#code-review
Wiki 17
- Code Review as a Principal-Agent Problem Why review-then-commit relied on cheaply-inferable effort signals from contributors; how agents collapse that signal and what it means for review processes
- Code review throughput limits The empirical caps on effective code review (~400 LOC/h, ~1h sessions, no parallelism) and why they put a hard ceiling on "just review the AI's output"
- code-review-knowledge-transfer Empirical finding that <15% of code review comments are about bugs — review's primary value is knowledge transfer, awareness, and alternative solutions, not defect detection
- Cross-model code review Who should check an LLM's code, and why the model that wrote it reviews poorly, why the reviewer must be able to solve the task, and when a weaker writer pays
- Leverage Code Review for Sustainable AI Coding Development CACM news piece where practitioners say review of AI code shifts from end gate to continuous risk check aimed at assumptions, trust boundaries, evidence
- Maybe We Shouldn't Be Reviewing All This Code Rachel Laycock on moving review's jobs earlier into pairing, design sessions and automation, keeping human code review for the exceptions
- pair-programming Two developers working the same code at the same time — peer-reviewed evidence of comparable quality at equivalent cost to solo+review, strongest benefit on complex tasks and for junior developers
- Reviewing AI Code Thomas Depierre's empirical case that "just review the AI's code like an intern's" collapses against what research says about code-review throughput and reviewer overconfidence
- ship-show-ask Wilsenach's three-way classification of changes — Ship (merge directly), Show (merge then review), Ask (open PR and wait) — that reduces the proportion of work needing blocking review
- Stacked PRs Pipelining the code-review process by submitting sequential dependent PRs simultaneously; the workflow that exposes git's missing successor-commit primitive
- Stop Using Pull Requests Laforgia's evidence synthesis against PRs as default workflow — origin-story category error, <15% of comments are about bugs, 86-99% of lead time is waiting, T*D as the alternative
- SWR-Bench: LLM Code Review Comment Generation on Real Pull Requests 1,000 real PRs with full repo context; the best LLM review setups reach about 20% F1, dragged down by false positives, and pooling several reviews helps
- The Agent Principal-Agent Problem Crawshaw on how agents broke code review by collapsing the effort signal between contributor and reviewer; the small-team escape and the big-co dead end
- The Short Leash AI Coding Method Read every diff in the permission prompt and deny freely — Slepak's method for critical software
- What to look for in a code review Google's reviewer checklist, ordered design first, and what it assumes about how review works
- Why Software Factories Fail Dex Horthy on why lights-off factories fail — RL rewards passing tests, never good design
- Your AI Agent Doesn't Understand Code, It Guesses Confidently Vendor post on CodeSlicer, an impact graph that separates proved call edges from plausible guesses