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this post was submitted on 28 Oct 2026
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I think you're misunderstanding the purpose of them, to be honest. They're meant to be used instead of LLMs instead of in conjunction with. Let's say you have 100 emails, you have 4 tags; "important", "normal", "low priority" and "spam". These decision models are made to cheaply and quickly classify those 100 emails into one of those 4 options. They tell you "this email is spam, with 83% confidence". Just by giving it the email contents.
An LLM will also be able to determine that and think about it and probably do a better job at it. But it will be an order or magnitude slower and more expensive at that task.
Feel free to correct me if I've misunderstood something haha
EDIT: Let me immediately correct myself here. They can absolutely be used in conjunction with LLMs, just not in the way you're thinking. It would rather be as a pre-sorter for something like "can this task be done by a cheap local LLM or should I pass it to opus" and it chooses between those. It isn't "smarter" than full LLMs so isn't deciding between code change options. It would rather be a cost/time saver in that case.
OK that latter use case makes some sense to me.