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What does debugging code with AI mean?
Debugging with AI means using an AI explanation or suggestion to help investigate unexpected program behaviour. A suggested cause or change is a possibility to evaluate, rather than proof that the problem is solved.
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Download on the App Store ↗An explanation is different from a verified fix
When a total looks wrong, the cause could be the input, a calculation, or an assumption about the result. AI can suggest possibilities, but those suggestions still need review and testing in the relevant program.
Project-aware agents can connect a symptom to evidence
Codex and Claude Code can work with project files and development tools when those are available. That lets a debugging request refer to an actual implementation and its checks. The request is clearer when it distinguishes the observed failure from the behaviour that should happen.
For a save problem, visible confirmation and a record still existing after reopening are different observations. A useful review connects the proposed change to the original failure. A confident explanation alone does not show that the relevant behaviour was reproduced and checked.
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