Why AI Gets Your Technical Question Wrong, and How to Check Before You Paste

Description and use

AI often produces technically plausible answers that silently fail. Verify diagnostics, specify the exact version, test with a minimal example, apply the fix, and compare outputs against official documentation to ensure correctness.

Problem

AI-generated technical answers often appear correct but contain silent failures, leading developers to trust incorrect fixes.

Outcome

By systematically validating AI suggestions against real tool behavior and documentation, developers avoid silent failures and ensure reliable fixes.

Workflow

• 1. Ask the AI for a diagnostic: "If this were wrong, what would I see?"
• 2. Specify the exact tool version and ask about version differences.
• 3. Reduce the problem to a minimal file that reproduces the symptom.
• 4. Apply the suggested fix and run the minimal example before touching production.
• 5. Compare outputs (diff, row counts, generated files) to confirm the change.
• 6. Verify any error messages or output against the vendor’s official documentation or source code.

Evidence

"If this were wrong, what would I see?" Then confirm that the error it names actually exists in your tool.

Source

Of 113 unsettled questions, 82 came back with at least one wrong claim, and 56 had a claim that fails without saying so.

Source