 +ale-0231,Agentic Code Review,https://addyosmani.com/blog/agentic-code-review/,external,addyosmani.com,ok,200,https://addyosmani.com/blog/agentic-code-review/,text/html; charset=UTF-8,AddyOsmani.com - Agentic Code Review,"Coding agents are extraordinarily good now, and getting better fast. The interesting consequence is that the hard part of engineering moved from writing code...",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0232,Using DSPy to Evaluate and Improve Datasette Agent's SQL System Prompts,https://simonwillison.net/2026/Jul/2/dspy-datasette-agent-prompts/,external,simonwillison.net,ok,200,https://simonwillison.net/2026/Jul/2/dspy-datasette-agent-prompts/,text/html; charset=utf-8,Research: Using DSPy to evaluate and improve Datasette Agent's SQL system prompts,"Leveraging the DSPy framework, this project evaluates and refines the core production system prompts used by Datasette Agentā€™s read-only SQL question answerer. The methodology involves a harness where DSPy agents ā€¦",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0233,agentops (boshu2),https://github.com/boshu2/agentops,external,github.com,ok,200,https://github.com/boshu2/agentops,text/html; charset=utf-8,"GitHub - boshu2/agentops: Independent verification for coding agents. A change isn't done until a different model or a real test checks it, and the verdict is recorded in your repo. Ā· GitHub","Independent verification for coding agents. A change isn't done until a different model or a real test checks it, and the verdict is recorded in your repo. - boshu2/agentops",boshu2/agentops,409,40,6,"Independent verification for coding agents. A change isn't done until a different model or a real test checks it, and the verdict is recorded in your repo.",Apache-2.0,2026-07-12T10:34:38Z,,,2026-07-12T10:56:07+00:00 +ale-0234,HALO (Hierarchical Agent Loop Optimizer),https://github.com/context-labs/halo,external,github.com,ok,200,https://github.com/context-labs/halo,text/html; charset=utf-8,GitHub - context-labs/HALO: Hierarchal Agent Loop Optimizer Ā· GitHub,Hierarchal Agent Loop Optimizer. Contribute to context-labs/HALO development by creating an account on GitHub.,context-labs/halo,1089,77,8,Hierarchal Agent Loop Optimizer,,2026-07-12T04:46:11Z,,,2026-07-12T10:56:07+00:00 +ale-0235,"Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions",https://arxiv.org/abs/2607.03935,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.03935,text/html; charset=utf-8,"[2607.03935] Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions","Abstract page for arXiv paper 2607.03935: Harness-Aware Self-Evolving: Co-Evolving Model Weights, Harness, and Task Solutions",,,,,,,,2607.03935,,2026-07-12T10:56:07+00:00 +ale-0236,Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference,https://arxiv.org/abs/2607.02882,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.02882,text/html; charset=utf-8,[2607.02882] Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference,Abstract page for arXiv paper 2607.02882: Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference,,,,,,,,2607.02882,,2026-07-12T10:56:07+00:00 +ale-0237,SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use,https://arxiv.org/abs/2607.01874,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.01874,text/html; charset=utf-8,[2607.01874] SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use,Abstract page for arXiv paper 2607.01874: SkillCoach: Self-Evolving Rubrics for Evaluating and Enhancing Agentic Skill-Use,,,,,,,,2607.01874,,2026-07-12T10:56:07+00:00 +ale-0238,SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Bug Reproduction Tests,https://arxiv.org/abs/2607.00990,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.00990,text/html; charset=utf-8,[2607.00990] SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests,Abstract page for arXiv paper 2607.00990: SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests,,,,,,,,2607.00990,,2026-07-12T10:56:07+00:00 +ale-0239,Agentic coding notes,https://danluu.com/ai-coding/,external,danluu.com,ok,200,https://danluu.com/ai-coding/,text/html; charset=utf-8,"Agentic test processes, LLM benchmarks, and other notes on agentic coding from Galapagos Island",,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0240,Understanding Is the New Bottleneck,https://www.geoffreylitt.com/2026/07/02/understanding-is-the-new-bottleneck.html,external,www.geoffreylitt.com,ok,200,https://www.geoffreylitt.com/2026/07/02/understanding-is-the-new-bottleneck.html,text/html; charset=UTF-8,Understanding is the new bottleneck,"Agents can write code faster than we can absorb it. Here's why it still matters for humans to understand what they build ā€” and some techniques for doing that efficiently: explainer docs, quizzes, micro-worlds, and shared spaces.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0241,Verifying Agentic Development at Scale,https://cognition.com/blog/testing-development,external,cognition.com,ok,200,https://cognition.com/blog/testing-development,text/html; charset=utf-8,Verifying Agentic Development at Scale | Cognition,What weā€™ve learned building end-to-end testing capabilities in Devinā€™s virtual machine,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0242,Loop Engineering Without Verification Is Just Automation,https://www.sonarsource.com/blog/loop-engineering-without-verification-is-just-automation/,external,www.sonarsource.com,ok,200,https://www.sonarsource.com/blog/loop-engineering-without-verification-is-just-automation/,text/html,Loop engineering without verification is just automation | Sonar,Explore how LLM reviewers and deterministic checks work together to keep coding agent loops from shipping unfinished code.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0243,SkillSpec,https://github.com/modiqo/skillspec,external,github.com,ok,200,https://github.com/modiqo/skillspec,text/html; charset=utf-8,"GitHub - modiqo/skillspec: SkillSpec makes agent skills followable, testable, and provable with Doctor risk reports, guided imports, structured contracts, and alignment proof. Ā· GitHub","SkillSpec makes agent skills followable, testable, and provable with Doctor risk reports, guided imports, structured contracts, and alignment proof. - modiqo/skillspec",modiqo/skillspec,938,58,7,"SkillSpec makes agent skills followable, testable, and provable with Doctor risk reports, guided imports, structured contracts, and alignment proof.",Apache-2.0,2026-07-12T06:33:37Z,,,2026-07-12T10:56:07+00:00 +ale-0244,Shepherd,https://github.com/shepherd-agents/shepherd,external,github.com,ok,200,https://github.com/shepherd-agents/shepherd,text/html; charset=utf-8,"GitHub - shepherd-agents/shepherd: A runtime substrate that turns an agent's execution into a reversible, Git-like trace, so meta-agents can observe, fork, replay, and revert any run. Couples agent and environments in a copy-on-write fork ~5x faster than docker commit, with ~95% KV-cache reuse on replay. Framework built for meta-agents to supervise, optimize, and train other agents Ā· GitHub","A runtime substrate that turns an agent's execution into a reversible, Git-like trace, so meta-agents can observe, fork, replay, and revert any run. Couples agent and environments in a copy-on-write fork ~5x faster than docker commit, with ~95% KV-cache reuse on replay. Framework built for meta-agents to supervise, optimize, and train other agents - shepherd-agents/shepherd",shepherd-agents/shepherd,1356,96,7,"A runtime substrate that turns an agent's execution into a reversible, Git-like trace, so meta-agents can observe, fork, replay, and revert any run. Couples agent and environments in a copy-on-write fork ~5x faster than docker commit, with ~95% KV-cache reuse on replay. Framework built for meta-agents to supervise, optimize, and train other agents",MIT,2026-07-12T10:45:15Z,,,2026-07-12T10:56:07+00:00 +ale-0245,AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation,https://arxiv.org/abs/2607.06273,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06273,text/html; charset=utf-8,[2607.06273] AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation,Abstract page for arXiv paper 2607.06273: AgentTether: Graph-Guided Diagnosis and Runtime Intervention for Reliable LLM Agent Operation,,,,,,,,2607.06273,,2026-07-12T10:56:07+00:00 +ale-0246,SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review,https://arxiv.org/abs/2607.06065,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06065,text/html; charset=utf-8,[2607.06065] SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review,Abstract page for arXiv paper 2607.06065: SWE-Review: Closing the Loop on Issue Resolution with Agentic Code Review,,,,,,,,2607.06065,,2026-07-12T10:56:07+00:00 +ale-0247,"Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode",https://arxiv.org/abs/2607.07405,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07405,text/html; charset=utf-8,"[2607.07405] Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents","Abstract page for arXiv paper 2607.07405: Reason Less, Verify More: Deterministic Gates Recover a Silent Policy-Violation Failure Mode in Tool-Using LLM Agents",,,,,,,,2607.07405,,2026-07-12T10:56:07+00:00 +ale-0248,Harnessing Code Agents for Automatic Software Verification,https://arxiv.org/abs/2607.06341,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06341,text/html; charset=utf-8,[2607.06341] Harnessing Code Agents for Automatic Software Verification,Abstract page for arXiv paper 2607.06341: Harnessing Code Agents for Automatic Software Verification,,,,,,,,2607.06341,,2026-07-12T10:56:07+00:00 +ale-0249,LLM-as-a-Verifier: A General-Purpose Verification Framework,https://arxiv.org/abs/2607.05391,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05391,text/html; charset=utf-8,[2607.05391] LLM-as-a-Verifier: A General-Purpose Verification Framework,Abstract page for arXiv paper 2607.05391: LLM-as-a-Verifier: A General-Purpose Verification Framework,,,,,,,,2607.05391,,2026-07-12T10:56:07+00:00 +ale-0250,From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents,https://arxiv.org/abs/2607.08028,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08028,text/html; charset=utf-8,[2607.08028] From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents,Abstract page for arXiv paper 2607.08028: From Prompts to Contracts: Harness Engineering for Auditable Enterprise LLM Agents,,,,,,,,2607.08028,,2026-07-12T10:56:07+00:00 +ale-0251,From Noisy Traces to Root Causes: Structural Trajectory Analysis and Causal Extraction for Agent Optimization,https://arxiv.org/abs/2607.07702,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07702,text/html; charset=utf-8,[2607.07702] From Noisy Traces to Root Causes: Structural Trajectory Analysis and Causal Extraction for Agent Optimization,Abstract page for arXiv paper 2607.07702: From Noisy Traces to Root Causes: Structural Trajectory Analysis and Causal Extraction for Agent Optimization,,,,,,,,2607.07702,,2026-07-12T10:56:07+00:00 +ale-0252,Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems,https://arxiv.org/abs/2607.07989,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07989,text/html; charset=utf-8,[2607.07989] Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems,Abstract page for arXiv paper 2607.07989: Who Broke the System? Failure Localization in LLM-Based Multi-Agent Systems,,,,,,,,2607.07989,,2026-07-12T10:56:07+00:00 +ale-0253,3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse,https://arxiv.org/abs/2607.07980,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07980,text/html; charset=utf-8,[2607.07980] 3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse,Abstract page for arXiv paper 2607.07980: 3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse,,,,,,,,2607.07980,,2026-07-12T10:56:07+00:00 +ale-0254,grill-for-unknowns,https://github.com/nicobailon/grill-for-unknowns,external,github.com,ok,200,https://github.com/nicobailon/grill-for-unknowns,text/html; charset=utf-8,"GitHub - nicobailon/grill-for-unknowns: Agent skill for finding unknowns, grilling plans, and reaching shared understanding before implementation Ā· GitHub","Agent skill for finding unknowns, grilling plans, and reaching shared understanding before implementation - nicobailon/grill-for-unknowns",nicobailon/grill-for-unknowns,160,5,0,"Agent skill for finding unknowns, grilling plans, and reaching shared understanding before implementation",MIT,2026-07-12T09:18:10Z,,,2026-07-12T10:56:07+00:00 +ale-0255,Persuasion Attacks Can Decrease Effectiveness of CoT Monitoring,https://arxiv.org/abs/2607.08066,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08066,text/html; charset=utf-8,[2607.08066] Persuasion Attacks Can Decrease Effectiveness of CoT Monitoring,Abstract page for arXiv paper 2607.08066: Persuasion Attacks Can Decrease Effectiveness of CoT Monitoring,,,,,,,,2607.08066,,2026-07-12T10:56:07+00:00 +ale-0256,Physics-Audited Agentic Discovery in Scientific Machine Learning,https://arxiv.org/abs/2607.07379,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07379,text/html; charset=utf-8,[2607.07379] Physics-Audited Agentic Discovery in Scientific Machine Learning,Abstract page for arXiv paper 2607.07379: Physics-Audited Agentic Discovery in Scientific Machine