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How can test-driven development act as guardrails when you delegate coding to an AI agent?

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Test-driven development gives an agent an executable contract and a short feedback loop, making delegated work narrower and easier to inspect.

  1. Review a test that expresses one required behavior and confirm it fails for the right reason.
  2. Ask for the smallest implementation that makes the test pass.
  3. Protect tests from unapproved edits so the agent cannot weaken the contract.
  4. Add boundaries, invalid inputs, and failure paths, then rerun focused checks.
  5. Inspect the implementation and repeat with the next behavior.

A green suite proves only the specified cases, so human review and broader verification still matter.

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Guided practice for AI in Engineering Teams One question at a time. Answer out loud, get graded, see what you missed.
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Who does what when an AI agent writes the code
You
AI agent
Test suite
review and run one test
fails: behavior missing
protect test from edits
smallest code to pass
code written, test passes
add edge-case tests
rerun focused tests
try to edit test: blocked
code fixed, tests pass
inspect, then next behavior
1step

You check that the test fails for the right reason, not because of a typo.

1 / 10

You review and protect the tests, and the agent only writes code. A green suite still proves only the cases you tested.

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Likely follow-ups

  • Why does it matter that the test fails for the right reason before the agent writes any code? A test that fails on a typo or missing import, or already passes, proves nothing. The failure should point at the missing behavior.
  • The agent keeps changing tests to get to green. How do you prevent that in practice? Name a real control, like read-only test files, CI that flags test diffs, or approval for test edits, and why a prompt instruction alone is not enough.
  • What goes wrong if you let the agent write the tests as well as the implementation? The tests can copy the code's bugs as expected values and pass without checking intent. A human should own or review what counts as correct.
  • How can you tell whether the tests would catch a wrong implementation? Mention mutation testing: inject small faults and see if a test fails. Also check that assertions are specific, not just 'does not throw'.
  • The suite is green but you still don't trust the change. What else do you check? Tests prove only the cases written. Read the diff, look for untested paths, run broader integration and security checks, and consider property-based tests.

What you can say

  1. TDD gives the agent an executable contract and a short feedback loop, so each piece of delegated work stays narrow and easy to check.
  2. I start by reviewing a test for one required behavior and running it to confirm it fails for the right reason, not because of a typo or a missing import.
  3. Then I ask the agent for the smallest implementation that makes it pass. It can't edit the tests without my approval, so it can't weaken the contract.
  4. Once it passes, I add boundaries, invalid inputs and failure paths, rerun the focused checks, read the implementation, and move on to the next behavior.
  5. The limit is that a green suite only proves the cases I specified, so I still review the code and run broader verification before I trust it.

Weak answers to avoid

  • Lets the agent write both tests and code Then the tests check what the code does, not what you need. Say you review each test first and confirm it fails for the right reason.
  • Treats a green suite as proof of correctness Tests prove only the cases written. A strong answer adds code review, edge and failure cases, and verification beyond the suite.
  • Ignores the agent editing tests to pass An agent can weaken or delete assertions to reach green. Say how you block unapproved test edits and check test diffs in review.
  • Recites TDD with no link to agents Reciting red-green-refactor misses the question. Tie each step to delegation: small scope per test, fast feedback for the agent, easy human inspection.
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