I think it's possible we'll see a local model that can do this well within the next few months though - it needs good tool calling, not an encyclopedic knowledge of the world. Might be possible to fit that in a model that runs locally.
I wonder if there are any groups/companies out there building something like this
Would love to have models that only know 1 or 2 languages (eg. python + js), but are great at them and at tool calling. Definitely don't need my coding agent to know all of Wikipedia and translating between 10 different languages
1. A special code dataset 2. A bunch of "unrelated" books
My understanding is that the model trained on just the first will never beat the model trained on both. Bloomberg model is my favorite example of this.
If you can squirell away special data then that special data plus everything else will beat the any other models. But that's basically what openai, google, and anthropic are all currently doing.
Essentially just giving LLMs more state of the art systems made for incremental development?
Ed: looks like that sort of exists: https://github.com/bhauman/clojure-mcp
(Would also be interesting if one could have a few LLMs working together on red/green TDD approach - have an orchestrator that parse requirements, and dispatch a red goblin to write a failing test; a green goblin that writes code until the test pass; and then some kind of hobgoblin to refactor code, keeping test(s) green - working with the orchestrator to "accept" a given feature as done and move on to the next...
With any luck the resulting code might be a bit more transparent (stricter form) than other LLM code)?
Personally I am convinced JSON is a bad format for LLMs and code orchestration in python-ish DSL is the future. But local models are pretty bad at code gen too.
It seems like maybe similar approaches could be used for coding tasks, especially with tool calls for reading man pages, info pages, running `tldr`, specifically consulting Stack Overflow, etc. Some of the recent small MoE models from Chinese companies are significantly smarter than models like Qwen 4B, but run about as quickly, so maybe on systems with high RAM or high unified memory, even with middling GPUs, they could be genuinely useful for coding if they are made to be avoid doing anything without tool use.