row_id string | section string | section_slug string | resource_type string | marker string | title string | url string | url_kind string | domain string | annotation string | description string | key_contribution string | novelty string | impact string | signal string | signal_strength string | source_readme string | source_line int64 | source_url string | date_added string | collection string | collection_slug string | user_goal string | lifecycle_stages string | audience string | loop_layer string | scope_fit string | evidence_class string | evidence_tier string | source_status string | canonical_url string | source_title string | source_description string | authors string | publication_date string | publication_year string | publication_venue string | publisher string | doi string | publication_note string | primary_category string | metadata_source string | github_repo string | github_stars string | github_forks string | github_license string | github_created_at string | github_updated_at string | arxiv_id string | audited_at timestamp[ms] |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ale-0901 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Blog | 📝 | Ten AI Agents Destroyed Production, Zero Postmortems | https://www.harperfoley.com/blog/ai-agents-destroyed-production-zero-postmortems | external | www.harperfoley.com | Older than the sweep window (March 2026) but absent from the list and squarely on-topic. Harper Foley (Tribe AI, ex-Navy EOD) catalogs ten production-destroying agent incidents across six tools over 16 months, each sourced to GitHub issues, Fortune, The Register, or first-hand reports, and shows not one vendor publishe... | Older than the sweep window (March 2026) but absent from the list and squarely on-topic. Harper Foley (Tribe AI, ex-Navy EOD) catalogs ten production-destroying agent incidents across six tools over 16 months, each sourced to GitHub issues, Fortune, The Register, or first-hand reports, and shows not one vendor publishe... | Older than the sweep window (March 2026) but absent from the list and squarely on-topic. Harper Foley (Tribe AI, ex-Navy EOD) catalogs ten production-destroying agent incidents across six tools over 16 months, each sourced to GitHub issues, Fortune, The Register, or first-hand reports, and shows not one vendor publishe... | Keeps adoption grounded in known failure modes, economics, and operational limits. Older than the sweep window (March 2026) but absent from the list and squarely on-topic. Harper Foley (Tribe AI, ex-Navy EOD) catalogs ten production-destroying agent incidents across six tools over 16 months, each sourced to GitHub issu... | Use Ten AI Agents Destroyed Production, Zero Postmortems to bound risk before recurring or unattended execution. | Contextual source from www.harperfoley.com; useful for practice signals or boundary conditions, not independent validation. | contextual | README.md | 1,654 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1654 | 2026-08-02 | Govern | govern | Bound permissions, cost, failure, and escalation. | intake;workspace | operator;security | cross-layer | enabling | practitioner-analysis | B | ok | https://www.harperfoley.com/blog/ai-agents-destroyed-production-zero-postmortems | Ten AI Agents Destroyed Production. Zero Postmortems. | Harper Foley | 10 documented incidents across 6 AI coding tools in 16 months. Missing audit trails, no liability frameworks, no vendor postmortems. The accountability infrastructure doesn't exist. | Harper Foley | 2026-03-08 | 2026 | Harper Foley - AI Product Leader | html-meta | 2026-08-07T12:31:05 | |||||||||||
ale-0902 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Blog | 📝 | 2x, Not 10x: Coding With LLMs in 2026 | https://obryant.dev/p/2x-not-10x/ | external | obryant.dev | A calibration essay whose central claim is squarely a loop-engineering claim: LLMs became genuinely useful at the point they got reliable enough to run inside automated feedback loops, and past that threshold further model capability buys much less than retooling does. | A calibration essay whose central claim is squarely a loop-engineering claim: LLMs became genuinely useful at the point they got reliable enough to run inside automated feedback loops, and past that threshold further model capability buys much less than retooling does. | A calibration essay whose central claim is squarely a loop-engineering claim: LLMs became genuinely useful at the point they got reliable enough to run inside automated feedback loops, and past that threshold further model capability buys much less than retooling does. | Keeps adoption grounded in known failure modes, economics, and operational limits. A calibration essay whose central claim is squarely a loop-engineering claim: LLMs became genuinely useful at the point they got reliable enough to run inside automated feedback loops, and past that threshold further model capability buy... | Use 2x, Not 10x: Coding With LLMs in 2026 to bound risk before recurring or unattended execution. | Contextual source from obryant.dev; useful for practice signals or boundary conditions, not independent validation. | contextual | README.md | 1,655 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1655 | 2026-08-02 | Govern | govern | Bound permissions, cost, failure, and escalation. | budget;escalation;exit | operator;security | cross-layer | enabling | practitioner-analysis | B | ok | https://obryant.dev/p/2x-not-10x/ | 2x, not 10x: coding with LLMs in 2026 | Calibrate your enthusiasm | Jacob O'Bryant | obryant.dev | html-meta | 2026-08-07T12:31:05 | |||||||||||||
ale-0903 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Paper | 📄 | Reproducing LightMem: Naive RAG Is Just as Good for Memory Management | https://arxiv.org/abs/2607.29104 | external | arxiv.org | A reproduction study that lands harder than most original results. The authors rebuild LightMem, a well-cited lightweight memory-management approach, and compare it against naive RAG retrieving directly from raw user turns. | A reproduction study that lands harder than most original results. The authors rebuild LightMem, a well-cited lightweight memory-management approach, and compare it against naive RAG retrieving directly from raw user turns. | A reproduction study that lands harder than most original results. The authors rebuild LightMem, a well-cited lightweight memory-management approach, and compare it against naive RAG retrieving directly from raw user turns. | Persistent memory is treated as an external runtime artifact. A reproduction study that lands harder than most original results. The authors rebuild LightMem, a well-cited lightweight memory-management approach, and compare it against naive RAG retrieving directly from raw user turns. | Use Reproducing LightMem: Naive RAG Is Just as Good for Memory Management to bound risk before recurring or unattended execution. | Research source arXiv:2607.29104; inspect its method and evaluation before treating results as production evidence. | medium | README.md | 1,656 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1656 | 2026-08-05 | Govern | govern | Bound permissions, cost, failure, and escalation. | context | researcher;evaluator;operator;security | cross-layer | enabling | research-preprint | A | ok | https://arxiv.org/abs/2607.29104 | [2607.29104] Reproducing LightMem: Naive RAG Is Just as Good for Memory Management | Long-term conversational agents require access to information from earlier interactions, such as a user's preferences, past requests, or previously mentioned facts. Repeatedly providing the full dialogue history can be expensive as conversations grow, so many memory approaches instead transform past interactions into c... | Yongjie Zhou; Shuai Wang; Bevan Koopman; Guido Zuccon | 2026-07-31 | 2026 | arXiv | arXiv | Code: https://github.com/ielab/Reproducing-LightMem | cs.IR | arxiv-api | 2607.29104 | 2026-08-07T12:31:05 | |||||||