Learning,,,,,,,,2607.07379,,2026-07-12T10:56:07+00:00 +ale-0257,Bug Report Specification Refinement with Trajectory Guidance for Automated Program Repair,https://arxiv.org/abs/2607.07882,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07882,text/html; charset=utf-8,[2607.07882] Bug Report Specification Refinement with Trajectory Guidance for Automated Program Repair,Abstract page for arXiv paper 2607.07882: Bug Report Specification Refinement with Trajectory Guidance for Automated Program Repair,,,,,,,,2607.07882,,2026-07-12T10:56:07+00:00 +ale-0258,Fable Harness,https://github.com/Miguok/fable-harness,external,github.com,ok,200,https://github.com/Miguok/fable-harness,text/html; charset=utf-8,"GitHub - Miguok/fable-harness: Make Claude Code work like a disciplined engineer: OODA, multi-party adversarial review, tiered model routing, fail-then-pass ā€” token-efficient by design (route heavy work to smaller models, isolate sub-agent context). Distilled from Fable to reinforce the Opus harness. Ā· GitHub","Make Claude Code work like a disciplined engineer: OODA, multi-party adversarial review, tiered model routing, fail-then-pass ā€” token-efficient by design (route heavy work to smaller models, isolate sub-agent context). Distilled from Fable to reinforce the Opus harness. - Miguok/fable-harness",Miguok/fable-harness,187,32,1,"Make Claude Code work like a disciplined engineer: OODA, multi-party adversarial review, tiered model routing, fail-then-pass ā€” token-efficient by design (route heavy work to smaller models, isolate sub-agent context). Distilled from Fable to reinforce the Opus harness.",MIT,2026-07-12T03:45:29Z,,,2026-07-12T10:56:07+00:00 +ale-0259,The lethal trifecta for AI agents,https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/,external,simonwillison.net,ok,200,https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/,text/html; charset=utf-8,"The lethal trifecta for AI agents: private data, untrusted content, and external communication",If you are a user of LLM systems that use tools (you can call them ā€œAI agentsā€ if you like) it is critically important that you understand the risk of ā€¦,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0260,Prompt injection series,https://simonwillison.net/series/prompt-injection/,external,simonwillison.net,ok,200,https://simonwillison.net/series/prompt-injection/,text/html; charset=utf-8,Simon Willison: Prompt injection,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0261,Agentic AI - Threats and Mitigations,https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/,external,genai.owasp.org,ok,200,https://genai.owasp.org/resource/agentic-ai-threats-and-mitigations/,text/html; charset=UTF-8,Agentic AI - OWASP Lists Threats and Mitigations,"Explore key threats and mitigation strategies for agentic AI, focusing on security measures to address vulnerabilities in AI applications and their potential risks.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0262,Designing AI agents to resist prompt injection,https://openai.com/index/designing-agents-to-resist-prompt-injection/,external,openai.com,restricted,403,https://openai.com/index/designing-agents-to-resist-prompt-injection/,text/html; charset=UTF-8,,,,,,,,,,,restricted_or_rate_limited,2026-07-12T10:56:07+00:00 +ale-0263,sandbox-runtime,https://github.com/anthropic-experimental/sandbox-runtime,external,github.com,ok,200,https://github.com/anthropic-experimental/sandbox-runtime,text/html; charset=utf-8,"GitHub - anthropic-experimental/sandbox-runtime: A lightweight sandboxing tool for enforcing filesystem and network restrictions on arbitrary processes at the OS level, without requiring a container. Ā· GitHub","A lightweight sandboxing tool for enforcing filesystem and network restrictions on arbitrary processes at the OS level, without requiring a container. - anthropic-experimental/sandbox-runtime",anthropic-experimental/sandbox-runtime,4637,357,125,"A lightweight sandboxing tool for enforcing filesystem and network restrictions on arbitrary processes at the OS level, without requiring a container.",Apache-2.0,2026-07-12T10:19:42Z,,,2026-07-12T10:56:07+00:00 +ale-0264,E2B,https://github.com/e2b-dev/E2B,external,github.com,ok,200,https://github.com/e2b-dev/E2B,text/html; charset=utf-8,"GitHub - e2b-dev/E2B: Open-source, secure environment with real-world tools for enterprise-grade agents. Ā· GitHub","Open-source, secure environment with real-world tools for enterprise-grade agents. - e2b-dev/E2B",e2b-dev/E2B,12935,964,61,"Open-source, secure environment with real-world tools for enterprise-grade agents.",Apache-2.0,2026-07-11T23:23:35Z,,,2026-07-12T10:56:07+00:00 +ale-0265,Modal Sandboxes,https://modal.com/docs/guide/sandboxes,external,modal.com,ok,200,https://modal.com/docs/guide/sandboxes,text/html,Sandboxes | Modal Docs,"This page is a high-level guide to Sandboxes, secure containers for executing untrusted user or agent code on Modal.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0266,Daytona,https://www.daytona.io/,external,www.daytona.io,ok,200,https://www.daytona.io/,text/html,Daytona - Secure Infrastructure for Running AI-Generated Code,"Deploy Al code with confidence using Daytona's lightning-fast infrastructure. 90ms environment creation, stateful operations, and enterprise-grade security.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0267,peerd,https://github.com/NotASithLord/peerd,external,github.com,ok,200,https://github.com/NotASithLord/peerd,text/html; charset=utf-8,"GitHub - NotASithLord/peerd: The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds peer-to-peer. BYOK, no backend, no telemetry. Ā· GitHub","The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds peer-to-peer. BYOK, no backend, no telemetry. - NotASithLord/peerd",NotASithLord/peerd,346,36,20,"The first AI agent harness native to the browser. A browser extension that runs a full agent loop where you already work: it drives your tabs, spins up sandboxed compute (JS notebooks, WASM Linux VMs, client-side apps), and shares what it builds peer-to-peer. BYOK, no backend, no telemetry.",Apache-2.0,2026-07-12T08:32:55Z,,,2026-07-12T10:56:07+00:00 +ale-0268,When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents,https://arxiv.org/abs/2607.05189,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05189,text/html; charset=utf-8,[2607.05189] When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents,Abstract page for arXiv paper 2607.05189: When Claws Remember but Do Not Tell: Stealthy Memory Injection in Persistent Personal Agents,,,,,,,,2607.05189,,2026-07-12T10:56:07+00:00 +ale-0269,Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses,https://arxiv.org/abs/2607.05029,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05029,text/html; charset=utf-8,[2607.05029] Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses,Abstract page for arXiv paper 2607.05029: Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses,,,,,,,,2607.05029,,2026-07-12T10:56:07+00:00 +ale-0270,Distributed Attacks in Persistent-State AI Control,https://arxiv.org/abs/2607.02514,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.02514,text/html; charset=utf-8,[2607.02514] Distributed Attacks in Persistent-State AI Control,Abstract page for arXiv paper 2607.02514: Distributed Attacks in Persistent-State AI Control,,,,,,,,2607.02514,,2026-07-12T10:56:07+00:00 +ale-0271,ElephantAgent: Contextual State Continuity in Agentic Systems,https://arxiv.org/abs/2607.01919,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.01919,text/html; charset=utf-8,[2607.01919] ElephantAgent: Contextual State Continuity in Agentic Systems,Abstract page for arXiv paper 2607.01919: ElephantAgent: Contextual State Continuity in Agentic Systems,,,,,,,,2607.01919,,2026-07-12T10:56:07+00:00 +ale-0272,Cloudflare security-audit-skill,https://github.com/cloudflare/security-audit-skill,external,github.com,ok,200,https://github.com/cloudflare/security-audit-skill,text/html; charset=utf-8,"GitHub - cloudflare/security-audit-skill: A coding-agent skill for multi-phase security audits with independently verified, machine-readable findings Ā· GitHub","A coding-agent skill for multi-phase security audits with independently verified, machine-readable findings - cloudflare/security-audit-skill",cloudflare/security-audit-skill,2435,180,2,"A coding-agent skill for multi-phase security audits with independently verified, machine-readable findings",MIT,2026-07-12T10:19:14Z,,,2026-07-12T10:56:07+00:00 +ale-0273,The Balkanization of Execution-Security Research for AI Coding Agents,https://arxiv.org/abs/2607.05743,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05743,text/html; charset=utf-8,"[2607.05743] The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities","Abstract page for arXiv paper 2607.05743: The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities",,,,,,,,2607.05743,,2026-07-12T10:56:07+00:00 +ale-0274,Context-to-Execution Integrity for LLM Agents,https://arxiv.org/abs/2607.06000,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06000,text/html; charset=utf-8,[2607.06000] Context-to-Execution Integrity for LLM Agents,Abstract page for arXiv paper 2607.06000: Context-to-Execution Integrity for LLM Agents,,,,,,,,2607.06000,,2026-07-12T10:56:07+00:00 +ale-0275,When Agents Remember Too Much: Memory Poisoning Attacks on Large Language Model Agents,https://arxiv.org/abs/2607.06595,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.06595,text/html; charset=utf-8,[2607.06595] When Agents Remember Too Much: Memory Poisoning Attacks on Large Language Model Agents,Abstract page for arXiv paper 2607.06595: When Agents Remember Too Much: Memory Poisoning Attacks on Large Language Model Agents,,,,,,,,2607.06595,,2026-07-12T10:56:07+00:00 +ale-0276,Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents,https://arxiv.org/abs/2607.08395,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08395,text/html; charset=utf-8,[2607.08395] Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents,Abstract page for arXiv paper 2607.08395: Token-Flow Firewall: Semantic Runtime Auditing for Persistent AI Agents,,,,,,,,2607.08395,,2026-07-12T10:56:07+00:00 +ale-0277,Prismata: Confining Cross-Site Prompt Injection in Web Agents,https://arxiv.org/abs/2607.08147,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08147,text/html; charset=utf-8,[2607.08147] Prismata: Confining Cross-Site Prompt Injection in Web Agents,Abstract page for arXiv paper 2607.08147: Prismata: Confining Cross-Site Prompt Injection in Web Agents,,,,,,,,2607.08147,,2026-07-12T10:56:07+00:00 +ale-0278,TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories,https://arxiv.org/abs/2607.08400,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08400,text/html; charset=utf-8,[2607.08400] TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories,Abstract page for arXiv paper 2607.08400: TRACE: A Two-Channel Robust Attribution Watermark via Complementary Embeddings for LLM-Agent Trajectories,,,,,,,,2607.08400,,2026-07-12T10:56:07+00:00 +ale-0279,Beyond Attack-Success Rate: Action-Graded Severity Scale for Tool-Using AI Agents,https://arxiv.org/abs/2607.07474,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07474,text/html; charset=utf-8,[2607.07474] Beyond Attack-Success Rate: Action-Graded Severity Scale for Tool-Using AI Agents,Abstract page for arXiv paper 2607.07474: Beyond Attack-Success Rate: Action-Graded Severity Scale for Tool-Using AI Agents,,,,,,,,2607.07474,,2026-07-12T10:56:07+00:00 +ale-0280,Beware of Agentic Botnets: Scalable Untargeted Promptware Attacks via Universal and Transferable Adversarial HalluSquatting,https://arxiv.org/abs/2607.07433,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07433,text/html; charset=utf-8,[2607.07433] Beware of Agentic Botnets: Scalable Untargeted Promptware Attacks via Universal and Transferable Adversarial HalluSquatting,Abstract page for arXiv paper 2607.07433: Beware of Agentic Botnets: Scalable Untargeted Promptware Attacks via Universal and Transferable Adversarial HalluSquatting,,,,,,,,2607.07433,,2026-07-12T10:56:07+00:00 +ale-0281,GitLost: How We Tricked GitHub's AI Agent into Leaking Private Repos,https://noma.security/blog/gitlost-how-we-tricked-githubs-ai-agent-into-leaking-private-repos/,external,noma.security,ok,200,https://noma.security/blog/gitlost-how-we-tricked-githubs-ai-agent-into-leaking-private-repos/,text/html; charset=UTF-8,GitLost: How We Tricked GitHubā€™s AI Agent into Leaking Private Repos - Noma Security,"TL;DR: Noma Labs discovered a critical prompt injection vulnerability within GitHubā€™s new Agentic Workflows, allowing an unauthenticated attacker to silently pull data from private repositories by posting a crafted GitHub Issue in a public repository belonging to the same organization as the private repositories. Noma Labs named the vulnerability GitLost. Introduction GitHub recently launched [ā€¦]",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0282,ScopeJudge: Cost-Aware Pre-Execution Gating for Offensive Security Agents,https://arxiv.org/abs/2607.07774,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07774,text/html; charset=utf-8,[2607.07774] ScopeJudge: Cost-Aware Pre-Execution Gating for Offensive Security Agents,Abstract page for arXiv paper 2607.07774: ScopeJudge: Cost-Aware Pre-Execution Gating for Offensive Security Agents,,,,,,,,2607.07774,,2026-07-12T10:56:07+00:00 +ale-0283,Multi-Agent AI Control: Distributed Attacks Hamper Per-Instance Monitors,https://arxiv.org/abs/2607.07368,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07368,text/html; charset=utf-8,[2607.07368] Multi-Agent AI Control: Distributed Attacks Hamper Per-Instance Monitors,Abstract page for arXiv paper 2607.07368: Multi-Agent AI Control: Distributed Attacks Hamper Per-Instance Monitors,,,,,,,,2607.07368,,2026-07-12T10:56:07+00:00 +ale-0284,Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptions,https://arxiv.org/abs/2607.07461,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07461,text/html; charset=utf-8,[2607.07461] Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptions,Abstract page for arXiv paper 2607.07461: Mitigating Taint-Style Vulnerabilities in MCP Servers via Security-Aware Tool Descriptions,,,,,,,,2607.07461,,2026-07-12T10:56:07+00:00 +ale-0285,Factory Droid Shield 2.0: Learned Secret Detection for Autonomous Commits,https://factory.ai/news/droid-shield-2-0,external,factory.ai,ok,200,https://factory.ai/news/droid-shield-2-0,text/html; charset=utf-8,Droid Shield 2.0: learned secret detection | Factory.ai Factory.ai Logo Arrow Right Icon,"Droid Shield 2.0: learned secret detection Factory's Droids write, refactor, and commit code autonomously at a volume th...",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0286,Effective Context Engineering for AI Agents,https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents,external,www.anthropic.com,ok,200,https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents,text/html; charset=utf-8,Effective context engineering for AI agents \ Anthropic,"Anthropic is an AI safety and research company that's working to build reliable, interpretable, and steerable AI systems.