AI can produce code that looks polished, compiles, and still violates a requirement or introduces a security flaw. The practical safeguard is a review gate: define the behavior first, keep the change focused, verify it independently, inspect the tests as carefully as the implementation, and require a responsible human to approve the merge. No prompt, agent confidence, or green test suite proves correctness on its own.
Define the expected behavior before asking for code
Start with the requirement, not an implementation idea. Write down what should happen, what must remain unchanged, which interfaces are affected, and how the change should behave in important failure cases. This contract gives you a standard for judging both the generated code and its tests.
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Make the request concrete enough to check. For example, specify valid and invalid inputs, boundary conditions, expected errors, compatibility requirements, and any security constraints relevant to the change. If the requirement is ambiguous, resolve that ambiguity before implementation rather than letting the model silently choose a behavior.
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Keep the generated change small and inspectable
Ask for a focused modification that addresses the defined contract. A narrow diff is easier to understand, test, and reverse than a broad refactor mixed with the requested fix. Review the full diff, including configuration, dependency, and test changes—not only the main source file.
- Check whether the change touches interfaces or behavior outside the stated scope.
- Review new dependencies for necessity and suitability before adding them.
- Read generated commands before running them, especially commands that write, move, or delete files.
- Look for unrelated formatting or refactoring that makes it harder to identify the meaningful change.
Generated output can be syntactically valid without being accurate, complete, secure, or aligned with the requirement. GitHub advises users of Copilot agents to review and test the content before merging; its guidance for inline suggestions similarly warns that suggestions may be insecure and should be validated. See GitHub Copilot Agents: Responsible use and GitHub Copilot inline suggestions: Responsible use.
Verify the requirement independently
Run the relevant existing checks and add tests that correspond to the contract. Include ordinary success cases, but also consider malformed inputs, boundaries, failure handling, and regressions where those apply. A test should establish that the intended behavior holds, not merely that the implementation behaves consistently with itself.
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Do not treat tests written by the same agent that produced the code as independent proof. OWASP puts the problem plainly: “A passing test suite generated by the same agent that produced the code provides no independent assurance.” A useful safeguard is to derive checks from the requirement itself, then review whether each test actually exercises the behavior and would fail if that behavior were broken.
Choose verification methods for the risks involved
There is no universally best bundle of checks. Select methods based on the likely failure modes, the change’s scope, the independence of the evidence, and the project’s risk. NIST’s Guidelines on Minimum Standards for Developer Verification of Software, published October 6, 2021, describes techniques including automated testing, static scanning, threat modeling, fuzzing, historical tests, and review of included code.
| Check | Useful for | Evidence and limits |
|---|---|---|
| Requirement-based automated tests | Expected behavior, boundaries, malformed inputs, and regressions within the tested scope | Reproducible results for the cases covered; they do not establish behavior for untested cases |
| Static analysis and secret detection | Patterns of potential defects, insecure constructs, and accidentally exposed secrets | Tool findings to investigate; a clean scan does not prove the code is safe |
| Threat modeling | Security assumptions, trust boundaries, and plausible abuse cases | Documented analysis of risks and mitigations; quality depends on scope and reviewer understanding |
| Historical regression tests | Known bugs or previously observed failures | Evidence that specified past cases remain covered; new failure modes may need new tests |
| Fuzzing and relevant application scanning | Unexpected inputs or weaknesses within the areas and configurations exercised | Findings from the tested inputs and scope; results are not a guarantee that no defect exists |
| Included-code and dependency review | Risks introduced by copied code, new dependencies, or changes to included components | A reviewed diff and dependency assessment; suitability still depends on the project’s needs |
Use only checks relevant to the change, and record what was actually run and reviewed. A green result is evidence about that check’s scope—not a blanket correctness claim.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Review test changes as carefully as production code
Tests can be weakened while the suite continues to pass. Inspect additions, edits, and deletions for changes that make the evidence less meaningful:
- Existing tests have been deleted or skipped without a justified replacement.
- Assertions have been loosened, removed, or changed to accept more outcomes than the requirement permits.
- A meaningful integration or dependency path has been replaced with mocks that bypass the behavior at issue.
- A new test merely encodes the generated implementation’s behavior instead of checking the independently stated requirement.
These are not hypothetical reasons to distrust every generated test; they are concrete review points identified by OWASP’s guidance on AI-assisted coding. When a test change is necessary, assess whether it preserves meaningful coverage and why the old expectation no longer applies.
Keep a human accountable for the merge
Assign a reviewer who understands the affected code and can judge its correctness, security, and maintenance impact. AI review can offer another perspective, but it should remain additional input rather than a substitute for the project’s review and release gates. OWASP states: “AI tools do not accept responsibility for the code they generate.” The accepting developer remains responsible for the change.
Merge only when the human reviewer has assessed the contract, implementation, tests, and relevant verification results, and has approved the change under the project’s normal process. GitHub’s responsible-use guidance likewise calls for human review and testing before agent output is merged.
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