Your build starts here
Replace bracketed details with your own goal, context, and checks. Keep the first build small enough to inspect.
Help me understand this generated change: [files or diff]. I know [current experience level], and I want to be able to explain [specific behavior]. Keep the lesson grounded in the actual implementation rather than a generic tour of the language.
Trace one input through the changed code to its observable result. Identify where state changes, where data crosses a boundary, and which assumptions the implementation makes. Before showing the result of each small example, ask me to predict it or provide a short prediction worksheet I can use myself. Include a normal input, an edge case, and a failure case relevant to this change.
Then show how to verify the predictions with a small local check or a manual interaction. Separate what the code demonstrates from what remains uncertain. Finish with a compact explanation I could give another maintainer and one small modification I can make myself. Avoid asking me to memorize unrelated syntax or accepting a polished explanation as evidence that the program works.Make this prompt yours
Useful for reducing the gap between generating code and maintaining it. The examples should come from your own project and use disposable data.
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- learning with AI
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The docs behind it
These references explain the underlying concepts and APIs. The prompt templates and project plans are original examples to adapt to your own setup.
Research sources reviewed .
Editorial review · October 28, 2026
Supported: Original, unexecuted explanation/checking exercise. It distinguishes predicted behavior from checks actually run; GitHub's documented need to validate generated changes supports the caution, not educational outcome claims.