ale-0904 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Blog | 📝 | Critical CVEs or LLM Slops? Inside 50+ Fake SQLite Advisories | https://research.jfrog.com/post/sqlite-critical-cves-or-llm-slops/ | external | research.jfrog.com | JFrog Security Research (Afek Berger) audited 55 SQLite vulnerability advisories published from a single GitHub account with initial CVSS scores of 7.5 to 9.8, and found 54 completely fabricated, non-existent functions, invalid line numbers, PoCs that trigger no crash, with one real bug wrapped in unverified CVE metada... | JFrog Security Research (Afek Berger) audited 55 SQLite vulnerability advisories published from a single GitHub account with initial CVSS scores of 7.5 to 9.8, and found 54 completely fabricated, non-existent functions, invalid line numbers, PoCs that trigger no crash, with one real bug wrapped in unverified CVE metada... | JFrog Security Research (Afek Berger) audited 55 SQLite vulnerability advisories published from a single GitHub account with initial CVSS scores of 7.5 to 9.8, and found 54 completely fabricated, non-existent functions, invalid line numbers, PoCs that trigger no crash, with one real bug wrapped in unverified CVE metada... | Keeps adoption grounded in known failure modes, economics, and operational limits. JFrog Security Research (Afek Berger) audited 55 SQLite vulnerability advisories published from a single GitHub account with initial CVSS scores of 7.5 to 9.8, and found 54 completely fabricated, non-existent functions, invalid line numb... | Use Critical CVEs or LLM Slops? Inside 50+ Fake SQLite Advisories to bound risk before recurring or unattended execution. | Contextual source from research.jfrog.com; useful for practice signals or boundary conditions, not independent validation. | contextual | README.md | 1,657 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1657 | 2026-08-05 | Govern | govern | Bound permissions, cost, failure, and escalation. | trigger | operator;security | cross-layer | enabling | practitioner-analysis | B | ok | https://research.jfrog.com/post/sqlite-critical-cves-or-llm-slops/ | SQLite Critical CVEs or LLM Slop? - JFrog Security Research | The JFrog security research team recently identified a supply chain attack targeting the `xinference` package on PyPI. Versions 2.6.0, 2.6.1, and 2.6.2 were compromised and yanked by maintainers after users reported suspicious behavior. If you installed or imported these versions, you must assume your environment is co... | research.jfrog.com | domain-fallback | 2026-08-07T12:31:05 | ||||||||||||||
ale-0905 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Blog | 📝 | Don't be a meat proxy | https://gruhn.me/blog/2026-08-03/ | external | gruhn.me | The highest-traction technical post of the Aug 1-3 window, arguing against the degenerate role humans fall into when they relay model output verbatim, into Slack threads, PR review comments, group chats, without reading, understanding or validating it first. | The highest-traction technical post of the Aug 1-3 window, arguing against the degenerate role humans fall into when they relay model output verbatim, into Slack threads, PR review comments, group chats, without reading, understanding or validating it first. | The highest-traction technical post of the Aug 1-3 window, arguing against the degenerate role humans fall into when they relay model output verbatim, into Slack threads, PR review comments, group chats, without reading, understanding or validating it first. | Keeps adoption grounded in known failure modes, economics, and operational limits. The highest-traction technical post of the Aug 1-3 window, arguing against the degenerate role humans fall into when they relay model output verbatim, into Slack threads, PR review comments, group chats, without reading, understanding or... | Use Don't be a meat proxy to bound risk before recurring or unattended execution. | Contextual source from gruhn.me; useful for practice signals or boundary conditions, not independent validation. | contextual | README.md | 1,658 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1658 | 2026-08-05 | Govern | govern | Bound permissions, cost, failure, and escalation. | budget;escalation;exit | operator;security | cross-layer | enabling | practitioner-analysis | B | ok | https://gruhn.me/blog/2026-08-03/ | Don't be a meat proxy | 2026 | gruhn.me | url-date | 2026-08-07T12:31:05 | ||||||||||||||
ale-0906 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Paper | 📄 | What Breaks When LLMs Code? Characterizing Operational Safety Failures of Agentic Code Assistants | https://arxiv.org/abs/2605.30777 | external | arxiv.org | An incident-driven empirical study rather than a benchmark paper: the authors screened 68,816 papers across 22 venues to curate 185 safety-relevant studies, then mined 16,586 GitHub issues from LLM-powered coding tools and manually confirmed 547 genuine operational safety failures, each annotated with contributing fact... | An incident-driven empirical study rather than a benchmark paper: the authors screened 68,816 papers across 22 venues to curate 185 safety-relevant studies, then mined 16,586 GitHub issues from LLM-powered coding tools and manually confirmed 547 genuine operational safety failures, each annotated with contributing fact... | An incident-driven empirical study rather than a benchmark paper: the authors screened 68,816 papers across 22 venues to curate 185 safety-relevant studies, then mined 16,586 GitHub issues from LLM-powered coding tools and manually confirmed 547 genuine operational safety failures, each annotated with contributing fact... | The work turns loop quality into a measurable task or score. An incident-driven empirical study rather than a benchmark paper: the authors screened 68,816 papers across 22 venues to curate 185 safety-relevant studies, then mined 16,586 GitHub issues from LLM-powered coding tools and manually confirmed 547 genuine opera... | Use What Breaks When LLMs Code? Characterizing Operational Safety Failures of Agentic Code Assistants to bound risk before recurring or unattended execution. | Research source arXiv:2605.30777; inspect its method and evaluation before treating results as production evidence. | medium | README.md | 1,659 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1659 | 2026-08-05 | Govern | govern | Bound permissions, cost, failure, and escalation. | intake;workspace;context;verification | researcher;evaluator;operator;security | cross-layer | enabling | research-preprint | A | ok | https://arxiv.org/abs/2605.30777 | [2605.30777] What Breaks When LLMs Code? Characterizing Operational Safety Failures of Agentic Code Assistants | Autonomous coding agents built on large language models (LLMs) are rapidly being integrated into development workflows, yet their operational safety properties remain poorly understood beyond evaluations of explicitly malicious inputs. In practice, high-impact failures arise during benign, goal-directed use through env... | Alif Al Hasan; Sumon Biswas | 2026-05-29 | 2026 | arXiv | arXiv | 10.1145/3832783.3834393 | This paper is accepted to the 41st IEEE/ACM International Conference on Automated Software Engineering (ASE 2026), Research Track | cs.SE | arxiv-api | 2605.30777 | 2026-08-07T12:31:05 | ||||||
ale-0907 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Paper | 📄 | How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions | https://arxiv.org/abs/2605.29442 | external | arxiv.org | A study of 20,574 real coding-agent sessions across 1,639 repositories, categorizing seven recurring forms of developer-agent misalignment and separating IDE from CLI usage patterns. | A study of 20,574 real coding-agent sessions across 1,639 repositories, categorizing seven recurring forms of developer-agent misalignment and separating IDE from CLI usage patterns. | A study of 20,574 real coding-agent sessions across 1,639 repositories, categorizing seven recurring forms of developer-agent misalignment and separating IDE from CLI usage patterns. | Keeps adoption grounded in known failure modes, economics, and operational limits. A study of 20,574 real coding-agent sessions across 1,639 repositories, categorizing seven recurring forms of developer-agent misalignment and separating IDE from CLI usage patterns. | Use How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions to bound risk before recurring or unattended execution. | Research source arXiv:2605.29442; inspect its method and evaluation before treating results as production evidence. | medium | README.md | 1,660 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1660 | 2026-08-05 | Govern | govern | Bound permissions, cost, failure, and escalation. | budget;escalation;exit | researcher;evaluator;operator;security | cross-layer | enabling | research-preprint | A | ok | https://arxiv.org/abs/2605.29442 | [2605.29442] How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions | AI coding agents increasingly act directly within software environments, yet existing analyses of their failures rely on benchmark trajectories that miss how developers actually experience misalignment. We present an observational study of 20,574 coding-agent sessions from 1,639 repositories across IDE and CLI workflow... | Ningzhi Tang; Chaoran Chen; Gelei Xu; Yiyu Shi; Yu Huang; Collin McMillan; Tao Dong; Toby Jia-Jun Li | 2026-05-28 | 2026 | arXiv | arXiv | cs.SE | arxiv-api | 2605.29442 | 2026-08-07T12:31:05 | ||||||||
