101–110 of 318 posts
My personal notes (not the author): have been way faster performance wise which is honestly the biggest improvement over correctless. I've posted https://github.com/can1357/oh-my-pi before, but didn't seem to gain traction. It's a great little agent.
I feel I want to write my own and that maybe in the future a lot of developers will have custom harnesses and have highly customized versions as each user of these models wants to use these things in a way that's unique to their brain, much like how emacs is so great for the customization but one persons emacs config is often not what another wants or only wants a subset and then write their own features.
As an aside what is the feeling on all the various ai coding tools, does aider suck is that aider-ce/cecli are better or are the bespoke tools for each model like claudeCode and such better.
Why not just use line numbers?
During my first LLM experiments in Emacs using gptel, I also found that the LLM has considerable difficulties changing source code files with the Unix patch tool. As Emacs has a built-in tree-sitter package, I implemented this same idea. I created gptel tools like tree_sitter_list_nodes, tree_sitter_get_nodes, tree_sitter_update_nodes, tree_sitter_insert_before_node and tree_sitter_insert_after_node. The "list" tool…
The harness is the model "body", it's weight the cognition. Like in nature they develop together and the iteration of natural selection works at both. If smaller labs (Zai, Moonshot, deepseek, mistral..) get together and embrace a harness, like opencode for example, as a consortium just by the power of "evolution across different environments" they might hit jackpot earlier than bigger labs.
But they rely on distilling the output of american leader models. Which will probably train against their own harness. Someone has to do the baseline training, development, and innovation. it can't be clones all the way down
Why not just use line numbers?
The harness is the model "body", it's weight the cognition. Like in nature they develop together and the iteration of natural selection works at both. If smaller labs (Zai, Moonshot, deepseek, mistral..) get together and embrace a harness, like opencode for example, as a consortium just by the power of "evolution across different environments" they might hit jackpot earlier than bigger labs.
But they rely on distilling the output of american leader models. Which will probably train against their own harness. Someone has to do the baseline training, development, and innovation. it can't be clones all the way down