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I have been using LLMs (chapt-gpt, perplexity, claude) for development for over a year. It is helpful for summary explanations of concepts and boilerplate for f
by aorona 2y ago
I have been using LLMs (chapt-gpt, perplexity, claude) for development for over a year. It is helpful for summary explanations of concepts and boilerplate for frameworks and library APIs. But it makes errors within those consistently.
Its a great tool and saves a great deal of time, but I have yet to go beyond generating snippets I have to vet, typically finding a made up library API call or misunderstanding of my natural language prompt.
I find it hard to pare down these LLM evangelizing articles into take aways that improve my day to day.
- nurettin 2y agoI know it is in the nature of probabilistic neural network outputs, but it almost feels like these commercial models are built to make those mistakes (making up functions/parameters) and it is all a big conspiracy to hide the real useful stuff from general public. I started giving the models api docs and headers before interacting with them and it seems to work a lot better.