Cultivating Trust

Trust in AI-generated code depends on multiple layers—from the initial ticket and engineer oversight to testing, deployment, and incident response—and building a culture of engineering accountability is essential. Organizations should establish clear coding guidelines, use deterministic tooling like linters and typed languages to maintain quality, enforce small pull requests for reviewability, and require engineers to write tests by hand while holding them accountable for the code they ship. This approach balances the speed advantages of AI coding agents with the need to prevent quality degradation and technical debt.