What's Actually Going On Inside an LLM (And Why Your Prompts Keep Failing)
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A few months into using ChatGPT and Claude daily for work, I hit a wall. Some days the model felt like magic it would write exactly the function I needed, catch a bug I'd missed, explain a concept better than any textbook. Other days, the same tool would confidently give me garbage. Wrong API names. Made-up library functions. Code that looked right but silently did the wrong thing. For a while I chalked this up to "the AI being inconsistent." Eventually I realized the inconsistency was mostly…
1Key Takeaways
- A few months into using ChatGPT and Claude daily for work, I hit a wall.
- Some days the model felt like magic it would write exactly the function I needed, catch a bug I'd missed, explain a concept better than any textbook.
- Other days, the same tool would confidently give me garbage.
- Code that looked right but silently did the wrong thing.
2AIWedia Score
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3Why it matters
Prompt and agent patterns spread fast; staying current saves time and token cost. DEV — Prompt Engineering reports that a few months into using ChatGPT and Claude daily for work, I hit a wall.
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