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nostrademonstoday at 1:15 AM1 replyview on HN

LLM APIs are more sticky than many other computing APIs. Much of the eng work is in the prompt engineering, and the prompt engineering is pretty specific to the particular LLM you're using. If you randomly swap out the API calls, you'll find you get significantly worse results, because you tuned your prompts to the particular LLM you were using.

It's much more akin to a programming language or platform than a typical data-access API, because the choice of LLM vendor then means that you build a lot of your future product development off the idiosyncracies of their platform. When you switch you have to redo much of that work.


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jsnelltoday at 2:40 AM

No, LLMs really are not more sticky than traditional APIs. Normal APIs are unforgiving in their inputs and rigid in their outputs. No matter how hard you try, Hyrum's Law will get you over and over again. Every migration is an exercise in pain. LLMs are the ultimate adapting, malleable tool. It doesn't matter if you'd carefully tuned your prompt against a specific six months old model. The new model of today is sufficiently smarter that it'll do a better job despite not having been tuned on those specific prompts.

This isn't even theory, we can observe the swings in practice on Openrouter.

If the value was in prompt engineering, people would stick to specific old versions of models, because a new version of a given model might as well be a totally different model. It will behave differently, and will need to be qualified again. But of course only few people stick with the obsolete models. How many applications do you think still use a model released a year ago?

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