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0287,Agent Harnesses: the Infrastructure Layer Your LLM Agent Actually Needs,https://ninadpathak.com/blog/agent-harnesses/,external,ninadpathak.com,ok,200,https://ninadpathak.com/blog/agent-harnesses/,text/html; charset=utf-8,Agent Harnesses: the Infrastructure Layer Your Llm Agent Actually Needs | Ninad Pathak,"Every production AI agent needs a harness. Here is what one contains, why frameworks often are not enough, and how to build the layer that actually determines reliability.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0288,The Agent Loop Is the New OS,https://www.harness.io/blog/agent-loop-new-os,external,www.harness.io,ok,200,https://www.harness.io/blog/agent-loop-new-os,text/html; charset=utf-8,The Agent Loop Is the New OS | Harness Blog | Harness Share in X Share in Facebook Share in LinkedIn Search in ChatGpt Github icon LinkedIn icon Facebook icon Instagram icon Twitter icon,"The Harness MCP server treats the AI agent loop as an operating system, mapping the LLM to the CPU and the Context Window to RAM. Learn how this design uses 10 generic, composable tools to abstract complexity and keep the context window clean for higher-quality, cost-efficient AI agent reasoning. | Blog",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0289,Harness engineering for coding agent users,https://martinfowler.com/articles/harness-engineering.html,external,martinfowler.com,ok,200,https://martinfowler.com/articles/harness-engineering.html,text/html,Harness engineering for coding agent users,"A mental model for building trust in coding agents through feedforward guides, feedback sensors, and iterative harness engineering.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0290,Context Engineering,https://simonwillison.net/2025/Jun/27/context-engineering/,external,simonwillison.net,ok,200,https://simonwillison.net/2025/Jun/27/context-engineering/,text/html; charset=utf-8,Context engineering,The term context engineering has recently started to gain traction as a better alternative to prompt engineering. I like it. I think this one may have sticking power. Here's an ā€¦,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0291,Agentic Coding in 2026,https://sourcegraph.com/blog/agentic-coding,external,sourcegraph.com,ok,200,https://sourcegraph.com/blog/agentic-coding,text/html,Agentic Coding in 2026: A Practical Guide for Big Code | Sourcegraph,"Learn what agentic coding is, how AI coding agents work in real engineering orgs, and how to give them the codebase context they need to ship safely.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0292,Agentic AI State Management with ScyllaDB and LangGraph,https://www.scylladb.com/2026/04/08/agentic-ai-state-management-with-scylladb-and-langgraph/,external,www.scylladb.com,ok,200,https://www.scylladb.com/2026/04/08/agentic-ai-state-management-with-scylladb-and-langgraph/,text/html; charset=UTF-8,Agentic AI State Management with ScyllaDB and LangGraph - ScyllaDB,"How to combine LangGraph and ScyllaDB for durable state management, crash recovery, and a highly available backend for your agentic AI applications.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0293,Mem0,https://github.com/mem0ai/mem0,external,github.com,ok,200,https://github.com/mem0ai/mem0,text/html; charset=utf-8,GitHub - mem0ai/mem0: Universal memory layer for AI Agents Ā· GitHub,Universal memory layer for AI Agents. Contribute to mem0ai/mem0 development by creating an account on GitHub.,mem0ai/mem0,60645,7056,549,Universal memory layer for AI Agents,Apache-2.0,2026-07-12T10:58:46Z,,,2026-07-12T10:56:07+00:00 +ale-0294,Letta,https://github.com/letta-ai/letta,external,github.com,ok,200,https://github.com/letta-ai/letta,text/html; charset=utf-8,GitHub - letta-ai/letta: Platform for stateful agents: AI with advanced memory that can learn and self-improve over time. Ā· GitHub,Platform for stateful agents: AI with advanced memory that can learn and self-improve over time. - letta-ai/letta,letta-ai/letta,23747,2515,49,Platform for stateful agents: AI with advanced memory that can learn and self-improve over time.,Apache-2.0,2026-07-12T05:58:56Z,,,2026-07-12T10:56:07+00:00 +ale-0295,Zep,https://github.com/getzep/zep,external,github.com,ok,200,https://github.com/getzep/zep,text/html; charset=utf-8,"GitHub - getzep/zep: Zep | Examples, Integrations, & More Ā· GitHub","Zep | Examples, Integrations, & More. Contribute to getzep/zep development by creating an account on GitHub.",getzep/zep,4742,639,14,"Zep | Examples, Integrations, & More",Apache-2.0,2026-07-11T16:53:07Z,,,2026-07-12T10:56:07+00:00 +ale-0296,LangMem,https://github.com/langchain-ai/langmem,external,github.com,ok,200,https://github.com/langchain-ai/langmem,text/html; charset=utf-8,GitHub - langchain-ai/langmem Ā· GitHub,Contribute to langchain-ai/langmem development by creating an account on GitHub.,langchain-ai/langmem,1549,176,57,,MIT,2026-07-10T07:57:50Z,,,2026-07-12T10:56:07+00:00 +ale-0297,Beads,https://github.com/steveyegge/beads,external,github.com,ok,200,https://github.com/gastownhall/beads,text/html; charset=utf-8,GitHub - gastownhall/beads: Beads - A memory upgrade for your coding agent Ā· GitHub,Beads - A memory upgrade for your coding agent. Contribute to gastownhall/beads development by creating an account on GitHub.,steveyegge/beads,25243,1689,454,Beads - A memory upgrade for your coding agent,MIT,2026-07-12T10:30:56Z,,,2026-07-12T10:56:07+00:00 +ale-0298,ARC: Active and Reflection-driven Context Management for Long-Horizon Agents,https://arxiv.org/abs/2601.12030,external,arxiv.org,ok,200,https://arxiv.org/abs/2601.12030,text/html; charset=utf-8,[2601.12030] ARC: Active and Reflection-driven Context Management for Long-Horizon Information Seeking Agents,Abstract page for arXiv paper 2601.12030: ARC: Active and Reflection-driven Context Management for Long-Horizon Information Seeking Agents,,,,,,,,2601.12030,,2026-07-12T10:56:07+00:00 +ale-0299,"Memory for Autonomous LLM Agents: Mechanisms, Evaluation, and Emerging Frontiers",https://arxiv.org/abs/2603.07670,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.07670,text/html; charset=utf-8,"[2603.07670] Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontiers","Abstract page for arXiv paper 2603.07670: Memory for Autonomous LLM Agents:Mechanisms, Evaluation, and Emerging Frontiers",,,,,,,,2603.07670,,2026-07-12T10:56:07+00:00 +ale-0300,"Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering",https://arxiv.org/abs/2604.08224,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.08224,text/html; charset=utf-8,"[2604.08224] Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering","Abstract page for arXiv paper 2604.08224: Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering",,,,,,,,2604.08224,,2026-07-12T10:56:07+00:00 +ale-0301,Meta Context Engineering via Agentic Skill Evolution,https://arxiv.org/abs/2601.21557,external,arxiv.org,ok,200,https://arxiv.org/abs/2601.21557,text/html; charset=utf-8,[2601.21557] Meta Context Engineering via Agentic Skill Evolution,Abstract page for arXiv paper 2601.21557: Meta Context Engineering via Agentic Skill Evolution,,,,,,,,2601.21557,,2026-07-12T10:56:07+00:00 +ale-0302,Are We Ready for an Agent-Native Memory System?,https://arxiv.org/abs/2606.24775,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.24775,text/html; charset=utf-8,[2606.24775] Are We Ready For An Agent-Native Memory System?,Abstract page for arXiv paper 2606.24775: Are We Ready For An Agent-Native Memory System?,,,,,,,,2606.24775,,2026-07-12T10:56:07+00:00 +ale-0303,Self-Evolving World Models for LLM Agent Planning,https://arxiv.org/abs/2606.30639,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.30639,text/html; charset=utf-8,[2606.30639] Self-Evolving World Models for LLM Agent Planning,Abstract page for arXiv paper 2606.30639: Self-Evolving World Models for LLM Agent Planning,,,,,,,,2606.30639,,2026-07-12T10:56:07+00:00 +ale-0304,Rethinking Continual Experience Internalization for Self-Evolving LLM Agents,https://arxiv.org/abs/2606.04703,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.04703,text/html; charset=utf-8,[2606.04703] Rethinking Continual Experience Internalization for Self-Evolving LLM Agents,Abstract page for arXiv paper 2606.04703: Rethinking Continual Experience Internalization for Self-Evolving LLM Agents,,,,,,,,2606.04703,,2026-07-12T10:56:07+00:00 +ale-0305,GenericAgent,https://github.com/lsdefine/GenericAgent,external,github.com,ok,200,https://github.com/lsdefine/GenericAgent,text/html; charset=utf-8,"GitHub - lsdefine/GenericAgent: Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption Ā· GitHub","Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption - lsdefine/GenericAgent",lsdefine/GenericAgent,13371,1540,170,"Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption",MIT,2026-07-12T10:25:46Z,,,2026-07-12T10:56:07+00:00 +ale-0306,Self-GC: Self-Governing Context for Long-Horizon LLM Agents,https://arxiv.org/abs/2607.00692,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.00692,text/html; charset=utf-8,[2607.00692] Self-GC: Self-Governing Context for Long-Horizon LLM Agents,Abstract page for arXiv paper 2607.00692: Self-GC: Self-Governing Context for Long-Horizon LLM Agents,,,,,,,,2607.00692,,2026-07-12T10:56:07+00:00 +ale-0307,CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents,https://arxiv.org/abs/2607.05378,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05378,text/html; charset=utf-8,[2607.05378] CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents,Abstract page for arXiv paper 2607.05378: CompactionRL: Reinforcement Learning with Context Compaction for Long-Horizon Agents,,,,,,,,2607.05378,,2026-07-12T10:56:07+00:00 +ale-0308,SelfMem: Self-Optimizing Memory for AI Agents,https://arxiv.org/abs/2607.03726,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.03726,text/html; charset=utf-8,[2607.03726] SelfMem: Self-Optimizing Memory for AI Agents,Abstract page for arXiv paper 2607.03726: SelfMem: Self-Optimizing Memory for AI Agents,,,,,,,,2607.03726,,2026-07-12T10:56:07+00:00 +ale-0309,Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture,https://arxiv.org/abs/2607.04391,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.04391,text/html; charset=utf-8,[2607.04391] Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture,Abstract page for arXiv paper 2607.04391: Memory-Orchestrated Semantic System (MOSS): An Auditable Agentic Memory Architecture,,,,,,,,2607.04391,,2026-07-12T10:56:07+00:00 +ale-0310,"The Log Is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems",https://arxiv.org/abs/2605.21997,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.21997,text/html; charset=utf-8,"[2605.21997] The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems","Abstract page for arXiv paper 2605.21997: The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems",,,,,,,,2605.21997,,2026-07-12T10:56:07+00:00 +ale-0311,Agentics: Memorizing Session Transcripts Isn't Useful,https://12gramsofcarbon.com/p/agentics-memorizing-session-transcripts,external,12gramsofcarbon.com,ok,200,https://12gramsofcarbon.com/p/agentics-memorizing-session-transcripts,text/html; charset=utf-8,Agentics: Memorizing Session Transcripts Isn't Useful,"Keep track of artifacts, not scratch. Alt title: Claude, please stop trying to memorize random crap",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0312,Long-Running Agents,https://addyo.substack.com/p/long-running-agents,external,addyo.substack.com,ok,200,https://addyo.substack.com/p/long-running-agents,text/html; charset=utf-8,Long-running Agents - by Addy Osmani - Elevate,"A long-running AI agent can keep making progress over hours, days, or weeks.