8 min
The test harness that detects the agent and lies to it
KillSwitch's interpreter walks the process tree, works out it is talking to a coding agent, then returns a fake error about drawing a pelican instead of the real parse failure.
Category · 8 of 40 articles
Explainers
What the category actually is, in terms an engineer can argue with.
5 min
The best AI code review tool is the one the agent built to review with
Trail of Bits spent six months having agents build an LSP, decompiler, static analyzer, and Lean proof model before the Miden review even started. That is where the leverage landed.
5 min
Once You Can Measure It, You Can Make It Faster: An Agentic Loop in Action
Anthropic made claude.ai 3x faster in two weeks by putting a model inside a measure-build-steer loop. An eval-grounded look at what the sprint proves about agentic workflows.
2 min
AI code review reads the patch, not the execution
When AI writes 30% of your lines, patch-text review hits a ceiling. The fix is an execution layer, not a bigger reviewer.
2 min
Reproducing zizmor's flag on the Snowflake injection
I ran zizmor 1.29.0 against the exact Snowflake GitHub Actions workflow. A deterministic static rule flagged the injection at High confidence while AI review cleared it.
11 min
AI Code Review Statistics (2026): Sourced Data
AI code review statistics for 2026: adoption, trust, review turnaround, AI code volume, and bug-catch benchmarks — every stat linked to a primary source.
12 min
AI Code Review vs Static Analysis: 2026 Guide
AI code review vs static analysis compared: determinism vs reasoning, false positives, SAST coverage, cost, and why mature teams run both.
12 min
What Is AI Code Review? How It Works (2026)
AI code review explained: how LLM reviewers work, what they catch and miss, how they differ from linters and static analysis, plus sourced adoption data.