ale-0908 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Paper | 📄 | Skill Use or Skill Theater? Evaluating the Reasoning Backroom in Skill-Augmented Language Agents | https://arxiv.org/abs/2607.27484 | external | arxiv.org | BACKTRACE measures whether a skill actually caused a decision by comparing skill-conditioned against no-skill runs and perturbing skill attributes. | BACKTRACE measures whether a skill actually caused a decision by comparing skill-conditioned against no-skill runs and perturbing skill attributes. | BACKTRACE measures whether a skill actually caused a decision by comparing skill-conditioned against no-skill runs and perturbing skill attributes. | Keeps adoption grounded in known failure modes, economics, and operational limits. BACKTRACE measures whether a skill actually caused a decision by comparing skill-conditioned against no-skill runs and perturbing skill attributes. | Use Skill Use or Skill Theater? Evaluating the Reasoning Backroom in Skill-Augmented Language Agents to bound risk before recurring or unattended execution. | Research source arXiv:2607.27484; inspect its method and evaluation before treating results as production evidence. | medium | README.md | 1,661 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1661 | 2026-08-05 | Govern | govern | Bound permissions, cost, failure, and escalation. | budget;escalation;exit | researcher;evaluator;operator;security | cross-layer | enabling | research-preprint | A | ok | https://arxiv.org/abs/2607.27484 | [2607.27484] Skill Use or Skill Theater? Evaluating the Reasoning Backroom in Skill-Augmented Language Agents | Reusable skills are becoming a standard interface for extending language agents with task procedures. Yet evaluators usually infer skill use from visible reasoning or the agent's own attribution. These signals show what the agent appears to use, not whether the skill changed its decision. We ask whether skill-augmented... | Jinwei Hu; Yi Qi; Xinmiao Huang; Youcheng Sun; Yi Dong; Xiaowei Huang | 2026-07-29 | 2026 | arXiv | arXiv | 21 pages | cs.AI | arxiv-api | 2607.27484 | 2026-08-07T12:31:05 | |||||||
ale-0909 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Paper | 📄 | Fidelity Is Not Safety: Gently-Compressed LLMs Pass Every Data-Free Quality Guard Yet Invent Procedure Steps in Agentic Execution | https://arxiv.org/abs/2607.28196 | external | arxiv.org | Compressed models clear perplexity, downstream accuracy, and data-free output-fidelity checks, then fabricate procedure steps once deployed in an agent loop, and the effect is specific to coherent low-rank (SVD) error, not magnitude pruning at matched perplexity. | Compressed models clear perplexity, downstream accuracy, and data-free output-fidelity checks, then fabricate procedure steps once deployed in an agent loop, and the effect is specific to coherent low-rank (SVD) error, not magnitude pruning at matched perplexity. | Compressed models clear perplexity, downstream accuracy, and data-free output-fidelity checks, then fabricate procedure steps once deployed in an agent loop, and the effect is specific to coherent low-rank (SVD) error, not magnitude pruning at matched perplexity. | Keeps adoption grounded in known failure modes, economics, and operational limits. Compressed models clear perplexity, downstream accuracy, and data-free output-fidelity checks, then fabricate procedure steps once deployed in an agent loop, and the effect is specific to coherent low-rank (SVD) error, not magnitude prun... | Use Fidelity Is Not Safety: Gently-Compressed LLMs Pass Every Data-Free Quality Guard Yet Invent Procedure Steps in Agentic Execution to bound risk before recurring or unattended execution. | Research source arXiv:2607.28196; inspect its method and evaluation before treating results as production evidence. | medium | README.md | 1,662 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1662 | 2026-08-05 | Govern | govern | Bound permissions, cost, failure, and escalation. | budget;escalation;exit | researcher;evaluator;operator;security | cross-layer | enabling | research-preprint | A | ok | https://arxiv.org/abs/2607.28196 | [2607.28196] Fidelity Is Not Safety: Gently-Compressed LLMs Pass Every Data-Free Quality Guard Yet Invent Procedure Steps in Agentic Execution | Practitioners accept a compressed language model once it clears a stack of data-cheap quality guards: perplexity within a small factor of the original, downstream accuracy (for example MMLU) inside a confidence interval, and data-free output-fidelity signals that compare the compressed and original network's internal r... | I. Kennedy; T. Kennedy | 2026-07-30 | 2026 | arXiv | arXiv | cs.CL | arxiv-api | 2607.28196 | 2026-08-07T12:31:05 | ||||||||
ale-0910 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Paper | 📄 | Rethinking Inference-Time Scaling in Local Computer-Use Agents: Failure Modes and Compute Tradeoffs | https://arxiv.org/abs/2607.28573 | external | arxiv.org | Tests whether spending more inference compute rescues small locally-hosted computer-use agents on OSWorld, and finds it mostly changes the failure mode rather than fixing it: contextual scaling stabilizes trajectories, but temporal scaling extends wrong paths instead of correcting them. A useful corrective to 'just let... | Tests whether spending more inference compute rescues small locally-hosted computer-use agents on OSWorld, and finds it mostly changes the failure mode rather than fixing it: contextual scaling stabilizes trajectories, but temporal scaling extends wrong paths instead of correcting them. A useful corrective to 'just let... | Tests whether spending more inference compute rescues small locally-hosted computer-use agents on OSWorld, and finds it mostly changes the failure mode rather than fixing it: contextual scaling stabilizes trajectories, but temporal scaling extends wrong paths instead of correcting them. A useful corrective to 'just let... | Keeps adoption grounded in known failure modes, economics, and operational limits. Tests whether spending more inference compute rescues small locally-hosted computer-use agents on OSWorld, and finds it mostly changes the failure mode rather than fixing it: contextual scaling stabilizes trajectories, but temporal scali... | Use Rethinking Inference-Time Scaling in Local Computer-Use Agents: Failure Modes and Compute Tradeoffs to bound risk before recurring or unattended execution. | Research source arXiv:2607.28573; inspect its method and evaluation before treating results as production evidence. | medium | README.md | 1,663 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1663 | 2026-08-05 | Govern | govern | Bound permissions, cost, failure, and escalation. | verification | researcher;evaluator;operator;security | cross-layer | enabling | research-preprint | A | ok | https://arxiv.org/abs/2607.28573 | [2607.28573] Rethinking Inference-Time Scaling in Local Computer-Use Agents: Failure Modes and Compute Tradeoffs | Deploying autonomous computer-use agents (CUAs) locally is increasingly important for privacy, cost efficiency, and practical usability, yet improving their performance under strict hardware constraints remains challenging. While recent studies show that inference-time scaling can improve frontier computer-use agents t... | Woongkyu Lee; Jungwook Choi | 2026-07-30 | 2026 | arXiv | arXiv | cs.AI | arxiv-api | 2607.28573 | 2026-08-07T12:31:05 | ||||||||
