OPEN LINK ↗
// 4h agoTUTORIAL
AI Coding Improves With Slower Reviews
Nolan Lawson argues that AI coding works best when you treat model output as a first draft and use multiple agents to review, challenge, and validate it before shipping. He says this slower workflow surfaces more bugs, improves tests and docs, and deepens understanding of the codebase even if it does not maximize raw throughput.
// ANALYSIS
Hot take: the strongest AI coding workflow is not “ship faster,” it’s “force the machine to make your review process ruthless.”
- –Treat AI output as a first draft, not a mergeable artifact.
- –Use multiple models to reduce blind spots and hallucinations in review.
- –Let the agent find bugs, but keep humans responsible for prioritization and final judgment.
- –The value is code quality, documentation, and system understanding, not raw throughput.
- –This is especially useful for legacy code, subtle edge cases, and PRs that span multiple domains.
// TAGS
aicoding-agentscode-reviewllmsoftware-engineeringai-coding
DISCOVERED
4h ago
2026-05-26
PUBLISHED
13h ago
2026-05-25
RELEVANCE
8/ 10
AUTHOR
signa11