Outcome#
You can bound an agent task, control context and commands, review the diff, verify the result personally, and reject a plausible but inferior suggestion.
Concept#
An agent can read files, edit code, execute commands, and publish changes. It is not merely a model or chatbot, and fluent output does not transfer responsibility away from the account owner.
Worked Example#
The fixture is corrected, the canary remains unchanged, the bounded verifier passes, and the submission records human review rather than a transcript.
A correct example uses these decisions:
- What is a safe agent task? One bounded outcome with explicit files, constraints, and verification.
- Who verifies the final diff and tests? You do, even if the agent reports success.
Common Trap#
Granting a broad task, sharing protected data, or accepting a claimed test result without checking the diff and rerunning it.
If Blocked#
Start a new bounded agent thread if context has become inconsistent. Return to the clean baseline when edits spread outside the fixture. Use the manual versus agent lab for recovery.
Useful references:
Understand Before Accepting AI Output#
You must understand the changed behavior, tests, files, commands, data sent, service used, and likely cost. Passing output without this explanation is not a pass.