Code Review Workflow
definition
The process of reviewing, validating, and approving AI-generated code before it merges into the main codebase, arguably the most important quality gate in any agentic coding workflow. Reviewing agent-generated code requires a different mental model than reviewing human code: agents produce syntactically correct code that may be architecturally wrong, subtly misaligned with project conventions, or implementing the wrong abstraction entirely.
The process of reviewing, validating, and approving AI-generated code before it merges into the main codebase, arguably the most important quality gate in any agentic coding workflow. Reviewing agent-generated code requires a different mental model than reviewing human code: agents produce syntactically correct code that may be architecturally wrong, subtly misaligned with project conventions, or implementing the wrong abstraction entirely. Effective AI code review focuses on intent alignment (did the agent build what was asked for?), architectural consistency (does it follow existing patterns?), and edge case coverage (are error paths handled?) rather than the syntax and formatting checks that agents already excel at. The highest-leverage practice is reviewing the diff, not the final code — understanding what the agent changed and why reveals mistakes that reading the output alone would miss. This concept connects to code review agents for automating the first pass, agentic git workflow for the version control practices that enable clean diffs, and spec-driven development for providing clear specifications that make reviews more focused.