Sync from GitHub 3114239

README.md

@@ -232,7 +232,6 @@ Direct resources about the new AI/coding-agent meaning of Loop Engineering.
 - 📝 **Blog** [Loop Engineering](https://addyo.substack.com/p/loop-engineering) - Substack version of the same essay; useful for the original discussion trail and quotations from Peter Steinberger and Boris Cherny.
 - 📝 **Blog** [Loop Engineering](https://cobusgreyling.substack.com/p/loop-engineering) - Concise explanation of the shift from prompting agents to designing loops that discover work, delegate, verify, persist, and continue.
 - 📝 **Blog** [Loop Engineering: The Guide for AI Agents](https://lushbinary.com/blog/loop-engineering-ai-coding-agents-guide/) - Practical guide that breaks the pattern into automations, worktrees, skills, connectors, subagents, and state.
-- 🔁 **Pattern** [Codex Loops: What Boris Cherny Gets Right About Managing Agent Work](https://www.developersdigest.tech/blog/codex-loops-boris-cherny-agent-routines) - Engineering note on recurring agent loops for PR babysitting, CI repair, deploy verification, and feedback clustering.
 - 📝 **Blog** [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/) - Coverage of Boris Cherny's "my job is to write loops" workflow.
 - 📝 **Blog** [My Lord! AI Programming Undergoes Another Major Shift](https://eu.36kr.com/en/p/3844224911346184) - Broad coverage of the Boris Cherny and Peter Steinberger discussion, including the distinction between cold-start scripts and persistent agent loops.
 - 📝 **Blog** [Peter Steinberger on designing loops](https://x.com/steipete/status/2063697162748260627) - The June 2026 post - "you shouldn't be prompting coding agents anymore, you should be designing loops that prompt your agents" - that catalyzed the current discussion.
@@ -532,6 +531,7 @@ This section focuses on durable loop state and cross-run context. For context-wi
 - 📄 **Paper** [SaaSBench: Coding Agents in Long-Horizon Enterprise SaaS Engineering](https://arxiv.org/abs/2605.17526) - Benchmark for agents on multi-dependency, interactive enterprise tasks, with automated evaluation that probes where long-horizon loops break down.
 - 📄 **Paper** [RoadmapBench: Evaluating Long-Horizon Agentic Software Development Across Version Upgrades](https://arxiv.org/abs/2605.15846) - 115 real version-upgrade tasks across 17 repositories requiring multi-file changes (median ~3,700 lines), stressing how far agent loops sustain coherent, large-scale work.
 - 📄 **Paper** [RefactorBench: Evaluating Stateful Reasoning in Language Agents Through Code](https://arxiv.org/abs/2503.07832) - Multi-file refactoring tasks that require tracking and carrying state across many steps, isolating the durable-state weakness that breaks long agent loops.
+- 📄 **Paper** [RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents](https://arxiv.org/abs/2606.22678) - Scores planning, verification coverage, recovery, abstention, and atomic transitions (not just whether code passes), measuring the loop discipline that separates reliable agents from reckless trial-and-error.
 - 📄 **Paper** [SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks](https://arxiv.org/abs/2603.24755) - Quantifies structural erosion and verbosity creep across iteration checkpoints in native harnesses like Claude Code and Codex, evidence for why loops need verification and budgets.
 - 📄 **Paper** [LongCLI-Bench: A Preliminary Benchmark for Long-horizon Agentic Programming in Command-Line Interfaces](https://arxiv.org/abs/2602.14337) - Long-horizon CLI tasks where most runs stall below 30% completion, mapping where unattended loops break down.