Generating Functions with Prompts

A developer reports that prompting a chat LLM for individual functions and pasting the output into code can work better than agentic harnesses for some situations, and that a local model such as Gemma 4 occasionally generates a better function than a cloud-based model. The developer argues LLM-generated functions make string manipulation far easier and faster than writing by hand, and that string manipulation tutorials will likely become less useful in the future. Working locally also avoids the risk of having an account canceled, the developer notes.

I know that agentic harnesses are popular in software development these days. But they are not the only way to generate code with AI. If I have a specific function in mind, I will sometimes just prompt for it in chat , and then paste it in. I have found this works well. And it is worth trying different LLMs—I have found that occasionally a local model like Gemma 4 can generate a better function than a cloud-based model. It does make me realize that: • For string manipulation, having an LLM generate a function is way easier and faster than writing one by hand. • String manipulation and similar tutorials are probably not going to be that useful in the future. It is possible to piece together a program with a chat bot's output, and for some situations this probably works better than an agentic harness. It allows me to do more work locally —which means I cannot have my account canceled.