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What you are probably seeing
Your current static analysis reports contain many warnings that developers ignore because the context is missing.
You notice that AI-generated documentation is more readable but occasionally includes incorrect code interpretations.
Why it happens
Legacy static analysis tools use rigid pattern matching that fails to understand complex code semantics.
AI models rely on probabilistic inference which produces plausible but sometimes inaccurate natural language descriptions.
What changed recently
Step by step
1. Generate documentation for a small sample of modules using the AI tool.
2. Manually review the AI output to identify factual errors or hallucinations.
3. Run your existing static analysis tool on the same codebase for comparison.
4. Document the specific false positives found in both the AI output and the legacy tool.
5. Create a decision matrix to weigh the value of AI documentation against the noise from false positives.
Ways to go further
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