Agentic AI and Code Reviews: Toward a Pattern Language for Code Reviews in the Age of Agentic AI
A collective article by seven authors (**Zach Davis**, **Michelle Gill**, **Elisabeth Hendrickson**, **Angie Jones**, **Sha Ma**, **Randy Shoup**, **James Wickett**), published in the *Enterprise Technology Leadership Journal* by **IT Revolution** (fall 2026, vol. 3, no. 2), under a CC BY-NC-SA license. About **7,500 words**, titled *« Toward a Pattern Language for Code Reviews in the Age of Agentic AI »*. **(A)** Framing: code review is defined as an examination by a non-author entity leading to an action; empirical studies (Microsoft 2013, Mäntylä 2009, Beller 2014) show that its value lies mainly in maintainability and knowledge sharing, less in functional defect detection. **(B)** Three conditions for taking the human out of the critical path: maximal deterministic validation, **risk-graded** review, a **durable trace** of every agent decision; *« no human in the loop »* is a configuration choice, not a default. **(C)** Nine composable patterns, presented as a toolbox rather than a maturity ladder: small changes, Shift Left, design for verification, deterministic engineering practices, context engineering, continuous quality loop, adversarial LLM review, multi-agent reviews, specification-driven development. **(D)** Three case studies: **Block**, **Cloudflare** (131,246 reviews across 48,095 PRs in one month, 1.2 findings per review), **DryRun Security**. Extends the corpus's notes on context engineering and agent-assisted code review.
Zach Davis (LaunchDarkly) · Michelle Gill (Engineered by AI) · Elisabeth Hendrickson (Curious Duck) · Angie Jones (Agentic AI Foundation) · Sha Ma (Topogy) · Randy Shoup (CircleCI) · James Wickett (DryRun Security) ; article collectif · IT Revolution.