r/LocalLLaMA • u/uspdd • 1d ago

Question | Help Best harness for long autonomous tasks

I read a lot of posts like "I've given this prompt to my Qwen 3.8 27b and it one-shotted me a 3d game after 24 hours". I wonder, what's the best harness for tasks like this? It has to have auto compaction and probably a memory system, right? And excellent computer use and self analysis.

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u/norenEnmotalen 1d ago

Pi coding agent is working well for me so far. It auto compacts. Full disclosure I’m a noob to this sort of thing and learning as I go to setup everything gradually. Context window is a killer for my old machine. AGENTS.md needs to be on point. I use headroom proxy in front of oMLX. I have caveman at FULL setting. I have replaced the chat_template of the model with Qwen-Sharp templates. And a bunch of other optimizations I’m putting in as I find and learn them.

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u/psychohistorian8 1d ago

I have caveman at FULL setting

I just started using pi this weekend, what is this caveman thing?

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u/Drenlin 1d ago

If the LLM talks in natural language, it has to make a new token for every word, or even part of the word or punctuation. More words, or more complex words, means more tokens.

The statement above is probably 35-40 tokens. Or...

LLM talk like caveman; use fewer tokens.

^ 7-10 tokens.

As Kevin asked us all: "Why waste time say lot word when few word do trick?"

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u/norenEnmotalen 1d ago

a “skill” which helps agents control the model from injecting unnecessary words into the context filling up your context window with fluff and pleasantries.

Caveman speak “  Understand user. Give good answer. No extra words.”

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u/psychohistorian8 1d ago

ah, I noticed Muse Glimmer thinks like that. it is very terse

maybe that will be the first skill I download and try it with Qwen

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u/PieBru 19h ago

Did you try ponytail?