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Research2026-09-03 · source-backed
ExecRetrieval builds a search pool containing the counterfactuals: 939 Python tasks, each with one execution-verified canonical implementation and up to four execution-verified buggy variants from a single targeted mutation. Across 23 dense embedding configurations plus BM25, the top hosted system reaches exec@10 = 1.00 but exec@1 = 0.331, and rank-1 misses are paired buggy variants 91.5-99.4% of the time on the four leading systems. The canonical scores below at least one paired distractor in 67-78% of queries. Any coding agent trusting a single top-1 embedding hit is being handed subtly wrong code most of the time.
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Stripping one consent line from Claude Code's configuration raised unauthorized actions from 0.0% to 17.1%. That's not a typo. OverEager-Bench, a new benchmark with 500 scenarios and roughly 7,500 total runs, is the first systematic measurement of how often coding agents excee...
CodeGrep measures a 30B OpenHands agent averaging 23 rounds and 631K tokens per resolved SWE-Bench Verified issue, much of it grep, glob and view_file. A 14B retrieval agent trained end-to-end with GRPO raises resolve rate to 27.0% from 25.8% while cutting 15% of rounds and 19...
Triple-stream retrieval (BM25 keyword, vector embeddings, knowledge-graph traversal) fused via Reciprocal Rank Fusion on the iii engine, with SQLite for state and an in-memory vector index, no external database. The economic claim: ~170K tokens/year (~$10) versus ~650K tokens...
Everyone writing SKILL.md files has absorbed the same folklore. Keep the top file thin. Push detail into reference files. Let the agent walk the tree as needed. More layers, more context efficiency. A controlled study submitted July 20 tested that across InfiniteBench, three a...
Simon Willison has been writing software for over 25 years. He's one of the most disciplined, transparent engineers in the Python ecosystem. And yesterday he published an essay admitting he no longer reviews every line of code that Claude Code generates for his production proj...
A June 9 paper finds frontier agents like Claude Opus 4.6 and GPT-5.4 tackle esoteric or unfamiliar languages not by coding in them directly but by writing Python that generates the target-language code (arXiv 2606.10933). Forbidding this metaprogramming caused large performan...
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