ale-0911 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Paper | 📄 | Safeguards Based on Copyable Context Cannot Provide Reliable Safety for LLMs | https://arxiv.org/abs/2607.27951 | external | arxiv.org | Submitted 2026-07-30. An impossibility argument aimed squarely at the standard loop-safety design: if the evidence a safeguard uses (system prompt, conversation history, stated role) is copyable, an attacker can imitate it. | Submitted 2026-07-30. An impossibility argument aimed squarely at the standard loop-safety design: if the evidence a safeguard uses (system prompt, conversation history, stated role) is copyable, an attacker can imitate it. | Submitted 2026-07-30. An impossibility argument aimed squarely at the standard loop-safety design: if the evidence a safeguard uses (system prompt, conversation history, stated role) is copyable, an attacker can imitate it. | Context is managed as durable loop state rather than a single prompt payload. Submitted 2026-07-30. An impossibility argument aimed squarely at the standard loop-safety design: if the evidence a safeguard uses (system prompt, conversation history, stated role) is copyable, an attacker can imitate it. | Use Safeguards Based on Copyable Context Cannot Provide Reliable Safety for LLMs to bound risk before recurring or unattended execution. | Research source arXiv:2607.27951; inspect its method and evaluation before treating results as production evidence. | medium | README.md | 1,664 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1664 | 2026-08-07 | Govern | govern | Bound permissions, cost, failure, and escalation. | context | researcher;evaluator;operator;security | cross-layer | enabling | research-preprint | A | ok | https://arxiv.org/abs/2607.27951 | [2607.27951] Safeguards Based on Copyable Context Cannot Provide Reliable Safety for LLMs | Large language model safeguards decide whether to answer before seeing how an answer will be used. This creates a basic problem for dual-use tasks: the same answer can help an authorized professional or an attacker, while an attacker can imitate a benign request and interaction history. We separate the capability relea... | Pingyu Wu; Lingyao Zhu; Weiming Zhang; Nenghai Yu | 2026-07-30 | 2026 | arXiv | arXiv | cs.CR | arxiv-api | 2607.27951 | 2026-08-07T12:31:05 | ||||||||
ale-0912 | Critiques, Risks, And Limitations | critiques-risks-and-limitations | Paper | 📄 | Do Context Files Help Coding Agents? A Two-Agent Ablation Study on Real Repositories | https://arxiv.org/abs/2607.27250 | external | arxiv.org | Submitted 2026-07-28. Controlled ablation of AGENTS.md / CLAUDE.md context files across two frontier agents, 17 real repository tasks, and 288 evaluated runs. Finding: context strategy does not measurably move correctness on either agent, and failures are dominated by implementation difficulty rather than missing repo ... | Submitted 2026-07-28. Controlled ablation of AGENTS.md / CLAUDE.md context files across two frontier agents, 17 real repository tasks, and 288 evaluated runs. Finding: context strategy does not measurably move correctness on either agent, and failures are dominated by implementation difficulty rather than missing repo ... | Submitted 2026-07-28. Controlled ablation of AGENTS.md / CLAUDE.md context files across two frontier agents, 17 real repository tasks, and 288 evaluated runs. Finding: context strategy does not measurably move correctness on either agent, and failures are dominated by implementation difficulty rather than missing repo ... | Context is managed as durable loop state rather than a single prompt payload. Submitted 2026-07-28. Controlled ablation of AGENTS.md / CLAUDE.md context files across two frontier agents, 17 real repository tasks, and 288 evaluated runs. Finding: context strategy does not measurably move correctness on either agent, and... | Use Do Context Files Help Coding Agents? A Two-Agent Ablation Study on Real Repositories to bound risk before recurring or unattended execution. | Research source arXiv:2607.27250; inspect its method and evaluation before treating results as production evidence. | medium | README.md | 1,665 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1665 | 2026-08-07 | Govern | govern | Bound permissions, cost, failure, and escalation. | context | researcher;evaluator;operator;security | cross-layer | enabling | research-preprint | A | ok | https://arxiv.org/abs/2607.27250 | [2607.27250] Do Context Files Help Coding Agents? A Two-Agent Ablation Study on Real Repositories | Persistent context files (AGENTS.md, CLAUDE.md) are standard practice for guiding AI coding agents, yet evidence for their effectiveness is contradictory. We present a controlled ablation of context-injection strategy across two frontier agents (Claude Code and Codex), 17 real tasks from 3 repositories (15 shared + 2 C... | Prakhar Khatri | 2026-07-28 | 2026 | arXiv | arXiv | cs.SE | arxiv-api | 2607.27250 | 2026-08-07T12:31:05 | ||||||||
ale-0913 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome Harness Engineering by ai-boost | https://github.com/ai-boost/awesome-harness-engineering | external | github.com | Comprehensive list for the agent harness layer that Loop Engineering builds on. | Comprehensive list for the agent harness layer that Loop Engineering builds on. | Comprehensive list for the agent harness layer that Loop Engineering builds on. | Connects neighboring ecosystems while preserving Loop Engineering as a narrower operating concept. Comprehensive list for the agent harness layer that Loop Engineering builds on. | Use Awesome Harness Engineering by ai-boost to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (3,446 stars; 389 forks; NOASSERTION license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,685 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1685 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/ai-boost/awesome-harness-engineering | GitHub - ai-boost/awesome-harness-engineering: Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration. · GitHub | Awesome list for AI agent harness engineering: tools, patterns, evals, memory, MCP, permissions, observability, and orchestration. - ai-boost/awesome-harness-engineering | 2026-03-29 | 2026 | ai-boost/awesome-harness-engineering | GitHub | github-api | ai-boost/awesome-harness-engineering | 3446 | 389 | NOASSERTION | 2026-03-29T15:39:49Z | 2026-08-07T09:18:17Z | 2026-08-07T12:31:05 | ||||||
ale-0914 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome Harness Engineering by walkinglabs | https://github.com/walkinglabs/awesome-harness-engineering | external | github.com | High-signal harness list with strong categories for context, guardrails, specs, evals, runtimes, and benchmarks. | High-signal harness list with strong categories for context, guardrails, specs, evals, runtimes, and benchmarks. | High-signal harness list with strong categories for context, guardrails, specs, evals, runtimes, and benchmarks. | Evaluation data is used as the feedback signal for improving loop behavior. High-signal harness list with strong categories for context, guardrails, specs, evals, runtimes, and benchmarks. | Use Awesome Harness Engineering by walkinglabs to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (3,776 stars; 310 forks; NOASSERTION license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,686 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1686 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | context;verification | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/walkinglabs/awesome-harness-engineering | GitHub - walkinglabs/awesome-harness-engineering: 🛠️ Awesome tools & guides for harness engineering. · GitHub | 🛠️ Awesome tools & guides for harness engineering. - walkinglabs/awesome-harness-engineering | 2026-03-29 | 2026 | walkinglabs/awesome-harness-engineering | GitHub | github-api | walkinglabs/awesome-harness-engineering | 3776 | 310 | NOASSERTION | 2026-03-29T11:29:37Z | 2026-08-07T12:17:05Z | 2026-08-07T12:31:05 | ||||||
