Cultivating Trust

The article argues that trust is the central challenge of AI-generated code, urging teams to hold engineers accountable for what they ship while granting them autonomy to use preferred methods. It recommends concrete practices—clear technology guidelines, deterministic tooling (typed languages, linters, CI/CD), small PRs, human-written tests, product alignment, prototype-style throwaway code, and outcome-focused pragmatism—to maintain code quality and prevent technical debt.