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Public story · 2026-03-14 · source-backed
Researchers systematically measured what happens when adversarial instructions are embedded in project documentation that high-privilege agents are directed to read. The result: agents with terminal, filesystem, and network access blindly execute the instructions and exfiltrate data. This isn't a jailbreak — it's the agent doing exactly what it was designed to do (follow instructions) on adversarial input. Builders shipping coding agents or CI/CD agents should audit all documentation sources treated as trusted input.
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The PlayCoder benchmark is the cold shower the vibe coding movement needed. Researchers tested 10 state-of-the-art code LLMs on generating GUI applications across six categories. The models achieved high compilation rates. The code built and ran. But when they measured whether...
Researchers analyzed 3,691 patches from AI coding agents. Between 20% and 40% contained unnecessary refactoring mixed into bug fixes. This isn't a prompting failure. It's a training data problem, and it's baked into the models. A paper on arXiv examined patches from Multi-SWE-...
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Researchers analyzed 61,837 GitHub Actions runs from 2,355 repos triggered by PRs from Claude, Devin, Cursor, Copilot, and Codex. Substantial differences in pass rates across bots. This is the first empirical data on how AI-generated code actually performs under real CI/CD con...
Researchers deployed 150 autonomous Claude Code agents to independently test six financial market hypotheses using identical NYSE TAQ data. Substantial agent-to-agent variation — different model families exhibit stable "empirical styles" where Sonnet 4.6 and Opus 4.6 make syst...
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