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0313,StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems,https://arxiv.org/abs/2607.05844,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05844,text/html; charset=utf-8,[2607.05844] StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems,Abstract page for arXiv paper 2607.05844: StateFuse: Deterministic Conflict-Preserving Memory for Multi-Agent Systems,,,,,,,,2607.05844,,2026-07-12T10:56:07+00:00 +ale-0314,Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents,https://arxiv.org/abs/2607.08716,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08716,text/html; charset=utf-8,[2607.08716] Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents,Abstract page for arXiv paper 2607.08716: Remember When It Matters: Proactive Memory Agent for Long-Horizon Agents,,,,,,,,2607.08716,,2026-07-12T10:56:07+00:00 +ale-0315,"What to Keep, What to Forget: A Rate-Distortion View of Memory Compaction",https://arxiv.org/abs/2607.08032,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08032,text/html; charset=utf-8,"[2607.08032] What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents","Abstract page for arXiv paper 2607.08032: What to Keep, What to Forget: A Rate--Distortion View of Memory Compaction in LLMs and Agents",,,,,,,,2607.08032,,2026-07-12T10:56:07+00:00 +ale-0316,A Hierarchical Memory Architecture Overcomes Context Limits in Long-Horizon Multi-Agent Modeling,https://arxiv.org/abs/2607.07666,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07666,text/html; charset=utf-8,[2607.07666] A hierarchical memory architecture overcomes context limits in long-horizon multi-agent computational modeling,Abstract page for arXiv paper 2607.07666: A hierarchical memory architecture overcomes context limits in long-horizon multi-agent computational modeling,,,,,,,,2607.07666,,2026-07-12T10:56:07+00:00 +ale-0317,SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents,https://arxiv.org/abs/2607.07676,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07676,text/html; charset=utf-8,[2607.07676] SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents,Abstract page for arXiv paper 2607.07676: SkillCenter: A Large-Scale Source-Grounded Skill Library for Autonomous AI Agents,,,,,,,,2607.07676,,2026-07-12T10:56:07+00:00 +ale-0318,How version control will evolve for the agent boom,https://entire.io/blog/how-version-control-will-evolve-for-the-agent-boom,external,entire.io,ok,200,https://entire.io/blog/how-version-control-will-evolve-for-the-agent-boom,text/html; charset=utf-8,How Version Control Will Evolve for the Agent Boom Ā· Entire,"To meet the demand of the agent boom, Git hosting must return to its original promise: a distributed network of many hosts.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0319,self-learning-skills,https://github.com/Kulaxyz/self-learning-skills,external,github.com,ok,200,https://github.com/Kulaxyz/self-learning-skills,text/html; charset=utf-8,"GitHub - Kulaxyz/self-learning-skills: A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won golden path in a session and harvest it into a reusable skill/rule for next time. Ā· GitHub","A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won golden path in a session and harvest it into a reusable skill/rule for next time. - Kulaxyz/self-learning-skills",Kulaxyz/self-learning-skills,841,28,2,"A self-improving skill for AI coding agents (Claude Code, Cursor, AGENTS.md): recognize a hard-won golden path in a session and harvest it into a reusable skill/rule for next time.",MIT,2026-07-12T07:53:53Z,,,2026-07-12T10:56:07+00:00 +ale-0320,GitLake: Git-for-data for the agentic lakehouse,https://arxiv.org/abs/2607.08319,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08319,text/html; charset=utf-8,[2607.08319] GitLake: Git-for-data for the agentic lakehouse,Abstract page for arXiv paper 2607.08319: GitLake: Git-for-data for the agentic lakehouse,,,,,,,,2607.08319,,2026-07-12T10:56:07+00:00 +ale-0321,AutoGen,https://github.com/microsoft/autogen,external,github.com,ok,200,https://github.com/microsoft/autogen,text/html; charset=utf-8,GitHub - microsoft/autogen: A programming framework for agentic AI Ā· GitHub,A programming framework for agentic AI. Contribute to microsoft/autogen development by creating an account on GitHub.,microsoft/autogen,59671,8983,945,A programming framework for agentic AI,CC-BY-4.0,2026-07-12T08:59:56Z,,,2026-07-12T10:56:07+00:00 +ale-0322,Microsoft Agent Framework,https://github.com/microsoft/agent-framework,external,github.com,ok,200,https://github.com/microsoft/agent-framework,text/html; charset=utf-8,"GitHub - microsoft/agent-framework: A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET. Ā· GitHub","A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET. - microsoft/agent-framework",microsoft/agent-framework,12056,2025,658,"A framework for building, orchestrating and deploying AI agents and multi-agent workflows with support for Python and .NET.",MIT,2026-07-12T10:04:57Z,,,2026-07-12T10:56:07+00:00 +ale-0323,LangGraph,https://github.com/langchain-ai/langgraph,external,github.com,ok,200,https://github.com/langchain-ai/langgraph,text/html; charset=utf-8,GitHub - langchain-ai/langgraph: Build resilient agents. Ā· GitHub,Build resilient agents. Contribute to langchain-ai/langgraph development by creating an account on GitHub.,langchain-ai/langgraph,37087,6225,616,Build resilient agents.,MIT,2026-07-12T10:29:24Z,,,2026-07-12T10:56:07+00:00 +ale-0324,CrewAI,https://github.com/crewAIInc/crewAI,external,github.com,ok,200,https://github.com/crewAIInc/crewAI,text/html; charset=utf-8,"GitHub - crewAIInc/crewAI: Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. Ā· GitHub","Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. - crewAIInc/crewAI",crewAIInc/crewAI,55378,7809,636,"Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.",MIT,2026-07-12T10:44:42Z,,,2026-07-12T10:56:07+00:00 +ale-0325,LlamaIndex Workflows,https://developers.llamaindex.ai/python/llamaagents/workflows/,external,developers.llamaindex.ai,ok,200,https://developers.llamaindex.ai/python/llamaagents/workflows/,text/html; charset=utf-8,Introduction | Developer Documentation,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0326,OpenAI Agents SDK handoffs,https://openai.github.io/openai-agents-python/handoffs/,external,openai.github.io,ok,200,https://openai.github.io/openai-agents-python/handoffs/,text/html; charset=utf-8,Handoffs - OpenAI Agents SDK,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0327,Agent Protocol,https://agentprotocol.ai/,external,agentprotocol.ai,ok,200,https://agentprotocol.ai/,text/html; charset=utf-8,AgentProtocol.ai ā€” A practical guide to AI agent communication standards.,"AgentProtocol.ai is an independent, vendor-neutral guide to AI agent communication standards ā€” MCP, A2A, Agent Protocol, AI agent APIs and agent interoperability.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0328,AgentKit,https://github.com/inngest/agent-kit,external,github.com,ok,200,https://github.com/inngest/agent-kit,text/html; charset=utf-8,GitHub - inngest/agent-kit: AgentKit: Build multi-agent networks in TypeScript with deterministic routing and rich tooling via MCP. Ā· GitHub,AgentKit: Build multi-agent networks in TypeScript with deterministic routing and rich tooling via MCP. - inngest/agent-kit,inngest/agent-kit,911,135,45,AgentKit: Build multi-agent networks in TypeScript with deterministic routing and rich tooling via MCP.,Apache-2.0,2026-07-12T08:55:01Z,,,2026-07-12T10:56:07+00:00 +ale-0329,deepagents,https://github.com/langchain-ai/deepagents,external,github.com,ok,200,https://github.com/langchain-ai/deepagents,text/html; charset=utf-8,GitHub - langchain-ai/deepagents: The batteries-included agent harness. Ā· GitHub,The batteries-included agent harness. Contribute to langchain-ai/deepagents development by creating an account on GitHub.,langchain-ai/deepagents,26120,3653,195,The batteries-included agent harness.,MIT,2026-07-12T10:39:31Z,,,2026-07-12T10:56:07+00:00 +ale-0330,Temporal for AI,https://temporal.io/solutions/ai,external,temporal.io,ok,200,https://temporal.io/solutions/ai,text/html; charset=utf-8,Temporal for AI | Temporal,"Temporal is a durable workflow platform that ensures AI applications run reliably, every time. Build faster, prevent failures, and stand out from the crowd.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0331,Restate,https://restate.dev/,external,restate.dev,ok,200,https://www.restate.dev/,text/html; charset=utf-8,Restate - Build innately resilient distributed apps,Restate is a lightweight runtime that lets developers build innately resilient distributed apps without the complexity tax.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0332,DBOS,https://www.dbos.dev/,external,www.dbos.dev,ok,200,https://www.dbos.dev/,text/html; charset=utf-8,DBOS | Durable Workflow Orchestration,"DBOS is an open source durable execution and workflow orchestration system that radically simplifies the development and operation of reliable, observable workflows.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0333,Composio Agent Orchestrator,https://github.com/ComposioHQ/agent-orchestrator,external,github.com,ok,200,https://github.com/AgentWrapper/agent-orchestrator,text/html; charset=utf-8,"GitHub - AgentWrapper/agent-orchestrator: Agentic orchestrator for parallel coding agents ā€” plans tasks, spawns agents, and autonomously handles CI fixes, merge conflicts, and code reviews. Ā· GitHub","Agentic orchestrator for parallel coding agents ā€” plans tasks, spawns agents, and autonomously handles CI fixes, merge conflicts, and code reviews. - AgentWrapper/agent-orchestrator",ComposioHQ/agent-orchestrator,8201,1169,446,"Agentic orchestrator for parallel coding agents ā€” plans tasks, spawns agents, and autonomously handles CI fixes, merge conflicts, and code reviews.",Apache-2.0,2026-07-12T10:36:51Z,,,2026-07-12T10:56:07+00:00 +ale-0334,Omnigent,https://github.com/omnigent-ai/omnigent,external,github.com,ok,200,https://github.com/omnigent-ai/omnigent,text/html; charset=utf-8,"GitHub - omnigent-ai/omnigent: Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents ā€” swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device. Ā· GitHub","Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents ā€” swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device. - omnigent-ai/omnigent",omnigent-ai/omnigent,7110,969,566,"Omnigent is an open-source AI agent framework and meta-harness: orchestrate Claude Code, Codex, Cursor, Pi, and custom agents ā€” swap harnesses without rewriting, enforce policies and sandboxing, and collaborate in real time from any device.",Apache-2.0,2026-07-12T10:51:58Z,,,2026-07-12T10:56:07+00:00 +ale-0335,From Agent Loops to Structured Graphs: A Scheduler-Theoretic Framework for LLM Agent Execution,https://arxiv.org/abs/2604.11378,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.11378,text/html; charset=utf-8,[2604.11378] From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution,Abstract page for arXiv paper 2604.11378: From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution,,,,,,,,2604.11378,,2026-07-12T10:56:07+00:00 +ale-0336,Eve,https://github.com/vercel/eve,external,github.com,ok,200,https://github.com/vercel/eve,text/html; charset=utf-8,GitHub - vercel/eve: The Framework for Building Agents Ā· GitHub,The Framework for Building Agents. Contribute to vercel/eve development by creating an account on GitHub.,vercel/eve,3439,292,248,The Framework for Building Agents,Apache-2.0,2026-07-12T08:12:00Z,,,2026-07-12T10:56:07+00:00 +ale-0337,Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework,https://arxiv.org/abs/2603.11445,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.11445,text/html; charset=utf-8,[2603.11445] Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution,Abstract page for arXiv paper 2603.11445: Verified Multi-Agent Orchestration: A Plan-Execute-Verify-Replan Framework for Complex Query Resolution,,,,,,,,2603.11445,,2026-07-12T10:56:07+00:00 +ale-0338,From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents,https://arxiv.org/abs/2603.22386,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.22386,text/html; charset=utf-8,[2603.22386] From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents,Abstract page for arXiv paper 2603.22386: From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents,,,,,,,,2603.22386,,2026-07-12T10:56:07+00:00 +ale-0339,Agent-as-a-Router,https://github.com/LanceZPF/agent-as-a-router,external,github.com,ok,200,https://github.com/LanceZPF/agent-as-a-router,text/html; charset=utf-8,GitHub - LanceZPF/agent-as-a-router: The official implementations of Agent-as-a-Router: Agentic Model Routing for Coding Tasks. Ā· GitHub,The official implementations of Agent-as-a-Router: Agentic Model Routing for Coding Tasks. - LanceZPF/agent-as-a-router,LanceZPF/agent-as-a-router,440,14,0,The official implementations of Agent-as-a-Router: Agentic Model Routing for Coding Tasks.,MIT,2026-07-12T10:31:31Z,,,2026-07-12T10:56:07+00:00 +ale-0340,Amp: Custom Agents,https://ampcode.com/news/custom-agents,external,ampcode.com,ok,200,https://ampcode.com/news/custom-agents,text/html,Amp,"Plugins can now create agents, run them once, and keep talking to their threads.