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recipes, from time-consuming experience
errors:
- prompting too simple: the AI doesn't respect any rule and can change things you don't want at first (like variable names)
- not using multi-AI loost the comparison and compensation (like orthographic errors, what is generated different is what to look)
- an easy before/after comparison test is usefull, better when they can auto-check themself, simpler if they write auto-test
- not adding safe exit to llm , "do you think it's possible ? is there enough information to", may reduce hallucinations
- accepting torents of lines of code... as AI can bloat you also on this
total time saver:
- asking AI to not disrupt existing code: "can you help rework it so it can do current feature and new one ?"
next level things:
- GitHub Copilot for Skeptics Who Still Think AI is Overrated: explains some AI beginner errors
This parodic picture summarizes well the standard pitfalls when using IA too blindly
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