[eru]

(Not the OP.)

The LLMs are much more eager to please and to write lots of code. When I was younger, I would get distracted and play computer games (or comment on HN..), rather than churn out mountains of mediocre code all the time.

[sdesol]

> 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]

one 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]

Yeah, 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.