AI & Technical question

Replit Agent can auto-deploy apps. How would you prevent users from shipping insecure code?

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

AI and technical product thinking on safety guardrails for a feature that removes the usual human deployment checkpoint.

Identify the risk: auto-deploy skips the manual review step where an experienced developer might catch exposed secrets or open endpoints.
Add pre-deploy automated checks: secret scanning, dependency vulnerability checks, and basic misconfiguration checks like open database ports or missing auth on admin routes.
Add a plain-language pre-deploy summary for non-technical users, flagging any risk found in terms they can understand, not a raw security report.
Default to safer configurations, such as requiring authentication scaffolding by default for any endpoint handling user data, rather than opt-in security.
Add a kill switch and easy rollback so a bad deploy can be pulled back quickly if an issue surfaces after launch.
Measure success by tracking the rate of security incidents per deployed app and how often the pre-deploy checks catch real issues.

Recognizes that the target user (non-technical vibe coder) cannot self-assess security risk, so the guardrail must be automatic, not advisory.
Proposes secure-by-default scaffolding rather than relying on users to opt into security features they do not understand.
Balances safety with speed by using automated checks instead of a manual review bottleneck, preserving the auto-deploy value proposition.
Adds a rollback mechanism as a safety net for issues that slip through pre-deploy checks.
Defines a measurable incident rate to track whether the guardrails are actually working over time.

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