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A customer wants AI coding agents working in their codebase. How do you assess whether it is ready, and what do you fix first?

The instinct is to grade the codebase. Grade the feedback loop instead: a repo with no docs and a 90-second test command is friendlier to an agent than a beautifully documented one whose suite takes 40 minutes and flakes 8% of the time, and the arithmetic on that second number is worse than it looks.

Updated Sep 2026 · Grounded in real Forward Deployed Engineer interview loops and written to a senior-engineer editorial bar.

The instinct is to grade the codebase. Grade the feedback loop instead: a repo with no docs and a 90-second test command is friendlier to an agent than a beautifully documented one whose suite takes 40 minutes and flakes 8% of the time, and the arithmetic on that second number is worse than it looks.

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FEDITOR'S NOTE

Most candidates answer this as a code-quality question and produce a checklist that would improve any repo: more tests, better docs, cleaner modules. That answer is unfalsifiable and forgettable. The two things being scored are whether you can say what an agent needs that a human does not, and whether you audit by running something rather than by reading. A candidate who says out loud that flaky tests are worse than absent tests, and can explain why the asymmetry exists for an agent and not for a person, has usually done this work.

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