If you've got some time, I highly recommend going through the exercise of trying to change the prompt in a way that would produce code similar to what you've achieved manually. Doing a similar exercise really helps to improve agent prompting skills, as it shows how changing parts of the prompt influences the result.

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foltik 2 hours ago | parent | next [-]

I haven’t had any luck prompting LLMs to “have taste.” They seem to over fixate on instructions (e.g. golfing when asked for concise code) or require specifying so many details and qualifications that the results no longer generalize well to other problems.

Do you have any examples or resources that worked well for you?

	▲	zarzavat 42 minutes ago \| parent [-]
		Yeah prompting doesn't work for this problem because the entire point of an LLM is you give it the what and it outputs the how. The more how that you have to condition it with in the prompt, the less profitable the interaction will be. A few hints is OK, but doing all the work for the LLM tends to lead to negative productivity. Writing prompts and writing code takes about the same amount of time, for the same amount of text, plus there's the extra time that the LLM takes to accomplish the task, and review time afterwards. So you might as well just write the code yourself if you have to specify every tiny implementation detail in the prompt.

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globnomulous 16 minutes ago | parent | prev [-]

I appreciate that your message is a good-natured, friendly tip. I don't mean for the following to crap on that. I just need to shout into the void:

If I have some time, the last thing I want to do with it is sharpen prompting skills. I can't imagine a worse or more boring use of my time on a computer or a skill I want less.

Every time I visit Hacker News I become more certain that I want nothing to do with either the future the enthusiasts think awaits us or the present that they think is building towards it.