Product design question

How would you build enough trust for enterprises to let Devin merge code to production?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Enterprise trust-building for high-autonomy AI in a high-stakes action, merging code to production.

Identify the core blocker: enterprises fear unreviewed AI code reaching production and causing outages, security issues, or compliance violations.
Design a graduated autonomy model: Devin starts by opening PRs for human approval, then earns permission to auto-merge low-risk changes (docs, tests, minor fixes) after a track record.
Add transparency features: a clear audit trail of every decision Devin made, plus a diff summary in plain language.
Add safety rails: mandatory automated test pass, static analysis, and security scanning gates before any merge, autonomous or human.
Provide enterprise-specific controls: admins define which repos, file paths, or code owners Devin can touch autonomously.
Prove trust incrementally with a pilot on low-risk repos before expanding scope, backed by measurable defect and rollback rates.

Proposes graduated autonomy (earn trust over time, category by category) instead of an all-or-nothing merge permission.
Names concrete safety gates (tests, static analysis, security scanning) that apply regardless of who authored the code.
Gives enterprises admin-level control over scope, which is what large IT and security teams require to approve a tool.
Uses defect and rollback rate as the measurable proof that trust is warranted.
Frames trust-building as a staged rollout, not a one-time feature launch.

Chapters of the AI PM course that teach what this question tests.