Commenters report practical harness preferences and inverse scaling relationship
5 Sep 17 2:24 AM · 9d ago · 1 post · 2 comments · 2 sources · development 5 of 7
Users share experience that harness importance scales inversely with model size: smaller models require more sophisticated harness work for context and memory management, while large models need only basic tooling and manage context themselves. One commenter reports switching from OpenCode to Pi harness found it simpler and preferable.
“The harness becomes more and more important, the smaller the model is as you need to offload context management as well as memory to the harness.”
calgoomatt_d HarnessTax research author/submitterYashjain413 HN commenterSupermancho HN commenternojs HN commenterlukax HN commenter
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What people said 2 voices · verbatim
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Harness and benchmark for the harness feels like a chicken and egg problem. The harness is to optimize the interaction results with the models. Any benchmark for harness has to focus on the goals that the harness was trying to optimize for unless we are only focussing on generic harnesses.At this point when all the models have been trained on all…
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I really disliked how opencode works IMO; the harness tries to do to much in my mind. Switching to Pi was a breath of fresh air for me, and I even use hax for some of my local needs where i dont want to have the giant pile of fertilizer that is NPM or PIP installed.The harness becomes more and more important, the smaller the model is as you need…
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