ale-0915 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome Agent Harness | https://github.com/AutoJunjie/awesome-agent-harness | external | github.com | Curated tools and resources for environments, constraints, and feedback around coding agents. | Curated tools and resources for environments, constraints, and feedback around coding agents. | Curated tools and resources for environments, constraints, and feedback around coding agents. | Connects neighboring ecosystems while preserving Loop Engineering as a narrower operating concept. Curated tools and resources for environments, constraints, and feedback around coding agents. | Use Awesome Agent Harness to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (507 stars; 54 forks; updated 2026-08-06); popularity is context, not proof of reliability. | medium | README.md | 1,687 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1687 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | workspace | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/AutoJunjie/awesome-agent-harness | GitHub - AutoJunjie/awesome-agent-harness · GitHub | Contribute to AutoJunjie/awesome-agent-harness development by creating an account on GitHub. | 2026-03-05 | 2026 | AutoJunjie/awesome-agent-harness | GitHub | github-api | AutoJunjie/awesome-agent-harness | 507 | 54 | 2026-03-05T13:19:10Z | 2026-08-06T21:07:18Z | 2026-08-07T12:31:05 | |||||||
ale-0916 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome Context Engineering | https://github.com/Meirtz/Awesome-Context-Engineering | external | github.com | Survey-style list for context engineering across LLMs and agents. | Survey-style list for context engineering across LLMs and agents. | Survey-style list for context engineering across LLMs and agents. | Context is managed as durable loop state rather than a single prompt payload. Survey-style list for context engineering across LLMs and agents. | Use Awesome Context Engineering to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (3,269 stars; 266 forks; MIT license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,688 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1688 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | context | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/Meirtz/Awesome-Context-Engineering | GitHub - Meirtz/Awesome-Context-Engineering: 🔥 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. · GitHub | 🔥 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 | 2025-07-02 | 2025 | Meirtz/Awesome-Context-Engineering | GitHub | github-api | Meirtz/Awesome-Context-Engineering | 3269 | 266 | MIT | 2025-07-02T17:46:03Z | 2026-08-07T08:09:24Z | 2026-08-07T12:31:05 | ||||||
ale-0917 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome Prompt Engineering | https://github.com/promptslab/Awesome-Prompt-Engineering | external | github.com | Classic adjacent list for prompt techniques and prompting resources. | Classic adjacent list for prompt techniques and prompting resources. | Classic adjacent list for prompt techniques and prompting resources. | Connects neighboring ecosystems while preserving Loop Engineering as a narrower operating concept. Classic adjacent list for prompt techniques and prompting resources. | Use Awesome Prompt Engineering to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (6,231 stars; 745 forks; Apache-2.0 license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,689 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1689 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/promptslab/Awesome-Prompt-Engineering | 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 · 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 Transform... | 2023-02-09 | 2023 | promptslab/Awesome-Prompt-Engineering | GitHub | github-api | promptslab/Awesome-Prompt-Engineering | 6231 | 745 | Apache-2.0 | 2023-02-09T18:22:52Z | 2026-08-07T07:27:17Z | 2026-08-07T12:31:05 | ||||||
ale-0918 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome LLM Agents | https://github.com/kaushikb11/awesome-llm-agents | external | github.com | General list of LLM agent papers, frameworks, and applications. | General list of LLM agent papers, frameworks, and applications. | General list of LLM agent papers, frameworks, and applications. | Connects neighboring ecosystems while preserving Loop Engineering as a narrower operating concept. General list of LLM agent papers, frameworks, and applications. | Use Awesome LLM Agents to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (1,559 stars; 335 forks; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,690 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1690 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/kaushikb11/awesome-llm-agents | GitHub - kaushikb11/awesome-llm-agents: A curated list of awesome LLM agents frameworks. · GitHub | A curated list of awesome LLM agents frameworks. Contribute to kaushikb11/awesome-llm-agents development by creating an account on GitHub. | 2023-04-04 | 2023 | kaushikb11/awesome-llm-agents | GitHub | github-api | kaushikb11/awesome-llm-agents | 1559 | 335 | 2023-04-04T10:22:43Z | 2026-08-07T12:32:50Z | 2026-08-07T12:31:05 | |||||||
ale-0919 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome AI Agents | https://github.com/e2b-dev/awesome-ai-agents | external | github.com | Broad AI agent ecosystem map. | Broad AI agent ecosystem map. | Broad AI agent ecosystem map. | Connects neighboring ecosystems while preserving Loop Engineering as a narrower operating concept. Broad AI agent ecosystem map. | Use Awesome AI Agents to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (29,296 stars; 3,287 forks; NOASSERTION license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,691 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1691 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/e2b-dev/awesome-ai-agents | GitHub - e2b-dev/awesome-ai-agents: A list of AI autonomous agents · GitHub | A list of AI autonomous agents. Contribute to e2b-dev/awesome-ai-agents development by creating an account on GitHub. | 2023-06-19 | 2023 | e2b-dev/awesome-ai-agents | GitHub | github-api | e2b-dev/awesome-ai-agents | 29296 | 3287 | NOASSERTION | 2023-06-19T00:20:06Z | 2026-08-07T10:32:15Z | 2026-08-07T12:31:05 | ||||||
ale-0920 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome CLI Coding Agents | https://github.com/bradAGI/awesome-cli-coding-agents | external | github.com | Directory of terminal-native coding agents, parallel runners, autonomous loops, and the harnesses that orchestrate them. | Directory of terminal-native coding agents, parallel runners, autonomous loops, and the harnesses that orchestrate them. | Directory of terminal-native coding agents, parallel runners, autonomous loops, and the harnesses that orchestrate them. | Orchestration and control flow are made explicit and inspectable. Directory of terminal-native coding agents, parallel runners, autonomous loops, and the harnesses that orchestrate them. | Use Awesome CLI Coding Agents to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (958 stars; 261 forks; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,692 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1692 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | delegation | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/bradAGI/awesome-cli-coding-agents | 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. · 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 dire... | 2026-02-07 | 2026 | bradAGI/awesome-cli-coding-agents | GitHub | github-api | bradAGI/awesome-cli-coding-agents | 958 | 261 | 2026-02-07T00:53:24Z | 2026-08-07T10:14:47Z | 2026-08-07T12:31:05 | |||||||
