Building Interactive Agentic Code Reviews in 20 Minutes
Blog post from Nx
Interactive agentic code reviews are presented as a practical automation workflow that can improve review throughput without replacing the human judgment needed to understand changes and assess their architectural implications. The proposed process connects an issue tracker, version control, agent session histories, temporary workspaces, orchestration tools, adversarial automated reviews, and human review, allowing reviewers to identify relevant work, prepare repositories and agent context, inspect automated findings, collaborate with agents, and submit feedback. Using GitHub, Linear, and Polygraph as an example, a roughly 600-line script finds assigned review issues, links them to implementation sessions, runs adversarial analysis, and stores summaries for a local review interface. Rather than reviewing pull requests in isolation, the approach emphasizes reviewing the broader decisions and context captured in agent sessions, enabling reviewers to request small fixes, run tests, validate changes directly, and work from pre-reviewed “warm” sessions. The author argues that scheduled background processing makes reviews more efficient and that conventional PR-based review tools provide a narrower, less contextual version of adversarial review.
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