Topic · 10 articles
Postgres 19 slipped past its usual release window because LLM-found bug reports outran the people who review and commit fixes. Here is how to count that gap in your own repo, using commit trailers.
A 471-comment thread argued about AI productivity using a metric that counts commits, reviews and issues as the same unit. Here are the four numbers that actually decompose, measured on vscode and node.
Copilot code review ships a documented excluded-file list. Every AI reviewer has a coverage boundary, and it changes what your eval measures.
A reviewer that loads your rules file is not a reviewer that enforces it. Two instruction-following studies give you three tests that tell the two apart.
Teams reviewing a growing volume of AI-generated code need to score what a reviewer fails to notice, not only what it flags. A measurable protocol.
A hands-on look at what "free" really means across AI code review tools — metered credits, trials, BYO-LLM, and how to evaluate them.
Atlassian says Rovo cut PR cycle time 45%. The number is real but self-attested. Here's how to measure whether AI actually reduces your review time.
Eval-grounded comparison of AI code review tools for large teams with many repositories: cross-repo context, verification, permission boundary.
The volume of AI-generated code is rising faster than review capacity. The fix starts in evaluation design: don't let the model that wrote the code also judge it.
AI is producing more code than teams can review. First-party data on why the old loop breaks (Salesforce, DORA) and what actually scales.