ale-0921 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome Self-Evolving Agents | https://github.com/XMUDeepLIT/Awesome-Self-Evolving-Agents | external | github.com | Survey-style list of agents that improve themselves over repeated runs, an adjacent angle on long-running loops with memory and verification. | Survey-style list of agents that improve themselves over repeated runs, an adjacent angle on long-running loops with memory and verification. | Survey-style list of agents that improve themselves over repeated runs, an adjacent angle on long-running loops with memory and verification. | Verification is promoted from a final check to a loop-control signal. Survey-style list of agents that improve themselves over repeated runs, an adjacent angle on long-running loops with memory and verification. | Use Awesome Self-Evolving Agents to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (382 stars; 23 forks; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,693 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1693 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | context;verification | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/XMUDeepLIT/Awesome-Self-Evolving-Agents | 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. · 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 | 2026-02-09 | 2026 | XMUDeepLIT/Awesome-Self-Evolving-Agents | GitHub | github-api | XMUDeepLIT/Awesome-Self-Evolving-Agents | 382 | 23 | 2026-02-09T10:57:30Z | 2026-08-07T08:35:24Z | 2026-08-07T12:31:05 | |||||||
ale-0922 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome AI Agent Papers | https://github.com/VoltAgent/awesome-ai-agent-papers | external | github.com | Curated 2026 research collection across agent engineering, memory, evaluation, workflows, and autonomous systems, a paper-level feeder for loop-design foundations. | Curated 2026 research collection across agent engineering, memory, evaluation, workflows, and autonomous systems, a paper-level feeder for loop-design foundations. | Curated 2026 research collection across agent engineering, memory, evaluation, workflows, and autonomous systems, a paper-level feeder for loop-design foundations. | Evaluation data is used as the feedback signal for improving loop behavior. Curated 2026 research collection across agent engineering, memory, evaluation, workflows, and autonomous systems, a paper-level feeder for loop-design foundations. | Use Awesome AI Agent Papers to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (1,661 stars; 172 forks; MIT license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,694 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1694 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | context;verification | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/VoltAgent/awesome-ai-agent-papers | 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. · 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 | 2026-02-10 | 2026 | VoltAgent/awesome-ai-agent-papers | GitHub | github-api | VoltAgent/awesome-ai-agent-papers | 1661 | 172 | MIT | 2026-02-10T10:58:31Z | 2026-08-07T00:40:39Z | 2026-08-07T12:31:05 | ||||||
ale-0923 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | awesome-ralph | https://github.com/snwfdhmp/awesome-ralph | external | github.com | Curated directory for the Ralph technique, collecting official resources, implementations, playbooks, tutorials, and community channels for running coding agents in automated loops until specifications are fulfilled. | Curated directory for the Ralph technique, collecting official resources, implementations, playbooks, tutorials, and community channels for running coding agents in automated loops until specifications are fulfilled. | Curated directory for the Ralph technique, collecting official resources, implementations, playbooks, tutorials, and community channels for running coding agents in automated loops until specifications are fulfilled. | Primary-source operational guidance rather than commentary. Curated directory for the Ralph technique, collecting official resources, implementations, playbooks, tutorials, and community channels for running coding agents in automated loops until specifications are fulfilled. | Use awesome-ralph to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (918 stars; 73 forks; updated 2026-08-03); popularity is context, not proof of reliability. | medium | README.md | 1,695 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1695 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/snwfdhmp/awesome-ralph | 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. · 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 | 2026-01-19 | 2026 | snwfdhmp/awesome-ralph | GitHub | github-api | snwfdhmp/awesome-ralph | 918 | 73 | 2026-01-19T08:42:54Z | 2026-08-03T02:14:41Z | 2026-08-07T12:31:05 | |||||||
ale-0924 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome Agent Loops | https://github.com/serenakeyitan/awesome-agent-loops | external | github.com | Curated collection of /loop, /goal, and /schedule commands for Claude Code and Codex sourced from practitioner posts, organized around trigger, condition, and skill structure. | Curated collection of /loop, /goal, and /schedule commands for Claude Code and Codex sourced from practitioner posts, organized around trigger, condition, and skill structure. | Curated collection of /loop, /goal, and /schedule commands for Claude Code and Codex sourced from practitioner posts, organized around trigger, condition, and skill structure. | The trigger or cadence is explicit, making the workflow recurring rather than one-off. Curated collection of /loop, /goal, and /schedule commands for Claude Code and Codex sourced from practitioner posts, organized around trigger, condition, and skill structure. | Use Awesome Agent Loops to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (199 stars; 15 forks; CC-BY-4.0 license; updated 2026-07-31); popularity is context, not proof of reliability. | medium | README.md | 1,696 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1696 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | objective;trigger | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/serenakeyitan/awesome-agent-loops | GitHub - serenakeyitan/awesome-agent-loops: A curated collection of the best /loop, /goal, and /schedule uses for Claude Code & Codex — real commands sourced from Twitter/X. The awesome-list of agent loops. · GitHub | A curated collection of the best /loop, /goal, and /schedule uses for Claude Code & Codex — real commands sourced from Twitter/X. The awesome-list of agent loops. - serenakeyitan/awesome-agent-loops | 2026-06-09 | 2026 | serenakeyitan/awesome-agent-loops | GitHub | github-api | serenakeyitan/awesome-agent-loops | 199 | 15 | CC-BY-4.0 | 2026-06-09T01:26:51Z | 2026-07-31T21:42:36Z | 2026-08-07T12:31:05 | ||||||
ale-0925 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | Awesome Loop Models | https://github.com/huskydoge/Awesome-Loop-Models | external | github.com | Dedicated catalog of architectures that reuse a learned layer, block, module, or operator within one forward process; use it for deeper model-level coverage while this repository focuses on the bridge to operational agent loops. | Dedicated catalog of architectures that reuse a learned layer, block, module, or operator within one forward process; use it for deeper model-level coverage while this repository focuses on the bridge to operational agent loops. | Dedicated catalog of architectures that reuse a learned layer, block, module, or operator within one forward process; use it for deeper model-level coverage while this repository focuses on the bridge to operational agent loops. | Connects neighboring ecosystems while preserving Loop Engineering as a narrower operating concept. Dedicated catalog of architectures that reuse a learned layer, block, module, or operator within one forward process; use it for deeper model-level coverage while this repository focuses on the bridge to operational agent... | Use Awesome Loop Models to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (251 stars; 7 forks; MIT license; updated 2026-08-06); popularity is context, not proof of reliability. | medium | README.md | 1,697 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1697 | 2026-07-18 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | model | adjacent | curated-index | C | ok | https://github.com/huskydoge/Awesome-Loop-Models | GitHub - huskydoge/Awesome-Loop-Models: A curated list of papers and selected technical blogs on Loop Models. · GitHub | A curated list of papers and selected technical blogs on Loop Models. - huskydoge/Awesome-Loop-Models | 2026-04-24 | 2026 | huskydoge/Awesome-Loop-Models | GitHub | github-api | huskydoge/Awesome-Loop-Models | 251 | 7 | MIT | 2026-04-24T12:16:55Z | 2026-08-06T06:39:28Z | 2026-08-07T12:31:05 | |||||