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0341,AgentsMesh,https://github.com/AgentsMesh/AgentsMesh,external,github.com,ok,200,https://github.com/AgentsMesh/AgentsMesh,text/html; charset=utf-8,"GitHub - AgentsMesh/AgentsMesh: The AI Agent Workforce Platform. Run a hundred AI coding agents across your own machines ā€” schedule, isolate, and steer them all from one console. Ā· GitHub","The AI Agent Workforce Platform. Run a hundred AI coding agents across your own machines ā€” schedule, isolate, and steer them all from one console. - AgentsMesh/AgentsMesh",AgentsMesh/AgentsMesh,2271,229,18,"The AI Agent Workforce Platform. Run a hundred AI coding agents across your own machines ā€” schedule, isolate, and steer them all from one console.",NOASSERTION,2026-07-11T21:46:24Z,,,2026-07-12T10:56:07+00:00 +ale-0342,Bernstein,https://github.com/sipyourdrink-ltd/bernstein,external,github.com,ok,200,https://github.com/sipyourdrink-ltd/bernstein,text/html; charset=utf-8,"GitHub - sipyourdrink-ltd/bernstein: Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run Ā· GitHub","Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run - sipyourdrink-ltd/bernstein",sipyourdrink-ltd/bernstein,661,61,8,"Audit-grade multi-agent orchestration for CLI coding agents (Claude Code, Codex, Gemini CLI, +40 more). HMAC-chained audit log, signed agent cards, per-artefact lineage, air-gap deploy. The orchestrator your compliance team will sign off on. https://bernstein.run",Apache-2.0,2026-07-12T09:58:20Z,,,2026-07-12T10:56:07+00:00 +ale-0343,Aeon,https://github.com/aaronjmars/aeon,external,github.com,ok,200,https://github.com/aaronjmars/aeon,text/html; charset=utf-8,"GitHub - aaronjmars/aeon: The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever. Ā· GitHub","The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever. - aaronjmars/aeon",aaronjmars/aeon,573,209,0,"The most autonomous agent framework. No approval loops. No babysitting. Configure once, forget forever.",MIT,2026-07-11T23:01:16Z,,,2026-07-12T10:56:07+00:00 +ale-0344,h5i,https://github.com/h5i-dev/h5i,external,github.com,ok,200,https://github.com/h5i-dev/h5i,text/html; charset=utf-8,"GitHub - h5i-dev/h5i: Auditable workspaces for AI coding agents: sandboxed worktrees, conflict-free multi-agent orchestra, 95% lower token waste, and persistent memory. Ā· GitHub","Auditable workspaces for AI coding agents: sandboxed worktrees, conflict-free multi-agent orchestra, 95% lower token waste, and persistent memory. - h5i-dev/h5i",h5i-dev/h5i,464,35,26,"Auditable workspaces for AI coding agents: sandboxed worktrees, conflict-free multi-agent orchestra, 95% lower token waste, and persistent memory.",Apache-2.0,2026-07-12T03:03:21Z,,,2026-07-12T10:56:07+00:00 +ale-0345,SwarmResearch: Orchestrating Coding Agents for Open-Ended Discovery,https://arxiv.org/abs/2607.02807,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.02807,text/html; charset=utf-8,[2607.02807] SwarmResearch: Orchestrating Coding Agents for Open-Ended Discovery,Abstract page for arXiv paper 2607.02807: SwarmResearch: Orchestrating Coding Agents for Open-Ended Discovery,,,,,,,,2607.02807,,2026-07-12T10:56:07+00:00 +ale-0346,Scaling Long-Running Autonomous Coding,https://cursor.com/blog/scaling-agents,external,cursor.com,ok,200,https://cursor.com/blog/scaling-agents,text/html; charset=utf-8,Scaling long-running autonomous coding Ā· Cursor,We've been experimenting with running coding agents autonomously for weeks at a time.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0347,babysitter,https://github.com/a5c-ai/babysitter,external,github.com,ok,200,https://github.com/a5c-ai/babysitter,text/html; charset=utf-8,"GitHub - a5c-ai/babysitter: Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration Ā· GitHub","Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration - a5c-ai/babysitter",a5c-ai/babysitter,1529,88,86,"Babysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestration",MIT,2026-07-12T08:32:21Z,,,2026-07-12T10:56:07+00:00 +ale-0348,claude-code-merge-queue,https://github.com/funador/claude-code-merge-queue,external,github.com,ok,200,https://github.com/funador/claude-code-merge-queue,text/html; charset=utf-8,"GitHub - funador/claude-code-merge-queue: The local, zero-cost merge queue for parallel Claude Code agents Ā· GitHub","The local, zero-cost merge queue for parallel Claude Code agents - funador/claude-code-merge-queue",funador/claude-code-merge-queue,5,0,0,"The local, zero-cost merge queue for parallel Claude Code agents",MIT,2026-07-12T01:23:15Z,,,2026-07-12T10:56:07+00:00 +ale-0349,Devin can now manage Devins,https://cognition.com/blog/devin-can-now-manage-devins,external,cognition.com,ok,200,https://cognition.com/blog/devin-can-now-manage-devins,text/html; charset=utf-8,Devin can now Manage Devins | Cognition,"Devin can now break down large tasks and delegate them to a team of managed Devins, with each running in its own isolated VM in parallel.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0350,pilotfish,https://github.com/Nanako0129/pilotfish,external,github.com,ok,200,https://github.com/Nanako0129/pilotfish,text/html; charset=utf-8,"GitHub - Nanako0129/pilotfish: Multi-model orchestration layer for Claude Code ā€” the frontier model plans, cheaper models execute, verification guards quality. One-prompt install. Ā· GitHub","Multi-model orchestration layer for Claude Code ā€” the frontier model plans, cheaper models execute, verification guards quality. One-prompt install. - Nanako0129/pilotfish",Nanako0129/pilotfish,370,27,0,"Multi-model orchestration layer for Claude Code ā€” the frontier model plans, cheaper models execute, verification guards quality. One-prompt install.",MIT,2026-07-12T08:48:06Z,,,2026-07-12T10:56:07+00:00 +ale-0351,fable-advisor,https://github.com/DannyMac180/fable-advisor,external,github.com,ok,200,https://github.com/DannyMac180/fable-advisor,text/html; charset=utf-8,"GitHub - DannyMac180/fable-advisor: Claude Fable as an orchestrator for Opus, GPT and Grok Ā· GitHub","Claude Fable as an orchestrator for Opus, GPT and Grok - DannyMac180/fable-advisor",DannyMac180/fable-advisor,455,34,4,"Claude Fable as an orchestrator for Opus, GPT and Grok",MIT,2026-07-12T10:49:02Z,,,2026-07-12T10:56:07+00:00 +ale-0352,agent-chief,https://github.com/SmileLikeYe/agent-chief,external,github.com,ok,200,https://github.com/SmileLikeYe/agent-chief,text/html; charset=utf-8,"GitHub - SmileLikeYe/agent-chief: Attention is your scarcest resource. Chief is the local-first layer that guards it ā€” turning every agent, alert, and feed into one honest call: interrupt, or not. Ā· GitHub","Attention is your scarcest resource. Chief is the local-first layer that guards it ā€” turning every agent, alert, and feed into one honest call: interrupt, or not. - SmileLikeYe/agent-chief",SmileLikeYe/agent-chief,479,3,0,"Attention is your scarcest resource. Chief is the local-first layer that guards it ā€” turning every agent, alert, and feed into one honest call: interrupt, or not.",MIT,2026-07-12T10:59:00Z,,,2026-07-12T10:56:07+00:00 +ale-0353,OpenTag,https://github.com/amplifthq/opentag,external,github.com,ok,200,https://github.com/amplifthq/opentag,text/html; charset=utf-8,"GitHub - amplifthq/opentag: Open-source @agent mentions for Slack and GitHub. OpenTag routes tagged requests to Codex, Claude Code, then returns results in thread. Ā· GitHub","Open-source @agent mentions for Slack and GitHub. OpenTag routes tagged requests to Codex, Claude Code, then returns results in thread. - amplifthq/opentag",amplifthq/opentag,1146,66,5,"Open-source @agent mentions for Slack and GitHub. OpenTag routes tagged requests to Codex, Claude Code, then returns results in thread.",MIT,2026-07-12T10:48:48Z,,,2026-07-12T10:56:07+00:00 +ale-0354,SWE-bench,https://www.swebench.com/,external,www.swebench.com,ok,200,https://www.swebench.com/,text/html; charset=utf-8,SWE-bench Leaderboards,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0355,SWE-bench: Can Language Models Resolve Real-World GitHub Issues?,https://arxiv.org/abs/2310.06770,external,arxiv.org,ok,200,https://arxiv.org/abs/2310.06770,text/html; charset=utf-8,[2310.06770] SWE-bench: Can Language Models Resolve Real-World GitHub Issues?,Abstract page for arXiv paper 2310.06770: SWE-bench: Can Language Models Resolve Real-World GitHub Issues?,,,,,,,,2310.06770,,2026-07-12T10:56:07+00:00 +ale-0356,SWE-bench Goes Live,https://arxiv.org/abs/2505.23419,external,arxiv.org,ok,200,https://arxiv.org/abs/2505.23419,text/html; charset=utf-8,[2505.23419] SWE-bench Goes Live!,Abstract page for arXiv paper 2505.23419: SWE-bench Goes Live!,,,,,,,,2505.23419,,2026-07-12T10:56:07+00:00 +ale-0357,Terminal-Bench,https://www.tbench.ai/,external,www.tbench.ai,ok,200,https://www.tbench.ai/,text/html; charset=utf-8,Terminal-Bench,A benchmark for terminal agents,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0358,Terminal-Bench repository,https://github.com/harbor-framework/terminal-bench,external,github.com,ok,200,https://github.com/harbor-framework/terminal-bench,text/html; charset=utf-8,GitHub - harbor-framework/terminal-bench: A benchmark for LLMs on complicated tasks in the terminal Ā· GitHub,A benchmark for LLMs on complicated tasks in the terminal - harbor-framework/terminal-bench,harbor-framework/terminal-bench,2437,554,317,A benchmark for LLMs on complicated tasks in the terminal,Apache-2.0,2026-07-11T10:21:38Z,,,2026-07-12T10:56:07+00:00 +ale-0359,AgentBench,https://arxiv.org/abs/2308.03688,external,arxiv.org,ok,200,https://arxiv.org/abs/2308.03688,text/html; charset=utf-8,[2308.03688] AgentBench: Evaluating LLMs as Agents,Abstract page for arXiv paper 2308.03688: AgentBench: Evaluating LLMs as Agents,,,,,,,,2308.03688,,2026-07-12T10:56:07+00:00 +ale-0360,WebArena,https://arxiv.org/abs/2307.13854,external,arxiv.org,ok,200,https://arxiv.org/abs/2307.13854,text/html; charset=utf-8,[2307.13854] WebArena: A Realistic Web Environment for Building Autonomous Agents,Abstract page for arXiv paper 2307.13854: WebArena: A Realistic Web Environment for Building Autonomous Agents,,,,,,,,2307.13854,,2026-07-12T10:56:07+00:00 +ale-0361,OSWorld,https://arxiv.org/abs/2404.07972,external,arxiv.org,ok,200,https://arxiv.org/abs/2404.07972,text/html; charset=utf-8,[2404.07972] OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments,Abstract page for arXiv paper 2404.07972: OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments,,,,,,,,2404.07972,,2026-07-12T10:56:07+00:00 +ale-0362,ToolBench,https://arxiv.org/abs/2307.16789,external,arxiv.org,ok,200,https://arxiv.org/abs/2307.16789,text/html; charset=utf-8,[2307.16789] ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs,Abstract page for arXiv paper 2307.16789: ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs,,,,,,,,2307.16789,,2026-07-12T10:56:07+00:00 +ale-0363,GAIA,https://arxiv.org/abs/2311.12983,external,arxiv.org,ok,200,https://arxiv.org/abs/2311.12983,text/html; charset=utf-8,[2311.12983] GAIA: a benchmark for General AI Assistants,Abstract page for arXiv paper 2311.12983: GAIA: a benchmark for General AI Assistants,,,,,,,,2311.12983,,2026-07-12T10:56:07+00:00 +ale-0364,Tau-bench,https://arxiv.org/abs/2406.12045,external,arxiv.org,ok,200,https://arxiv.org/abs/2406.12045,text/html; charset=utf-8,[2406.12045] $Ļ„$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains,Abstract page for arXiv paper 2406.12045: $Ļ„$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains,,,,,,,,2406.12045,,2026-07-12T10:56:07+00:00 +ale-0365,VisualWebArena,https://arxiv.org/abs/2401.13649,external,arxiv.org,ok,200,https://arxiv.org/abs/2401.13649,text/html; charset=utf-8,[2401.13649] VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks,Abstract page for arXiv paper 2401.13649: VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks,,,,,,,,2401.13649,,2026-07-12T10:56:07+00:00 +ale-0366,AppWorld,https://arxiv.org/abs/2407.18901,external,arxiv.org,ok,200,https://arxiv.org/abs/2407.18901,text/html; charset=utf-8,[2407.18901] AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents,Abstract page for arXiv paper 2407.18901: AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents,,,,,,,,2407.18901,,2026-07-12T10:56:07+00:00 +ale-0367,Vending-Bench,https://arxiv.org/abs/2502.15840,external,arxiv.org,ok,200,https://arxiv.org/abs/2502.15840,text/html; charset=utf-8,[2502.15840] Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents,Abstract page for arXiv paper 2502.15840: Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents,,,,,,,,2502.15840,,2026-07-12T10:56:07+00:00 +ale-0368,Vending-Bench leaderboard,https://andonlabs.com/evals/vending-bench,external,andonlabs.com,ok,200,https://andonlabs.com/evals/vending-bench,text/html; charset=UTF-8,Vending-Bench: Testing long-term coherence in agents | Andon Labs,"How do agents act over very long horizons? We answer this by letting agents manage a simulated vending machine business. The agents need to handle ordering, inventory management, and pricing over long context horizons to successfully make money.