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ontouchstartyesterday at 8:27 PM2 repliesview on HN

I am running local offline small models in the old fashioned REPL style, without any agentic features. One prompt at a time.

Instead of asking for answers, I ask for specific files to read or specific command line tools with specific options. I pipe the results to a file and then load it into the CLI session. Then I turn these commands into my own scripts and documentation (in Makefile).

I forbid the model wandering around to give me tons of irrelevant markdown text or generated scripts.

I ask straight questions and look for straight answers. One line at a time, one file at a time.

This gives me plenty of room to think what I want and how I get what I want.

Learning what we want and what we need to do to achieve it is the precious learning experience that we don’t want to offload to the machine.


Replies

pragma_xyesterday at 10:11 PM

> I ask straight questions and look for straight answers. One line at a time, one file at a time.

I've also taken to using the Socratic Method when interrogating an LLM. No loaded questions, squeaky clean session/context, no language that is easy to misinterpret. This has worked well for me. The information I need is in there, I just need to coax it back out.

I did exactly this for an exercise a while back. I wanted to learn Rust while coding a project and AI was invaluable for accelerating my learning. I needed to know completely off-the-wall things that involved translating idioms and practices from other languages. I also needed to know more about Rust idoms to solve specific problems and coding patterns. So I carefully asked these things, one at a time, rather than have it write the solution for me. I saved weeks if not months on that activity, and I'm at least dangerous at Rust now (still learning).

FitchAppsyesterday at 9:16 PM

This. I'm also using an LLM very similarly and treat it like a knowledgeable co-worker I can ask for an advice or check something. I want to be the one applying changes to my codebase and then running the tests. Ok, agents may improve the efficiency but it's a slippery slope. I don't want to sit here all day watching the agents modify and re-modify my codebase, I want to do this myself because it's still fun though not as much fun as it was pre-AI

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