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> The LLMs are much more eager to please and to write lots of code. My process right now when working LLMs is to do the following: - Create problem and soluti
by sdesol 2y ago
> The LLMs are much more eager to please and to write lots of code.
My process right now when working LLMs is to do the following:
- Create problem and solution statement
- Create requirements and user stories
- Create architecture
- Create skeleton code
- Map the skeleton code
- Create the full code
At every step, where I don't need the full code, the LLM will start coding and I need to stop it and add "Do not generate code. The focus is still design".
- code_for_monkey 2y agoone of my biggest issues with the LLM is how it always wants to give me a mountain of code. A lot of the time Im using it for react, and it always gives me a full component no matter how much I specify I just want the method. It will not remember this for more than one message and will go back to giving me as much code as possible.
- sdesol 2y agoYeah, it almost feels like you are talking to somebody with OCD. The frustrating part is, output tokens are usually a lot more expensive than input tokens, so they are wasting energy and money :-). Also, the more they generate, the greater the chance it will create attention issues as the conversation progresses. This is why I built my chat app to let me manipulate LLM responses. If I feel it is not worth knowing, I'll just erase parts of it to ensure the conversation doesn't get side tracked. Or I will go back to the original user message and modify it to say ### IMPORTANT - Do not generate more code than required. The nice thing about LLM conversations are, every time you chat, the LLM treats it as a first time conversation, so this trick will work if the model is smart enough.