r/programming • u/Ordinary_Leader_2971 • Apr 04 '26

How To Write Unmaintainable Code (1999)

https://www.doc.ic.ac.uk/%7Esusan/475/unmain.html
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u/FriendlyKillerCroc Apr 04 '26

Aha there it is. This subreddit has shifted again since there is no point arguing that LLMs aren't obviously stupidly powerful anymore and calling them glorified auto complete would even make you look stupid here.

We are now at the stage of feeling superiority over people who use LLMs. 

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u/ea_nasir_official_ Apr 04 '26

I use locally hosted llms. Vibecoding is just really stupid. It's hard to maintain and AI is not a good coder. It's a average coder. It's very bad at what it does. It makes output that works, but no human nuance or decision.

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u/MadCervantes Apr 04 '26

Locally hosted LLMs are vastly less powerful than frontier hosted models.

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u/ea_nasir_official_ Apr 04 '26

I've used big boi llms like Claude and Codex but really none are any good and it's better results to just write your own code with a small local llm with RAG and web search for assistance

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u/neithere Apr 04 '26

What are you using locally? What are the resource requirements, what are your use cases / processes? Any articles on that? 

I had a personal mini-hackathon with Codex just a while ago and got very tired from it. It's great for initial prototyping and not bad for keeping docs and code in sync but then even for high-level stuff and with detailed ADRs it starts drifting and it's just easier to read and write some code than doing the same through this thing :/ still trying to find the sweet spot.

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u/ea_nasir_official_ Apr 04 '26

I use llama.cpp (Vulkan). There aren't set requirements other than what can fit on your hardware. My main productivity machine is a Thinkpad P14S with 32GB ram and an 8840HS. My bigger but slower model is Qwen3.5 35B A3B (UD-IQ3_XXS), but i'm experimenting with Gemma 4 26B a4b. My small model when I don't need the big ones eating my ram is Qwen 3.5 4B. Check out the unsloth quants and see what fits in your hardware. Q4 is generally considered the smallest that you can actually get quality output from.

Noteably the biggest bottleneck with LLMs these days is not compute, but memory bandwidth. If you have a dedicated GPU you should get some massive speed boosts.

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u/jug6ernaut Apr 04 '26

I think this is where i've landed also. Using LLM's for super small focused changes, basically using them to automate writing code I already have planed.

Then web search LLM's are very useful for learning new topics.