ale-0926 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | harness-engineering (Ryan Lopopolo) | https://github.com/lopopolo/harness-engineering | external | github.com | Ryan Lopopolo's anthology, field guide, and agent context bundle for harness engineering, collecting primary sources on the layer directly beneath loop engineering. | Ryan Lopopolo's anthology, field guide, and agent context bundle for harness engineering, collecting primary sources on the layer directly beneath loop engineering. | Ryan Lopopolo's anthology, field guide, and agent context bundle for harness engineering, collecting primary sources on the layer directly beneath loop engineering. | Context is managed as durable loop state rather than a single prompt payload. Ryan Lopopolo's anthology, field guide, and agent context bundle for harness engineering, collecting primary sources on the layer directly beneath loop engineering. | Use harness-engineering (Ryan Lopopolo) to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (2,464 stars; 253 forks; CC-BY-4.0 license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,698 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1698 | 2026-07-22 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | context | builder | cross-layer | adjacent | curated-index | C | ok | https://github.com/lopopolo/harness-engineering | GitHub - lopopolo/harness-engineering: 🐎 Ryan Lopopolo’s anthology, field guide, and agent context bundle for harness engineering · GitHub | 🐎 Ryan Lopopolo’s anthology, field guide, and agent context bundle for harness engineering - lopopolo/harness-engineering | 2026-07-18 | 2026 | lopopolo/harness-engineering | GitHub | github-api | lopopolo/harness-engineering | 2464 | 253 | CC-BY-4.0 | 2026-07-18T21:42:28Z | 2026-08-07T11:28:06Z | 2026-08-07T12:31:05 | |||||
ale-0927 | Adjacent Awesome Lists | adjacent-awesome-lists | List | 🧭 | A Coding-Agent Reading List: Behind the Loops | https://insights.ml4trading.io/p/a-coding-agent-reading-list-behind | external | insights.ml4trading.io | Stefan Jansen's curated reading path of 60+ resources on coding-agent loops, organized to separate practitioner discourse, control-theory foundations, agent primitives, harness papers, adoption studies, and safety work by evidence type. | Stefan Jansen's curated reading path of 60+ resources on coding-agent loops, organized to separate practitioner discourse, control-theory foundations, agent primitives, harness papers, adoption studies, and safety work by evidence type. | Stefan Jansen's curated reading path of 60+ resources on coding-agent loops, organized to separate practitioner discourse, control-theory foundations, agent primitives, harness papers, adoption studies, and safety work by evidence type. | Connects neighboring ecosystems while preserving Loop Engineering as a narrower operating concept. Stefan Jansen's curated reading path of 60+ resources on coding-agent loops, organized to separate practitioner discourse, control-theory foundations, agent primitives, harness papers, adoption studies, and safety work by... | Use A Coding-Agent Reading List: Behind the Loops to reuse a concrete artifact or connect it to the wider ecosystem. | Contextual source from insights.ml4trading.io; useful for practice signals or boundary conditions, not independent validation. | contextual | README.md | 1,699 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1699 | 2026-07-23 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | adjacent | curated-index | C | ok | https://insights.ml4trading.io/p/a-coding-agent-reading-list-behind | A Coding-Agent Reading List: Behind the Loops | Loop engineering is only the surface. A reading path through the older control problems underneath — and the line between what a coding agent may change and the experimental decisions that determine whether a result is valid. | Stefan Jansen | insights.ml4trading.io | html-meta | 2026-08-07T12:31:05 | |||||||||||||
ale-0928 | Explore And Reuse | explore-and-reuse | Template | 🧾 | Resource Atlas | https://chaoyue0307.github.io/awesome-loop-engineering/ | external | chaoyue0307.github.io | Filter 937 resources by goal, loop layer, lifecycle stage, artifact type, evidence class, and search query. | Filter 937 resources by goal, loop layer, lifecycle stage, artifact type, evidence class, and search query. | Filter 937 resources by goal, loop layer, lifecycle stage, artifact type, evidence class, and search query. | Turns the evidence into an interactive atlas and structured data. Filter 937 resources by goal, loop layer, lifecycle stage, artifact type, evidence class, and search query. | Use Resource Atlas to reuse a concrete artifact or connect it to the wider ecosystem. | Reusable template, schema, checklist, or guide; signal comes from concrete adaptation and validation. | medium | README.md | 1,707 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1707 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | objective | builder | cross-layer | enabling | reusable-artifact | A | ok | https://chaoyue0307.github.io/awesome-loop-engineering/ | Awesome Loop Engineering | Explore 931 resources from model recurrence to governed agent operations, then build with 22 patterns, 22 contracts, and 8 runtime starters. | Chaoyue He | chaoyue0307.github.io | html-meta | 2026-08-07T12:31:05 | ||||||||||||||
ale-0929 | Explore And Reuse | explore-and-reuse | List | 🧭 | Hugging Face dataset | https://huggingface.co/datasets/cy0307/awesome-loop-engineering | external | huggingface.co | Query the full collection as generated CSV and JSONL tables with publication, evidence, and lifecycle fields. | Query the full collection as generated CSV and JSONL tables with publication, evidence, and lifecycle fields. | Query the full collection as generated CSV and JSONL tables with publication, evidence, and lifecycle fields. | Packages the evidence as queryable CSV and JSONL rather than only a rendered page. Query the full collection as generated CSV and JSONL tables with publication, evidence, and lifecycle fields. | Use Hugging Face dataset to reuse a concrete artifact or connect it to the wider ecosystem. | Contextual source from huggingface.co; useful for practice signals or boundary conditions, not independent validation. | contextual | README.md | 1,708 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1708 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | enabling | curated-index | C | ok | https://huggingface.co/datasets/cy0307/awesome-loop-engineering | cy0307/awesome-loop-engineering · Datasets at Hugging Face | We’re on a journey to advance and democratize artificial intelligence through open source and open science. | Hugging Face | domain-fallback | 2026-08-07T12:31:05 | |||||||||||||||
ale-0930 | Explore And Reuse | explore-and-reuse | Template | 🧾 | Dataset export guide | data/README.md | local_path | Load, query, regenerate, and audit the CSV, JSONL, and Resource Atlas data. | Load, query, regenerate, and audit the CSV, JSONL, and Resource Atlas data. | Load, query, regenerate, and audit the CSV, JSONL, and Resource Atlas data. | Packages the evidence as queryable CSV and JSONL rather than only a rendered page. Load, query, regenerate, and audit the CSV, JSONL, and Resource Atlas data. | Use Dataset export guide to reuse a concrete artifact or connect it to the wider ecosystem. | Repository file; inspect the linked schema, example, guide, or implementation. | medium | README.md | 1,709 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1709 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | enabling | repository-native | A | local_ok | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/data/README.md | Dataset export guide | 2026 | GitHub | GitHub | repository | 2026-08-07T12:31:05 | |||||||||||||||
