alt Hacker NewsIs selection really the issue?
You'd still need to figure out what payload to give to the tool based on your context.
But I guess depending on your business case it might be worth it. It's not something I'd do from the beginning, though.
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it’s not just about selection. say you’ve got 100k tool calls — in the current hosted llm setup, you don’t actually learn anything new about your data to improve future tool accuracy.
this gets worse when you’re chaining 3–4+ tools. context gets noisy, priors stay frozen and there's prompt soup..
my intuition here is: you can learn the tool routing and the llm prompts before and after the call. (can always swap out the rnn for a more expressive encoder model and backprop through the whole thing).
super useful when you’re building complex workflows -- it gives you a way to learn the full pipeline, not just guess and hope.
This is a bigger problem than it looks like at first glance. For isecases where llm + tool calls make more sense compared to say llm assisted codegen, figuring out the tool arguments is nontrivial. Where it is relatively easy I think codegen is a better option wrt amortised running costs