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Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →When an AI coding agent says “The test was wrong” and proposes rewriting it, don’t accept the change on that sentence alone. First identify what the test was meant to prove; then check whether it actually exercised that behavior, whether the implementation is correct, and what the revised test now asserts. A failing test can mean the code is wrong, the test is wrong, or both.
What does “the test was wrong” actually establish?
Only that the agent believes the test needs changing. It does not establish that the test was defective, that the implementation is correct, or that the replacement test will catch the intended bug. A test is initially just generated text. Running it adds evidence about its behavior, but a passing result still does not prove that it checks the right behavior.
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Gil Zilberfeld’s article describes several distinct points where an agent-assisted change can go wrong: implementing code, creating a test, checking the test against the code, running it, and evaluating whether the test serves its purpose. Those steps are related, but success at one does not certify the next.
How to review a proposed test rewrite
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Restate the test’s intended claim
In plain language, say what behavior the test is supposed to demonstrate or prevent. If that claim is unclear, the test cannot be meaningfully reviewed yet.
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Check whether the old test reached that behavior
Inspect the setup, execution path, and assertions. A test can fail—or pass—without exercising the condition it was intended to cover. Zilberfeld gives a race-condition example in which the test meant to recreate a race did not run the race at all. That is an anecdote, not evidence about how often such failures occur.
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Assess the implementation separately
Ask whether the code satisfies the stated behavior independently of the test’s result. The failure could expose a code defect, an incorrect test expectation, or a mismatch between the test and the behavior under examination.
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Inspect what the replacement test changes
Compare the old and new setup, path, and assertions. Confirm that the rewritten test now exercises the target behavior and would fail if that behavior regressed. A changed test that merely makes the current implementation pass has not, by itself, demonstrated correctness.
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Run the relevant tests and review the resulting changes
Execution tells you how the tests behave in that run; it does not settle whether they test the right thing. Review the code and test diffs as separate claims, along with the test output and any relevant logs.
Why a green run is limited evidence
Zilberfeld characterizes coding-agent reasoning and evaluation as opaque and non-deterministic. In that setting, a green test run is useful evidence that the executed tests passed, but it is not proof that the intended behavior was tested or that the fix is correct. The distinction matters most when an agent changes both the implementation and the test that is supposed to verify it.
The article is not an empirical study and provides no independently attributable failure rate. Zilberfeld mentions that this happened seven times in a single build in one personal example; that number should not be read as a general statistic or prediction.
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Keep agent changes small enough to inspect
Break work into smaller, manageable tasks so each code change, test change, and log is easier to examine. Smaller steps do not guarantee correctness, but they make it easier to see which claim is being tested and what changed when a result shifts. Zilberfeld calls reviewability “a delivery capability.”
Quick wins for a faster PC:
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