Why do tests matter differently for coding agents than for chatbots?
Instruction: Explain why tests play a special role in coding-agent workflows.
Updated
Example Answer
Tests give a coding agent feedback while it changes an executable system. For a retry bug, I'd first reproduce a duplicate record, then add a regression that checks the stored outcome, and run it against the proposed fix. A failure narrows the next investigation; a pass is evidence for that case.
Tests do not establish every requirement. A mocked request may pass while the real database still permits a race, and an agent could make a test pass by weakening the assertion. I'd inspect test changes, check relevant integration behavior, and separate environment failures from behavioral failures. Chatbot evaluations can also be iterative; the distinction is the coding agent's ability to modify and execute the implementation under test.
Why this works
Avoids an absolute chatbot contrast and ties test feedback to a concrete invariant and failure path.
Practice follow-up
How would you tell a legitimate regression-test update from a weakened test?
Your preparation path
Work through these questions in order. Read the answer aloud, then explain it in your own words.
1. Start with the foundations
Build the vocabulary and explain the core decisions.
2. Apply it to a real workflow
Practice diagnosis, validation, and everyday tradeoffs.
3. Prepare for senior discussions
Explain failure boundaries, recovery, and production choices.
- A coding agent can modify infrastructure, app code, and data access layers in one task. How do you constrain it? Member answer
- Two coding agents change an API and its client in parallel. How would you integrate their work safely? Member answer
- A coding-agent hook runs before the repository trust prompt. What is wrong with that design? Member answer
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