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0369,SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios,https://arxiv.org/abs/2512.18470,external,arxiv.org,ok,200,https://arxiv.org/abs/2512.18470,text/html; charset=utf-8,[2512.18470] SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios,Abstract page for arXiv paper 2512.18470: SWE-EVO: Benchmarking Coding Agents in Long-Horizon Software Evolution Scenarios,,,,,,,,2512.18470,,2026-07-12T10:56:07+00:00 +ale-0370,EvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification,https://arxiv.org/abs/2604.01687,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.01687,text/html; charset=utf-8,[2604.01687] CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification,Abstract page for arXiv paper 2604.01687: CoEvoSkills: Self-Evolving Agent Skills via Co-Evolutionary Verification,,,,,,,,2604.01687,,2026-07-12T10:56:07+00:00 +ale-0371,SaaSBench: Coding Agents in Long-Horizon Enterprise SaaS Engineering,https://arxiv.org/abs/2605.17526,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.17526,text/html; charset=utf-8,[2605.17526] SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering,Abstract page for arXiv paper 2605.17526: SaaSBench: Exploring the Boundaries of Coding Agents in Long-Horizon Enterprise SaaS Engineering,,,,,,,,2605.17526,,2026-07-12T10:56:07+00:00 +ale-0372,RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades,https://arxiv.org/abs/2605.15846,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.15846,text/html; charset=utf-8,[2605.15846] RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades,Abstract page for arXiv paper 2605.15846: RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades,,,,,,,,2605.15846,,2026-07-12T10:56:07+00:00 +ale-0373,RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code,https://arxiv.org/abs/2503.07832,external,arxiv.org,ok,200,https://arxiv.org/abs/2503.07832,text/html; charset=utf-8,[2503.07832] RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code,Abstract page for arXiv paper 2503.07832: RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code,,,,,,,,2503.07832,,2026-07-12T10:56:07+00:00 +ale-0374,RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents,https://arxiv.org/abs/2606.22678,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.22678,text/html; charset=utf-8,[2606.22678] RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents,Abstract page for arXiv paper 2606.22678: RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents,,,,,,,,2606.22678,,2026-07-12T10:56:07+00:00 +ale-0375,SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks,https://arxiv.org/abs/2603.24755,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.24755,text/html; charset=utf-8,[2603.24755] SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks,Abstract page for arXiv paper 2603.24755: SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks,,,,,,,,2603.24755,,2026-07-12T10:56:07+00:00 +ale-0376,LongCLI-Bench: A Preliminary Benchmark for Long-horizon Agentic Programming in Command-Line Interfaces,https://arxiv.org/abs/2602.14337,external,arxiv.org,ok,200,https://arxiv.org/abs/2602.14337,text/html; charset=utf-8,[2602.14337] LongCLI-Bench: A Preliminary Benchmark and Study for Long-horizon Agentic Programming in Command-Line Interfaces,Abstract page for arXiv paper 2602.14337: LongCLI-Bench: A Preliminary Benchmark and Study for Long-horizon Agentic Programming in Command-Line Interfaces,,,,,,,,2602.14337,,2026-07-12T10:56:07+00:00 +ale-0377,Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?,https://arxiv.org/abs/2606.29920,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.29920,text/html; charset=utf-8,[2606.29920] Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?,Abstract page for arXiv paper 2606.29920: Can LLM-as-a-Judge Reliably Verify Rubrics in Agentic Scenarios?,,,,,,,,2606.29920,,2026-07-12T10:56:07+00:00 +ale-0378,SentinelBench: A Benchmark for Long-Running Monitoring Agents,https://arxiv.org/abs/2606.05342,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.05342,text/html; charset=utf-8,[2606.05342] SentinelBench: A Benchmark for Long-Running Monitoring Agents,Abstract page for arXiv paper 2606.05342: SentinelBench: A Benchmark for Long-Running Monitoring Agents,,,,,,,,2606.05342,,2026-07-12T10:56:07+00:00 +ale-0379,SWE-Together: Evaluating Coding Agents in Interactive User Sessions,https://arxiv.org/abs/2606.29957,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.29957,text/html; charset=utf-8,[2606.29957] SWE-Together: Evaluating Coding Agents in Interactive User Sessions,Abstract page for arXiv paper 2606.29957: SWE-Together: Evaluating Coding Agents in Interactive User Sessions,,,,,,,,2606.29957,,2026-07-12T10:56:07+00:00 +ale-0380,The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break,https://arxiv.org/abs/2604.11978,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.11978,text/html; charset=utf-8,[2604.11978] The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break,Abstract page for arXiv paper 2604.11978: The Long-Horizon Task Mirage? Diagnosing Where and Why Agentic Systems Break,,,,,,,,2604.11978,,2026-07-12T10:56:07+00:00 +ale-0381,Beyond pass@1: A Reliability Science Framework for Long-Horizon LLM Agents,https://arxiv.org/abs/2603.29231,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.29231,text/html; charset=utf-8,[2603.29231] Beyond pass@1: A Reliability Science Framework for Long-Horizon LLM Agents,Abstract page for arXiv paper 2603.29231: Beyond pass@1: A Reliability Science Framework for Long-Horizon LLM Agents,,,,,,,,2603.29231,,2026-07-12T10:56:07+00:00 +ale-0382,SEAGym: An Evaluation Environment for Self-Evolving LLM Agents,https://arxiv.org/abs/2606.17546,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.17546,text/html; charset=utf-8,[2606.17546] SEAGym: An Evaluation Environment for Self-Evolving LLM Agents,Abstract page for arXiv paper 2606.17546: SEAGym: An Evaluation Environment for Self-Evolving LLM Agents,,,,,,,,2606.17546,,2026-07-12T10:56:07+00:00 +ale-0383,EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions,https://arxiv.org/abs/2605.24110,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.24110,text/html; charset=utf-8,[2605.24110] EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions,Abstract page for arXiv paper 2605.24110: EvoCode-Bench: Evaluating Coding Agents in Multi-Turn Iterative Interactions,,,,,,,,2605.24110,,2026-07-12T10:56:07+00:00 +ale-0384,On the Reliability of Computer Use Agents,https://arxiv.org/abs/2604.17849,external,arxiv.org,ok,200,https://arxiv.org/abs/2604.17849,text/html; charset=utf-8,[2604.17849] On the Reliability of Computer Use Agents,Abstract page for arXiv paper 2604.17849: On the Reliability of Computer Use Agents,,,,,,,,2604.17849,,2026-07-12T10:56:07+00:00 +ale-0385,AgentLens: Revealing the Lucky Pass Problem in SWE-Agent Evaluation,https://arxiv.org/abs/2605.12925,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.12925,text/html; charset=utf-8,[2605.12925] AgentLens: Revealing The Lucky Pass Problem in SWE-Agent Evaluation,Abstract page for arXiv paper 2605.12925: AgentLens: Revealing The Lucky Pass Problem in SWE-Agent Evaluation,,,,,,,,2605.12925,,2026-07-12T10:56:07+00:00 +ale-0386,ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction,https://arxiv.org/abs/2601.21008,external,arxiv.org,ok,200,https://arxiv.org/abs/2601.21008,text/html; charset=utf-8,[2601.21008] ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction and Behavioral Rationality in Operations Research,Abstract page for arXiv paper 2601.21008: ORLoopBench: Solver-in-the-Loop Benchmarks for Self-Correction and Behavioral Rationality in Operations Research,,,,,,,,2601.21008,,2026-07-12T10:56:07+00:00 +ale-0387,LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis,https://arxiv.org/abs/2605.30434,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.30434,text/html; charset=utf-8,[2605.30434] LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis,Abstract page for arXiv paper 2605.30434: LongDS-Bench: On the Failure of Long-Horizon Agentic Data Analysis,,,,,,,,2605.30434,,2026-07-12T10:56:07+00:00 +ale-0388,MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks,https://arxiv.org/abs/2602.16313,external,arxiv.org,ok,200,https://arxiv.org/abs/2602.16313,text/html; charset=utf-8,[2602.16313] MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks,Abstract page for arXiv paper 2602.16313: MemoryArena: Benchmarking Agent Memory in Interdependent Multi-Session Agentic Tasks,,,,,,,,2602.16313,,2026-07-12T10:56:07+00:00 +ale-0389,Momento: Evaluating Persistent Memory and Reasoning with Multi-Session Agentic Conversations,https://arxiv.org/abs/2606.00832,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.00832,text/html; charset=utf-8,[2606.00832] Momento: Evaluating Persistent Memory and Reasoning with Multi-Session Agentic Conversations,Abstract page for arXiv paper 2606.00832: Momento: Evaluating Persistent Memory and Reasoning with Multi-Session Agentic Conversations,,,,,,,,2606.00832,,2026-07-12T10:56:07+00:00 +ale-0390,Ļ€-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows,https://arxiv.org/abs/2605.14678,external,arxiv.org,ok,200,https://arxiv.org/abs/2605.14678,text/html; charset=utf-8,[2605.14678] $Ļ€$-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows,Abstract page for arXiv paper 2605.14678: $Ļ€$-Bench: Evaluating Proactive Personal Assistant Agents in Long-Horizon Workflows,,,,,,,,2605.14678,,2026-07-12T10:56:07+00:00 +ale-0391,Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation,https://arxiv.org/abs/2603.23638,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.23638,text/html; charset=utf-8,[2603.23638] Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment,Abstract page for arXiv paper 2603.23638: Can LLM Agents Be CFOs? Benchmarking Long-Horizon Resource Allocation in an Uncertain Enterprise Environment,,,,,,,,2603.23638,,2026-07-12T10:56:07+00:00 +ale-0392,EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer,https://arxiv.org/abs/2607.05202,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05202,text/html; charset=utf-8,[2607.05202] EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer,Abstract page for arXiv paper 2607.05202: EvoAgentBench: Benchmarking Agent Self-Evolution via Ability Transfer,,,,,,,,2607.05202,,2026-07-12T10:56:07+00:00 +ale-0393,AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents,https://arxiv.org/abs/2607.02255,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.02255,text/html; charset=utf-8,[2607.02255] AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents,Abstract page for arXiv paper 2607.02255: AgenticSTS: A Bounded-Memory Testbed for Long-Horizon LLM Agents,,,,,,,,2607.02255,,2026-07-12T10:56:07+00:00 +ale-0394,Is Three the Magic Number? An Empirical Evaluation of LLM-Based Repair Loops,https://arxiv.org/abs/2607.05197,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.05197,text/html; charset=utf-8,[2607.05197] Is Three the Magic Number? An Empirical Evaluation of LLM-Based Repair Loops,Abstract page for arXiv paper 2607.05197: Is Three the Magic Number? An Empirical Evaluation of LLM-Based Repair Loops,,,,,,,,2607.05197,,2026-07-12T10:56:07+00:00 +ale-0395,"DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks",https://arxiv.org/abs/2607.07946,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07946,text/html; charset=utf-8,"[2607.07946] DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks","Abstract page for arXiv paper 2607.07946: DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks",,,,,,,,2607.07946,,2026-07-12T10:56:07+00:00 +ale-0396,PERFOPT-Bench: Evaluating Coding Agents on Software Performance Optimization,https://arxiv.org/abs/2607.07744,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07744,text/html; charset=utf-8,[2607.07744] PERFOPT-Bench: Evaluating Coding Agents on Software Performance Optimization,Abstract page for arXiv paper 2607.07744: PERFOPT-Bench: Evaluating Coding Agents on Software Performance Optimization,,,,,,,,2607.07744,,2026-07-12T10:56:07+00:00 +ale-0397,Benchmarking coding agents on Databricks' multi-million line codebase,https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase,external,www.databricks.com,ok,200,https://www.databricks.com/blog/benchmarking-coding-agents-databricks-multi-million-line-codebase,text/html; charset=utf-8,Benchmarking Coding Agents on Databricksā€™ Multi-Million Line Codebase | Databricks Blog,"Databricks shares results from its internal coding benchmark, evaluating coding agents on a multi-million line codebase to optimize engineering cost and performance.