Section 192 · Chapter 9, Generated Code Changes the Job
Testing AI Review Loops with Coding Agents
A coding agent should not be the only judge of its own work. Use AI-assisted review loops to add fast, skeptical, evidence-oriented checking close to the development workflow.
review loops coding agents
What to do
- Use AI-assisted review loops to add fast, skeptical, evidence-oriented checking close to the development workflow.
- Define when they run, what targets they cover, which findings block release, how reports are stored, how fixes are verified, and where human review is required.
- Version the review prompt, save the evidence, and periodically compare the reviewer against human findings so the loop itself does not quietly drift.
Evidence to preserve
- Preserve the inputs, versions, configurations, raw outcomes, and results for review loops coding agents needed to reproduce work on Testing AI Review Loops with Coding Agents.
- Report results for review loops coding agents by relevant slice, separate blocker failures from averages, state uncertainty and blind spots, and connect the result to a release decision.
Expert note
The deeper move is to make AI-assisted review loops part of the development contract. Define when they run, what targets they cover, which findings block release, how reports are stored, how fixes are verified, and where human review is required.
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Cite this page
Jason Arbon. "Testing AI Review Loops with Coding Agents." Testing AI Knowledge Edition, section 192.
https://jarbon.ai/testing-ai/knowledge/ch192-review-loops-coding-agents.html