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Research2026-09-01 · source-backed
FlowCheck lets someone specify user-visible information flows through the application interface, then compiles those constraints into deterministic CodeQL analyses (arXiv 2608.28880). Across four applications generated with Claude Code it flagged all 30 injected violations with no false positives, while Claude Opus 4.7, DeepSeek V3 and Gemini Pro prompted to find bugs in the same code all fell well short. State intent in interface terms and check it deterministically. Asking a model to review code it just wrote remains a weak control.
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Everyone spent yesterday arguing about benchmark numbers. Tencent quietly published data suggesting the numbers belong to your infrastructure, not the model. The WorkBuddy Bench leaderboard reports every model under two different agent harnesses — CodeBuddy Code and Claude Cod...
Alibaba released Qwen3.6-27B on April 22. Dense architecture. Open weights. 77.2% on SWE-bench Verified, within 3.7 points of Claude Opus 4.6. On SkillsBench, it scores 48.2% versus its own 397B MoE predecessor's 30.0%. That's a 77% improvement with 14.8x fewer parameters. Let...
Four stories about things going wrong. Here's one about something working, with actual numbers attached. In an August 7 disclosure covered by TechCrunch, Airbnb said AI now writes 60% of its new code, that concept-to-launch time on key initiatives has dropped by as much as 60%...
If you have a CLAUDE.md, you're in scope. Today. arXiv 2607.14611 (cs.CR, filed July 16) evaluates prompt injection planted in the persistent memory files that agentic coding systems write and re-read across sessions. The researchers tested both Anthropic's Claude Code and Ope...
$3,054 against $38,370. Same benchmark, better score. Praxist (arXiv 2608.25955, submitted August 26) replaces per-attempt agent memory with a typed evidence graph of findings, plus lane-structured frontiers and agendas, so later attempts inherit validated mechanisms rather th...
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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