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0398,UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks,https://arxiv.org/abs/2607.08768,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08768,text/html; charset=utf-8,[2607.08768] UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks,Abstract page for arXiv paper 2607.08768: UniClawBench: A Universal Benchmark for Proactive Agents on Real-World Tasks,,,,,,,,2607.08768,,2026-07-12T10:56:07+00:00 +ale-0399,Agentic Engineering: The Agent Loop,https://junpingyi.com/books/agentic-engineering/agent-loop/,external,junpingyi.com,ok,200,https://junpingyi.com/books/agentic-engineering/agent-loop/,text/html,Chapter 1: The Agent Loop ā€” Agentic Engineering: How to Build AI Agents Like Claude Code,Chapter 1: The Agent Loop from Agentic Engineering: How to Build AI Agents Like Claude Code,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0400,"The agent loop: ReAct, plan-and-execute, reflection",https://www.kunwar.page/chapter/067-the-agent-loop-react-plan-and-execute-reflection,external,www.kunwar.page,ok,200,https://www.kunwar.page/chapter/067-the-agent-loop-react-plan-and-execute-reflection,text/html; charset=utf-8,"Chapter 67: The agent loop: ReAct, plan-and-execute, reflection ā€” The Holy Grail Basic agent loop: generate, check for tool calls, execute tools and loop back, or return final answer on no tool call. ReAct interleaves Thought, Action, and Observation triplets; each Thought improves the next Action choice by externalizing reasoning. Agent cost vs single-shot: one LLM call versus 5-12 interleaved LLM and tool calls, showing the 10x cost and latency multiplier.",An agent is a loop of `model.generate()` calls with tool calls in between. The loop is the entire pattern,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0401,How to Build an Agent,https://ampcode.com/how-to-build-an-agent,external,ampcode.com,ok,200,https://ampcode.com/notes/how-to-build-an-agent,text/html,Amp,"Building a fully functional, code-editing agent in less than 400 lines.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0402,Agentic Coding Recommendations,https://lucumr.pocoo.org/2025/6/12/agentic-coding/,external,lucumr.pocoo.org,ok,200,https://lucumr.pocoo.org/2025/6/12/agentic-coding/,text/html; charset=utf-8,Agentic Coding Recommendations | Armin Ronacher's Thoughts and Writings,Current recommendations of agentic coding.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0403,Coding Agents 101: The Art of Actually Getting Things Done,https://devin.ai/agents101,external,devin.ai,ok,200,https://devin.ai/agents101,text/html; charset=utf-8,Coding Agents 101: The Art of Actually Getting Things Done,Coding Agents 101: The Art of Actually Getting Things Done,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0404,How Anthropic teams use Claude Code,https://claude.com/blog/how-anthropic-teams-use-claude-code,external,claude.com,ok,200,https://claude.com/blog/how-anthropic-teams-use-claude-code,text/html; charset=utf-8,How Anthropic teams use Claude Code | Claude by Anthropic,Teams across Anthropic use Claude Code for everything from debugging production issues and navigating unfamiliar codebases to building custom automation tools. Here's how. ā€,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0405,How Boris Uses Claude Code,https://howborisusesclaudecode.com/,external,howborisusesclaudecode.com,ok,200,https://howborisusesclaudecode.com/,text/html; charset=UTF-8,Boris Cherny's Claude Code Tips ā€” How He Actually Uses It (118+ Tips),"118+ tips from Boris Cherny, creator of Claude Code, on his daily workflow: CLAUDE.md, worktrees, plan mode, hooks, subagents, and more.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0406,Agent of the Day: Copilot Agent PR Analysis,https://github.github.com/gh-aw/blog/2026-05-26-agent-of-the-day/,external,github.github.com,ok,200,https://github.github.com/gh-aw/blog/2026-05-26-agent-of-the-day/,text/html; charset=utf-8,"Agent of the Day ā€“ May 26, 2026 | GitHub Agentic Workflows",Copilot Agent PR Analysis: a daily workflow that monitors GitHub Copilot coding agent performance across pull requests,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0407,"Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows",https://arxiv.org/abs/2607.07052,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07052,text/html; charset=utf-8,"[2607.07052] Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production","Abstract page for arXiv paper 2607.07052: Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Production",,,,,,,,2607.07052,,2026-07-12T10:56:07+00:00 +ale-0408,Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems,https://arxiv.org/abs/2607.08010,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.08010,text/html; charset=utf-8,[2607.08010] Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems,Abstract page for arXiv paper 2607.08010: Tool-Making and Self-Evolving LLM Agents in Low-Latency Systems,,,,,,,,2607.08010,,2026-07-12T10:56:07+00:00 +ale-0409,AI Loop Engineering: Build Autonomous Agents with Claude Code /goal and Routines,https://www.sabrina.dev/p/loop-engineering-claude-code-goal-routines,external,www.sabrina.dev,ok,200,https://www.sabrina.dev/p/loop-engineering-claude-code-goal-routines,text/html; charset=utf-8,AI Loop Engineering: Build Autonomous Agents with Claude Code /goal + Routines,"What loop engineering means in 2026, how to use the Claude Code /goal command, and how to build your first autonomous AI agent with a routine.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0410,Agent Delivery Engineering Predictive Reliability Framework,https://arxiv.org/abs/2607.07689,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07689,text/html; charset=utf-8,[2607.07689] Agent Delivery Engineering Predictive Reliability Framework,Abstract page for arXiv paper 2607.07689: Agent Delivery Engineering Predictive Reliability Framework,,,,,,,,2607.07689,,2026-07-12T10:56:07+00:00 +ale-0411,rocketplaneIO,https://github.com/olemeyer/rocketplaneIO,external,github.com,ok,200,https://github.com/olemeyer/rocketplaneIO,text/html; charset=utf-8,"GitHub - olemeyer/rocketplaneIO: Self-hosted AI SRE for Kubernetes ā€” zero-instrumentation eBPF observability plus a copilot that fixes issues through guardrailed, self-verifying actions. BYO-LLM, air-gapped capable. Ā· GitHub","Self-hosted AI SRE for Kubernetes ā€” zero-instrumentation eBPF observability plus a copilot that fixes issues through guardrailed, self-verifying actions. BYO-LLM, air-gapped capable. - olemeyer/rocketplaneIO",olemeyer/rocketplaneIO,131,2,0,"Self-hosted AI SRE for Kubernetes ā€” zero-instrumentation eBPF observability plus a copilot that fixes issues through guardrailed, self-verifying actions. BYO-LLM, air-gapped capable.",Apache-2.0,2026-07-12T07:23:45Z,,,2026-07-12T10:56:07+00:00 +ale-0412,Resource entry template,templates/resource-entry.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/templates/resource-entry.md,,Resource entry template,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0413,Loop pattern template,templates/loop-pattern.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/templates/loop-pattern.md,,Loop pattern template,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0414,Loop contract schema,schemas/loop-contract.schema.json,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/schemas/loop-contract.schema.json,,Loop contract schema,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0415,Loop contract preview script,scripts/preview_loop_contract.py,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/scripts/preview_loop_contract.py,,Loop contract preview script,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0416,Translation guide,TRANSLATIONS.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/TRANSLATIONS.md,,Translation guide,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0417,Pattern library index,patterns/README.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/patterns/README.md,,Pattern library index,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0418,Example loop specs,examples/README.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/README.md,,Example loop specs,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0419,Loop contract library,examples/README.md#contract-library,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/README.md#contract-library,,Loop contract library,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0420,Runnable test-repair loop,examples/runnable/test-repair-loop.sh,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/runnable/test-repair-loop.sh,,Runnable test-repair loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0421,Runnable loop guide,examples/runnable/README.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/examples/runnable/README.md,,Runnable loop guide,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0422,Loop gallery guide,gallery/README.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/README.md,,Loop gallery guide,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0423,Loop gallery template,gallery/template.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/template.md,,Loop gallery template,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0424,PR babysitter reference loop,gallery/pr-babysitter-reference.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/pr-babysitter-reference.md,,PR babysitter reference loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0425,CI repair reference loop,gallery/ci-repair-reference.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/ci-repair-reference.md,,CI repair reference loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0426,Docs drift reference loop,gallery/docs-drift-reference.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/gallery/docs-drift-reference.md,,Docs drift reference loop,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0427,Most Developers Do Not Need Agent Loops Yet,https://alphasignalai.substack.com/p/most-developers-do-not-need-agent,external,alphasignalai.substack.com,ok,200,https://alphasignalai.substack.com/p/most-developers-do-not-need-agent,text/html; charset=utf-8,Most Developers Do Not Need Agent Loops Yet,"The patterns were documented in 2024. Hereā€™s who it pays off for, and the four conditions that decide.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0428,Engineering Agentic Systems for Reliability,https://pruningmypothos.com/systems/engineering-agentic-systems-for-reliability/,external,pruningmypothos.com,ok,200,https://pruningmypothos.com/systems/engineering-agentic-systems-for-reliability/,text/html,,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0429,"Self-Correcting Agents: Reflexion, CRITIC, and ReAct Loops Compared",https://callsphere.ai/blog/self-correcting-agents-reflexion-critic-react-loops-compared-2026,external,callsphere.ai,ok,200,https://callsphere.ai/blog/self-correcting-agents-reflexion-critic-react-loops-compared-2026,text/html; charset=utf-8,"Self-Correcting Agents: Reflexion, CRITIC, and ReAct Loops Compared | CallSphere Blog","Three self-correction patterns dominate 2026 agent design. Side-by-side analysis of where each one wins, where each one fails, and how to combine them.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0430,How to Build an AI Agent Harness: A 2026 Complete Guide,https://atlan.com/know/how-to-build-ai-agent-harness/,external,atlan.com,ok,200,https://atlan.com/know/how-to-build-ai-agent-harness/,text/html,How to Build an AI Agent Harness: Step-by-Step Tutorial (2026),"Most agent harnesses fail at the data layer, not the loop. Build one the right way in 10 steps, with code and a done test for each. Start at Step 0.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0431,Harness Engineering vs Prompt Engineering vs Context Engineering Explained,https://medium.com/@visrow/harness-engineering-vs-prompt-engineering-vs-context-engineering-explained-0423b692c87d,external,medium.com,restricted,403,https://medium.com/@visrow/harness-engineering-vs-prompt-engineering-vs-context-engineering-explained-0423b692c87d,text/html; charset=UTF-8,,,,,,,,,,,restricted_or_rate_limited,2026-07-12T10:56:07+00:00 +ale-0432,Position: Coding Benchmarks Are Misaligned with Agentic Software Engineering,https://arxiv.org/abs/2606.17799,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.17799,text/html; charset=utf-8,[2606.17799] Position: Coding Benchmarks Are Misaligned with Agentic Software Engineering,Abstract page for arXiv paper 2606.17799: Position: Coding Benchmarks Are Misaligned with Agentic Software Engineering,,,,,,,,2606.17799,,2026-07-12T10:56:07+00:00 +ale-0433,Understanding the Challenges in Iterative Generative Optimization with LLMs,https://arxiv.org/abs/2603.23994,external,arxiv.org,ok,200,https://arxiv.org/abs/2603.23994,text/html; charset=utf-8,[2603.23994] Understanding the Challenges in Iterative Generative Optimization with LLMs,Abstract page for arXiv paper 2603.23994: Understanding the Challenges in Iterative Generative Optimization with LLMs,,,,,,,,2603.23994,,2026-07-12T10:56:07+00:00 +ale-0434,The Illusion of Multi-Agent Advantage,https://arxiv.org/abs/2606.13003,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.13003,text/html; charset=utf-8,[2606.13003] The Illusion of Multi-Agent Advantage,Abstract page for arXiv paper 2606.13003: The Illusion of Multi-Agent Advantage,,,,,,,,2606.13003,,2026-07-12T10:56:07+00:00 +ale-0435,The Coming Loop,https://lucumr.pocoo.org/2026/6/23/the-coming-loop/,external,lucumr.pocoo.org,ok,200,https://lucumr.pocoo.org/2026/6/23/the-coming-loop/,text/html; charset=utf-8,The Coming Loop | Armin Ronacher's Thoughts and Writings,"Loops, harnesses, and why even loop skeptics may end up with them.