To get an AI coding assistant to write a failing test before fixing a bug, describe the expected behavior, ask it to add one focused test without changing production code, and run that test yourself. Only after it fails for the right reason should the assistant implement the smallest fix. This red-green-refactor loop is a practical guardrail—not proof that a model is reliable or that a passing test guarantees a correct fix.
How to keep the test ahead of the fix
Use a short sequence with a clear handoff between describing the bug, writing the test, implementing the change, and cleaning up. The familiar TDD cycle is red, green, refactor: first establish the expected failure, then make the tests pass, then improve the code while keeping behavior covered. The Government Digital Service (GDS) recommends starting from desired behaviors, including the normal path, errors, and interactions with other components. Its guidance quotes Kent Beck: “For each desired change, make the change easy (warning: this may be hard), then make the easy change.”
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- Describe behavior, not a proposed implementation. State what happens now, what should happen instead, and how to recognize the difference. Include relevant project test conventions and the command used to run the tests. For example: “When a saved profile has no display name, the profile page should show the account email. It currently renders a blank heading. Add one test using the project’s existing profile-test conventions. Do not change production code.”
- Request one focused test only. Keep the first change to a single behavior that can be checked independently. Microsoft’s VS Code documentation demonstrates separating the red phase from implementation: the test-writing role is instructed not to write production code. Project-specific instructions help avoid tests that use the wrong framework patterns or overlook relevant scenarios.
- Run the test and inspect the failure. A useful red result demonstrates the bug: the test reaches the behavior under test and fails because the actual result differs from the expected result. A syntax error, broken fixture, missing dependency, or unrelated failure does not reproduce the bug. GDS advises checking that the test fails “in the way you expect.”
- Allow the smallest production change. Once the test establishes the behavior, ask for the minimal implementation change that makes it pass without changing the test. Run the new test and the existing relevant suite; VS Code’s documented workflow hands the red phase to a green phase that implements minimally and runs tests.
- Refactor after green. With behavior covered by passing tests, improve structure or remove duplication without changing the observed behavior. Then rerun the tests. GDS treats refactoring as a distinct phase after tests pass, and Martin Fowler notes that neglecting it is a common route to messy code fragments.
What makes a failing test meaningful
A test is valuable when it checks a behavior that matters outside the implementation detail, such as a returned value, visible state, or interaction contract. The xUnit.net guidance says tests should first capture intended behavior and that a behavioral change should start with a new test. If a test merely repeats the implementation’s internal choices, it may pass while the user-facing bug remains.
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- Confirm that test setup and fixtures are valid, and that the failure is not caused by a typo or unrelated environment issue.
- Keep the test aligned with the repository’s existing framework, naming, and setup conventions.
- Prefer one runnable increment over a broad suite of speculative cases; add further tests for other desired behaviors separately.
Do not treat a generated test file as evidence that the test was executed. Review the command output, and check that the assistant did not silently edit the test to make the implementation pass.
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How to separate the phases in an AI workflow
Put the phase boundary in the prompt or the tool workflow, not just in your intention. Microsoft’s VS Code documentation describes a red-green-refactor setup using separate custom agents and handoffs: one writes failing tests, another implements the change, and a later phase refactors. You can apply the same principle in a single chat by making each request conditional on the result of the previous phase.
- Ask for the test-only change and a brief explanation of the expected failure. Review the diff.
- Run the project’s test command yourself, or make execution visible in the assistant’s environment. Verify the failure is the one expected.
- Only then ask for the implementation change. Require the assistant to leave the test unchanged and report which tests it ran.
- Review both diffs and rerun relevant tests after any refactoring.
This separation makes it easier to spot when the assistant jumps ahead, changes the test instead of the code, or claims a test passed without running it. It does not guarantee compliance: the code and test still need review.
When to use a strict test-first loop
A failing test first is especially useful for a reproducible bug or a behavior that can be stated precisely and checked quickly. GDS describes TDD as effective for unit and component-integration tests, while noting that a tight cycle is a weaker fit for long feedback loops such as acceptance tests spanning multiple components that cannot be run locally before pushing.
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Use the feedback loop as the deciding factor. If a relevant test takes too long or cannot run in the local environment, look for a faster check that still gives useful feedback, such as a smaller unit test or a focused component test. IntelliJ IDEA’s documentation presents test-first development as a workflow developers can choose, including a Java and JUnit 5 example; it is not a rule that every change must follow the same sequence.
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What this workflow does—and does not—establish
The cited guidance explains how to structure TDD and AI-assisted phases; it does not report a controlled comparison of free and paid models, or establish that one model writes more reliable fixes. A red test shows that a particular test exposes a mismatch under the conditions in which it ran. A green suite shows that the checked tests pass; it cannot by itself prove the fix is correct for every untested case.
Use the test-first constraint to make the intended behavior explicit, keep the fix bounded, and get fast feedback. Do not use it as a substitute for reviewing whether the behavior is right, the test is meaningful, and the change is safe.
Quick Recap
Further reading
- Microsoft: Set up a test-driven development flow in VS Code
- Government Digital Service: Test-driven development (TDD) – The GDS Way
- JetBrains: Tutorial: Test-driven development
- Martin Fowler: Test Driven Development
- xUnit.net: Test Driven Development with xUnit.net
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