Problem
Standard AI-assisted coding (single model, single pass) produced inconsistent quality and didn’t scale trust across a team — no structured way to check business intent against technical risk before code shipped.
Action
Designed and ran a multi-agent development workflow across Claude, Codex, and Gemini with explicit roles: a context-extraction agent, parallel “Challenger” (business-intent) and “Risk” (technical-risk) agents, and a red-green-refactor cycle gated by human approval and acceptance-criteria evaluations.
Result
Time to market dropped from months to weeks on affected work, with fewer defects escaping to QA and more consistent documentation as a byproduct of the structured process. This work changed how the broader team operated around AI usage (details beyond this are NDA-scoped).