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0436,"Loop Engineering, the Latest AI Buzzword, Still Needs Humans in the Loop",https://www.theregister.com/ai-and-ml/2026/06/24/loop-engineering-latest-ai-buzzword-still-needs-humans-in-the-loop/5261735,external,www.theregister.com,ok,200,https://www.theregister.com/ai-and-ml/2026/06/24/loop-engineering-latest-ai-buzzword-still-needs-humans-in-the-loop/5261735,text/html; charset=UTF-8,"Loop engineering, latest AI buzzword, still needs humans in the loop",Prompting less and automating more comes with a price,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0437,When Agents Do Not Stop: Uncovering Infinite Agentic Loops in LLM Agents,https://arxiv.org/abs/2607.01641,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.01641,text/html; charset=utf-8,[2607.01641] When Agents Do Not Stop: Uncovering Infinite Agentic Loops in LLM Agents,Abstract page for arXiv paper 2607.01641: When Agents Do Not Stop: Uncovering Infinite Agentic Loops in LLM Agents,,,,,,,,2607.01641,,2026-07-12T10:56:07+00:00 +ale-0438,The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents,https://arxiv.org/abs/2607.07436,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07436,text/html; charset=utf-8,[2607.07436] The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents,Abstract page for arXiv paper 2607.07436: The Blind Curator: How a Biased Judge Silently Disables Skill Retirement in Self-Evolving Agents,,,,,,,,2607.07436,,2026-07-12T10:56:07+00:00 +ale-0439,Do LLM-Generated Skills Make Better AI Data Scientists? A Component Ablation Across Data-Science Workflows,https://arxiv.org/abs/2607.07504,external,arxiv.org,ok,200,https://arxiv.org/abs/2607.07504,text/html; charset=utf-8,[2607.07504] Do LLM-Generated Skills Make Better AI Data Scientists? A Component Ablation Across Data-Science Workflows,Abstract page for arXiv paper 2607.07504: Do LLM-Generated Skills Make Better AI Data Scientists? A Component Ablation Across Data-Science Workflows,,,,,,,,2607.07504,,2026-07-12T10:56:07+00:00 +ale-0440,The Verification Horizon: No Silver Bullet for Coding Agent Rewards,https://arxiv.org/abs/2606.26300,external,arxiv.org,ok,200,https://arxiv.org/abs/2606.26300,text/html; charset=utf-8,[2606.26300] The Verification Horizon: No Silver Bullet for Coding Agent Rewards,Abstract page for arXiv paper 2606.26300: The Verification Horizon: No Silver Bullet for Coding Agent Rewards,,,,,,,,2606.26300,,2026-07-12T10:56:07+00:00 +ale-0441,Write Code Like a Human Will Maintain It,https://unstack.io/write-code-like-a-human-will-maintain-it,external,unstack.io,ok,200,https://unstack.io/write-code-like-a-human-will-maintain-it,text/html; charset=utf-8,Write code like a human will maintain it,"One of the best things about LLMs is that they'll write code for you, all day long. Who cares about DRY? You don't have to be the one updating the same long con...",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0442,Awesome Harness Engineering,https://github.com/ai-boost/awesome-harness-engineering,external,github.com,ok,200,https://github.com/ai-boost/awesome-harness-engineering,text/html; charset=utf-8,"GitHub - ai-boost/awesome-harness-engineering: Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration. Ā· GitHub","Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration. - ai-boost/awesome-harness-engineering",ai-boost/awesome-harness-engineering,2998,313,96,"Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration.",NOASSERTION,2026-07-12T08:57:15Z,,,2026-07-12T10:56:07+00:00 +ale-0443,Awesome Harness Engineering,https://github.com/walkinglabs/awesome-harness-engineering,external,github.com,ok,200,https://github.com/walkinglabs/awesome-harness-engineering,text/html; charset=utf-8,GitHub - walkinglabs/awesome-harness-engineering: šŸ› ļø Awesome tools & guides for harness engineering. Ā· GitHub,šŸ› ļø Awesome tools & guides for harness engineering. - walkinglabs/awesome-harness-engineering,walkinglabs/awesome-harness-engineering,3588,286,24,šŸ› ļø Awesome tools & guides for harness engineering.,NOASSERTION,2026-07-12T09:49:09Z,,,2026-07-12T10:56:07+00:00 +ale-0444,Awesome Agent Harness,https://github.com/AutoJunjie/awesome-agent-harness,external,github.com,ok,200,https://github.com/AutoJunjie/awesome-agent-harness,text/html; charset=utf-8,GitHub - AutoJunjie/awesome-agent-harness Ā· GitHub,Contribute to AutoJunjie/awesome-agent-harness development by creating an account on GitHub.,AutoJunjie/awesome-agent-harness,482,43,16,,,2026-07-11T21:00:59Z,,,2026-07-12T10:56:07+00:00 +ale-0445,Awesome Context Engineering,https://github.com/Meirtz/Awesome-Context-Engineering,external,github.com,ok,200,https://github.com/Meirtz/Awesome-Context-Engineering,text/html; charset=utf-8,"GitHub - Meirtz/Awesome-Context-Engineering: šŸ”„ Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents. Ā· GitHub","šŸ”„ Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents. - Meirtz/Awesome-Context-Engineering",Meirtz/Awesome-Context-Engineering,3240,256,46,"šŸ”„ Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLMs and AI agents.",MIT,2026-07-12T10:03:51Z,,,2026-07-12T10:56:07+00:00 +ale-0446,Awesome Prompt Engineering,https://github.com/promptslab/Awesome-Prompt-Engineering,external,github.com,ok,200,https://github.com/promptslab/Awesome-Prompt-Engineering,text/html; charset=utf-8,"GitHub - promptslab/Awesome-Prompt-Engineering: This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc Ā· GitHub","This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc - GitHub - promptslab/Awesome-Prompt-Engineering: This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc",promptslab/Awesome-Prompt-Engineering,6155,723,88,"This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc",Apache-2.0,2026-07-12T08:37:32Z,,,2026-07-12T10:56:07+00:00 +ale-0447,Awesome LLM Agents,https://github.com/kaushikb11/awesome-llm-agents,external,github.com,ok,200,https://github.com/kaushikb11/awesome-llm-agents,text/html; charset=utf-8,GitHub - kaushikb11/awesome-llm-agents: A curated list of awesome LLM agents frameworks. Ā· GitHub,A curated list of awesome LLM agents frameworks. Contribute to kaushikb11/awesome-llm-agents development by creating an account on GitHub.,kaushikb11/awesome-llm-agents,1528,329,161,A curated list of awesome LLM agents frameworks.,,2026-07-12T03:40:11Z,,,2026-07-12T10:56:07+00:00 +ale-0448,Awesome AI Agents,https://github.com/e2b-dev/awesome-ai-agents,external,github.com,ok,200,https://github.com/e2b-dev/awesome-ai-agents,text/html; charset=utf-8,GitHub - e2b-dev/awesome-ai-agents: A list of AI autonomous agents Ā· GitHub,A list of AI autonomous agents. Contribute to e2b-dev/awesome-ai-agents development by creating an account on GitHub.,e2b-dev/awesome-ai-agents,28703,3137,830,A list of AI autonomous agents,NOASSERTION,2026-07-12T10:56:57Z,,,2026-07-12T10:56:07+00:00 +ale-0449,Awesome CLI Coding Agents,https://github.com/bradAGI/awesome-cli-coding-agents,external,github.com,ok,200,https://github.com/bradAGI/awesome-cli-coding-agents,text/html; charset=utf-8,"GitHub - bradAGI/awesome-cli-coding-agents: Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure. Ā· GitHub","Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure. - GitHub - bradAGI/awesome-cli-coding-agents: Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure.",bradAGI/awesome-cli-coding-agents,792,210,41,"Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure.",,2026-07-12T00:27:00Z,,,2026-07-12T10:56:07+00:00 +ale-0450,Awesome Self-Evolving Agents,https://github.com/XMUDeepLIT/Awesome-Self-Evolving-Agents,external,github.com,ok,200,https://github.com/XMUDeepLIT/Awesome-Self-Evolving-Agents,text/html; charset=utf-8,"GitHub - XMUDeepLIT/Awesome-Self-Evolving-Agents: A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents. Ā· GitHub","A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents. - XMUDeepLIT/Awesome-Self-Evolving-Agents",XMUDeepLIT/Awesome-Self-Evolving-Agents,322,19,4,"A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents.",,2026-07-11T11:12:27Z,,,2026-07-12T10:56:07+00:00 +ale-0451,Awesome AI Agent Papers,https://github.com/VoltAgent/awesome-ai-agent-papers,external,github.com,ok,200,https://github.com/VoltAgent/awesome-ai-agent-papers,text/html; charset=utf-8,"GitHub - VoltAgent/awesome-ai-agent-papers: A curated collection of AI agent research papers released in 2026, covering agent engineering, memory, evaluation, workflows, and autonomous systems. Ā· GitHub","A curated collection of AI agent research papers released in 2026, covering agent engineering, memory, evaluation, workflows, and autonomous systems. - VoltAgent/awesome-ai-agent-papers",VoltAgent/awesome-ai-agent-papers,1563,165,0,"A curated collection of AI agent research papers released in 2026, covering agent engineering, memory, evaluation, workflows, and autonomous systems.",MIT,2026-07-12T07:42:51Z,,,2026-07-12T10:56:07+00:00 +ale-0452,awesome-ralph,https://github.com/snwfdhmp/awesome-ralph,external,github.com,ok,200,https://github.com/snwfdhmp/awesome-ralph,text/html; charset=utf-8,"GitHub - snwfdhmp/awesome-ralph: A curated list of resources about Ralph, the AI coding technique that runs AI coding agents in automated loops until specifications are fulfilled. Ā· GitHub","A curated list of resources about Ralph, the AI coding technique that runs AI coding agents in automated loops until specifications are fulfilled. - snwfdhmp/awesome-ralph",snwfdhmp/awesome-ralph,910,71,12,"A curated list of resources about Ralph, the AI coding technique that runs AI coding agents in automated loops until specifications are fulfilled.",,2026-07-07T13:04:16Z,,,2026-07-12T10:56:07+00:00 +ale-0453,Awesome Agent Loops,https://github.com/serenakeyitan/awesome-agent-loops,external,github.com,ok,200,https://github.com/serenakeyitan/awesome-agent-loops,text/html; charset=utf-8,"GitHub - serenakeyitan/awesome-agent-loops: A curated collection of the best /loop, /goal, and /schedule uses for Claude Code & Codex ā€” real commands sourced from Twitter/X. The awesome-list of agent loops. Ā· GitHub","A curated collection of the best /loop, /goal, and /schedule uses for Claude Code & Codex ā€” real commands sourced from Twitter/X. The awesome-list of agent loops. - serenakeyitan/awesome-agent-loops",serenakeyitan/awesome-agent-loops,191,14,1,"A curated collection of the best /loop, /goal, and /schedule uses for Claude Code & Codex ā€” real commands sourced from Twitter/X. The awesome-list of agent loops.",CC-BY-4.0,2026-07-12T04:47:33Z,,,2026-07-12T10:56:07+00:00 +ale-0454,Landing page,https://chaoyue0307.github.io/awesome-loop-engineering/,external,chaoyue0307.github.io,ok,200,https://chaoyue0307.github.io/awesome-loop-engineering/,text/html; charset=utf-8,Awesome Loop Engineering,"A curated field guide to loop engineering: patterns, loop contracts, and runnable examples for recurring AI agent loops and coding-agent automation.",,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0455,Hugging Face dataset mirror,https://huggingface.co/datasets/cy0307/awesome-loop-engineering,external,huggingface.co,ok,200,https://huggingface.co/datasets/cy0307/awesome-loop-engineering,text/html; charset=utf-8,cy0307/awesome-loop-engineering Ā· Datasets at Hugging Face,Weā€™re on a journey to advance and democratize artificial intelligence through open source and open science.,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0456,Landing page source,docs/index.html,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/docs/index.html,,Landing page source,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0457,Sitemap,docs/sitemap.xml,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/docs/sitemap.xml,,Sitemap,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0458,Robots file,docs/robots.txt,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/docs/robots.txt,,Robots file,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0459,Roadmap,ROADMAP.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/ROADMAP.md,,Roadmap,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0460,Launch article,posts/launch.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/posts/launch.md,,Launch article,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0461,Discussion guide,meta/DISCUSSIONS.md,local_path,,local_ok,,https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/meta/DISCUSSIONS.md,,Discussion guide,,,,,,,,,,,2026-07-12T10:56:07+00:00 +ale-0462,Show your Loop Engineering patterns,https://github.com/ChaoYue0307/awesome-loop-engineering/discussions/2,external,github.com,ok,200,https://github.com/ChaoYue0307/awesome-loop-engineering/discussions/2,text/html; charset=utf-8,Show your Loop Engineering patterns Ā· ChaoYue0307/awesome-loop-engineering Ā· Discussion #2 Ā· GitHub,Show your Loop Engineering patterns,ChaoYue0307/awesome-loop-engineering,22,2,5,"Loop Engineering: a curated field guide to designing recurring AI agent and coding-agent loops ā€” patterns, loop contracts, runnable examples, and resources above prompt, context, and harness engineering.",CC0-1.0,2026-07-12T10:49:27Z,,,2026-07-12T10:56:07+00:00