And then you realize that what you’re using the smaller models for is ALSO decomposable and part of it is just a few if statements, and then you realize that for this feature you don’t actually need or want a model because the performance, reliability, reproducibility are cheaper and better for you and your users.

Indeed, I've been experimenting with agent workflows, for complicated tasks - where I essentially have a graph of agents with different roles/capabilities, including such things as breaking down complex tasks into simpler ones. There seems to be a point where a complex enough task is better performed by a group of cheaper agents/models than by one agent using one of the SOTA big models, in terms of both quality and cost.

It is also interesting because you get people with very different use cases arguing about the effectiveness of various models but doing very different things with them.

Its one things for a model to be very clearly instructed to add a REST endpoint to an existing Django app and add a button connected to it on the front vs "Design me a youtube". The smaller models can pretty dependably do the first and fall flat on the second.