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My LLM codegen workflow

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131–140 of 168 posts

Re: My LLM codegen workflow

#131

Post by foretop_yardarm »

cipehr wrote: post #112
btucker wrote: post #97

Earlier quoted context omitted.

It seems like you might be trying to use it like a search engine, which is a common mistake people make when first trying LLMs. LLMs are not like Google. The key is to give it context so it can help you. For example, if you want it to help you with Spark configuration, give it the Spark docs. If you want it to help you write code, give it your codebase. Tools like cursor and the like make this process very easy. You…

Thank you very much for the ideas here, i will try the approach of giving it context. I havent got into cursor, since i use helix and intellij… i need to look into the MCP server thing Thanks again!

Giving examples of inputs and outputs can also help

Re: My LLM codegen workflow

#132

Post by HPsquared »

briga wrote: post #73

Absolutely LLMs are great for greenfield projects. They can get you to a prototype for a new idea faster than any tool yet invented. Where they start to break down, I find, is when you ask it to make changes/refactors to existing code and mature projects. They usually lack context, so they doesn't hesitate to introduce lots of extra complexity, add frameworks you don't need, and in general just make the situation wor…

LLM coding is quite well-suited to projects that apply the Unix philosophy. Highly modular systems that can be broken into small components that do one thing well.

Re: My LLM codegen workflow

#133

Post by watt »

Isamu wrote: post #16

I’m curious, is adding “do not hallucinate” to prompts effective in preventing hallucinations? The author does this.

It will work - you can see it well with a Chain of Thought (CoT) model: it will keep asking itself: "am I hallucinating? let's double check" and then will self-reject thoughts if it can't find a proper grounding. In fact, this is the best part of CoT model, that you can see where it goes off rails and can add a message to fix it in the prompt.

For example, there is this common challenge, "count how many r letters in strawberry", and you can see the issue is not counting, but that model does not know if "rr" should be treated as single "r" because it is not sure if you are counting r "letters" or r "sounds" and when you sound out the word, there is a single "r" sound where it is spelled with double "r". so if you tell the model, double "r" stands for 2 letters, it will get it right.

Re: My LLM codegen workflow

#134

Post by matsemann »

mark_mcnally_je wrote: post #57

I'm a bit confused here, what promt do you use to start Aider and how do you just let Aider run wild so you can play cookie clicker?

Yeah, everyone is saying this article is great, but it's akin to "then draw rest of the owl". It's very detailed in planning, and then for execution just "paste prompt into claude". What prompt?

Re: My LLM codegen workflow

#135

Post by matsemann »

snowwrestler wrote: post #41

Spelling nit: “Over my skis” ~ in over my head. “Over my skies” ~ very far overhead. In orbit maybe?

> “Over my skis” ~ in over my head.

Is that correct? Never heard the expression before, but as a skier if you're over your skis you're in control of them, while if you're backseated the skis will control you.

Re: My LLM codegen workflow

#136

Post by ChrisRob »

In our company we are only allowed to use GitHub Copilot with GPT or Claude, but not Claude directly. I'm quite struggling with getting good results from it, so I'll try to adapt your workflow into that setup. To the community: Do you have some additional guidance for that setup?

Re: My LLM codegen workflow

#137

Post by anon7000 »

krupan wrote: post #118
bcoates wrote: post #85

That lonely/downtime section at the end is a giant red flag for me. It looks like the sort of nonproductive yak-shaving you do when you're stuck or avoiding an unpleasant task--coasting, fooling around incrementally with your LLM because your project's fucked and you psychologically need some sense of progress. The opposite of this is burnout--one of the things they don't tell you about successful projects with good…

Seriously!! Coding with LLM's is marketed as a huge time saver, but every time I've tried, it hasn't been. I'm told I just need to put in the time (ironic, no?) to learn to use the LLM properly. Why don't I just use that time to learn to write code better myself?

It’s not really ironic. You could spend a couple hours making yourself twice as good as using AI tools, or a couple hours making yourself like .1% of a better programmer, assuming you’re not banging your head against the wall anyways.

It’s one of those things where a little upskilling can make a big impact. So many things in life need a bit of practice before they’re useful to you.

For starters, you need to change the default prompt in your editor to make it do what you want. If it does something annoying or weird, put it in the prompt to not take that approach. For me, that was absurdly long, useless explanations. And now it’s short and sweet.

Re: My LLM codegen workflow

#138

Post by mrklol »

About the first step, you probably also need some kind of context that the LLM has most information to iterate with you about the new feature idea.

so either you put the whole codebase into the context (will mostly lead to problems as tokens are limited) or you have some kind of summary with your current features etc.

Or you do some kind of "black box" iterations, which I feel won’t be that useful for new features, as the model should know about current features etc?

What’s the way here?

Re: My LLM codegen workflow

#139

Post by mdrzn »

krupan wrote: post #118
bcoates wrote: post #85

That lonely/downtime section at the end is a giant red flag for me. It looks like the sort of nonproductive yak-shaving you do when you're stuck or avoiding an unpleasant task--coasting, fooling around incrementally with your LLM because your project's fucked and you psychologically need some sense of progress. The opposite of this is burnout--one of the things they don't tell you about successful projects with good…

Seriously!! Coding with LLM's is marketed as a huge time saver, but every time I've tried, it hasn't been. I'm told I just need to put in the time (ironic, no?) to learn to use the LLM properly. Why don't I just use that time to learn to write code better myself?

Seriously!! Cars are marketed as a huge time saver, but every time I’ve tried one, they haven’t been. I’m told I just need to put in the time (ironic, no?) to learn to drive properly. Why don’t I just use that time to train my legs and run faster instead?

Re: My LLM codegen workflow

#140

Post by infecto »

briga wrote: post #73

Absolutely LLMs are great for greenfield projects. They can get you to a prototype for a new idea faster than any tool yet invented. Where they start to break down, I find, is when you ask it to make changes/refactors to existing code and mature projects. They usually lack context, so they doesn't hesitate to introduce lots of extra complexity, add frameworks you don't need, and in general just make the situation wor…

You are right but that's also a good indication that the codebase itself is too complex and at a certain size / scale, too much for a human to reason over even or even if something a human could do, is not efficient doing so.

You should not be structuring the code for a LLM alone but I have found that trying to be very modular has helped both my code as well as the ability to utilize LLM on top of it.

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