Code Review
A quality control mechanism in software engineering in which developers examine a change for correctness, readability, security, and design consistency before it is merged into the main branch, and decide whether to approve it or return it for revision. It serves both as technical gatekeeping and as a means of knowledge sharing and risk control.
Core Facts
Timeline (last 90 days)
A common practice in engineering is to solidify the LLM's generated results, exporting them as static files and including them in version control and code review, rather than regenerating them on every startup.
Development teams can take concrete actions to embody "there are people behind the software," including: recording the background of key decisions and the decision-makers in documentation, establishing sustainable maintenance models for open-source projects, focusing on intent rather than merely correctness in code review, and maintaining empathy toward user feedback.
The study found that end-to-end delivered software did not grow proportionally with code output, code review is still done manually, and change requests initiated by reviewers grew almost linearly as agent adoption deepened.
The Claude Code team believes that "whether a human has read the code" is an imprecise proxy metric, and the real question that should be asked is what could go wrong with this change and which kind of check (automated or human) is best suited to catch it.
In human teams, code review, architecture decision records (ADRs) and a shared mental model within the team together suppress architecture drift.
AI coding assistants have entered development workflows at scale, dramatically increasing code output speed and causing continuous integration (CI) systems to become the slowest link in the delivery chain.
Beyond finding bugs, code review is more importantly about controlling the introduction of complexity and preventing the divergence of team mental models.
Research shows that code review can reduce defect rates by 60%–90%.
All Facts (8)
AI coding assistants have entered development workflows at scale, dramatically increasing code output speed and causing continuous integration (CI) systems to become the slowest link in the delivery chain.
65%UnverifiedA common practice in engineering is to solidify the LLM's generated results, exporting them as static files and including them in version control and code review, rather than regenerating them on every startup.
50%UnverifiedDevelopment teams can take concrete actions to embody "there are people behind the software," including: recording the background of key decisions and the decision-makers in documentation, establishing sustainable maintenance models for open-source projects, focusing on intent rather than merely correctness in code review, and maintaining empathy toward user feedback.
50%UnverifiedThe study found that end-to-end delivered software did not grow proportionally with code output, code review is still done manually, and change requests initiated by reviewers grew almost linearly as agent adoption deepened.
50%UnverifiedThe Claude Code team believes that "whether a human has read the code" is an imprecise proxy metric, and the real question that should be asked is what could go wrong with this change and which kind of check (automated or human) is best suited to catch it.
50%UnverifiedIn human teams, code review, architecture decision records (ADRs) and a shared mental model within the team together suppress architecture drift.
50%UnverifiedBeyond finding bugs, code review is more importantly about controlling the introduction of complexity and preventing the divergence of team mental models.
50%UnverifiedResearch shows that code review can reduce defect rates by 60%–90%.
50%