ale-0931 | Explore And Reuse | explore-and-reuse | Template | 🧾 | Runtime selection guide | meta/RUNTIME_SELECTION.md | local_path | Compare session, scheduled, CI, cron, and durable runtimes by persistence, isolation, permissions, and state. | Compare session, scheduled, CI, cron, and durable runtimes by persistence, isolation, permissions, and state. | Compare session, scheduled, CI, cron, and durable runtimes by persistence, isolation, permissions, and state. | Durable execution and replay are treated as first-class loop infrastructure. Compare session, scheduled, CI, cron, and durable runtimes by persistence, isolation, permissions, and state. | Use Runtime selection guide to reuse a concrete artifact or connect it to the wider ecosystem. | Repository file; inspect the linked schema, example, guide, or implementation. | medium | README.md | 1,710 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1710 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | trigger;workspace;state | builder | cross-layer | enabling | repository-native | A | local_ok | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/meta/RUNTIME_SELECTION.md | Runtime selection guide | 2026 | GitHub | GitHub | repository | 2026-08-07T12:31:05 | |||||||||||||||
ale-0932 | Explore And Reuse | explore-and-reuse | Template | 🧾 | Future Directions agenda | FUTURE-DIRECTIONS.md | local_path | Turn 15 open problems into measurable studies, runtime projects, product pilots, and shared standards. | Turn 15 open problems into measurable studies, runtime projects, product pilots, and shared standards. | Turn 15 open problems into measurable studies, runtime projects, product pilots, and shared standards. | Turns open gaps into measurable research, infrastructure, and product directions. Turn 15 open problems into measurable studies, runtime projects, product pilots, and shared standards. | Use Future Directions agenda to reuse a concrete artifact or connect it to the wider ecosystem. | Repository file; inspect the linked schema, example, guide, or implementation. | medium | README.md | 1,711 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1711 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | enabling | repository-native | A | local_ok | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/FUTURE-DIRECTIONS.md | Future Directions agenda | 2026 | GitHub | GitHub | repository | 2026-08-07T12:31:05 | |||||||||||||||
ale-0933 | Shape What Comes Next | shape-what-comes-next | Template | 🧾 | Release notes | https://github.com/ChaoYue0307/awesome-loop-engineering/releases | external | github.com | Versioned changelog of new resources, patterns, and repository changes. | Versioned changelog of new resources, patterns, and repository changes. | Versioned changelog of new resources, patterns, and repository changes. | Turns open questions and operating lessons into visible next work. Versioned changelog of new resources, patterns, and repository changes. | Use Release notes to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (48 stars; 8 forks; CC0-1.0 license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,726 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1726 | 2026-07-15 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | enabling | reusable-artifact | A | ok | https://github.com/ChaoYue0307/awesome-loop-engineering/releases | Releases · ChaoYue0307/awesome-loop-engineering · GitHub | 🔁 Build reliable recurring AI-agent systems: 931 resources, 22 operational patterns, 22 loop contracts, 8 runtime starters, an interactive atlas, and a structured dataset. - Releases · ChaoYue0307/awesome-loop-engineering | 2026-06-09 | 2026 | GitHub Releases | GitHub | github-api | ChaoYue0307/awesome-loop-engineering | 48 | 8 | CC0-1.0 | 2026-06-09T16:17:27Z | 2026-08-07T03:40:09Z | 2026-08-07T12:31:05 | |||||
ale-0934 | Shape What Comes Next | shape-what-comes-next | Template | 🧾 | Roadmap | ROADMAP.md | local_path | Near-term work, pattern priorities, gallery goals, and open questions. | Near-term work, pattern priorities, gallery goals, and open questions. | Near-term work, pattern priorities, gallery goals, and open questions. | Turns open questions and operating lessons into visible next work. Near-term work, pattern priorities, gallery goals, and open questions. | Use Roadmap to reuse a concrete artifact or connect it to the wider ecosystem. | Repository file; inspect the linked schema, example, guide, or implementation. | medium | README.md | 1,727 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1727 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | objective | builder | cross-layer | enabling | repository-native | A | local_ok | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/ROADMAP.md | Roadmap | 2026 | GitHub | GitHub | repository | 2026-08-07T12:31:05 | |||||||||||||||
ale-0935 | Shape What Comes Next | shape-what-comes-next | Template | 🧾 | Launch article | posts/launch.md | local_path | Concise explanation of the concept, implementation kit, and evidence base. | Concise explanation of the concept, implementation kit, and evidence base. | Concise explanation of the concept, implementation kit, and evidence base. | Turns open questions and operating lessons into visible next work. Concise explanation of the concept, implementation kit, and evidence base. | Use Launch article to reuse a concrete artifact or connect it to the wider ecosystem. | Repository file; inspect the linked schema, example, guide, or implementation. | medium | README.md | 1,728 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1728 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | enabling | repository-native | A | local_ok | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/posts/launch.md | Launch article | 2026 | GitHub | GitHub | repository | 2026-08-07T12:31:05 | |||||||||||||||
ale-0936 | Shape What Comes Next | shape-what-comes-next | Template | 🧾 | Discussion guide | meta/DISCUSSIONS.md | local_path | Suggested discussion categories, starter prompts, and moderation standard. | Suggested discussion categories, starter prompts, and moderation standard. | Suggested discussion categories, starter prompts, and moderation standard. | The resource is directly reusable as a starting artifact. Suggested discussion categories, starter prompts, and moderation standard. | Use Discussion guide to reuse a concrete artifact or connect it to the wider ecosystem. | Repository file; inspect the linked schema, example, guide, or implementation. | medium | README.md | 1,729 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1729 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | enabling | repository-native | A | local_ok | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/meta/DISCUSSIONS.md | Discussion guide | 2026 | GitHub | GitHub | repository | 2026-08-07T12:31:05 | |||||||||||||||
ale-0937 | Shape What Comes Next | shape-what-comes-next | Pattern | 🔁 | Show your Loop Engineering patterns | https://github.com/ChaoYue0307/awesome-loop-engineering/discussions/2 | external | github.com | Community discussion for real or anonymized loop examples. | Community discussion for real or anonymized loop examples. | Community discussion for real or anonymized loop examples. | Turns open questions and operating lessons into visible next work. Community discussion for real or anonymized loop examples. | Use Show your Loop Engineering patterns to reuse a concrete artifact or connect it to the wider ecosystem. | Inspectable GitHub source (48 stars; 8 forks; CC0-1.0 license; updated 2026-08-07); popularity is context, not proof of reliability. | medium | README.md | 1,730 | https://github.com/ChaoYue0307/awesome-loop-engineering/blob/main/README.md#L1730 | Apply | apply | Reuse, adapt, and contribute concrete loop artifacts. | whole-loop | builder | cross-layer | enabling | operational-pattern | B | ok | https://github.com/ChaoYue0307/awesome-loop-engineering/discussions/2 | Show your Loop Engineering patterns · ChaoYue0307/awesome-loop-engineering · Discussion #2 · GitHub | Show your Loop Engineering patterns | 2026-06-09 | 2026 | GitHub Discussions | GitHub | github-api | ChaoYue0307/awesome-loop-engineering | 48 | 8 | CC0-1.0 | 2026-06-09T16:17:27Z | 2026-08-07T03:40:09Z | 2026-08-07T12:31:05 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.