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Description
- Adopt a "
Hybrid Code-Explanation" workflow by explicitly asking the AI to explain the logic of any code it generates to ensure you understand the underlying concepts. - Resist the urge to immediately paste error messages into the chat, as manually debugging complex issues is the primary driver for retaining deep technical skills.
- Verify your mastery by using the "
Generation-Then-Comprehension" pattern, where you rigorously review and question AI-written code to confirm you could have written it yourself. - Maintain consistent effort throughout difficult tasks rather than sliding into "
Progressive AI Reliance," as handing over the hard parts deprives you of critical learning opportunities. - Sustain active "
cognitive engagement" by treating the AI as a subordinate to be supervised rather than a replacement, ensuring you remain capable of auditing code in safety-critical scenarios.
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