> [...]it's just a simple calculation of "is this worth it?" which I suspect for most cases will be 'yes'

Once the landgrab-stage flat-pricing goes away, it will become a case-by-case calculation because unsupervised agents can (and will) run up your billing with zero understanding of the business value of what they're instructed to solve.

> with zero understanding of the business value

What kind of products/services are you building where you aren't able to tie your eval suite to business value? If you can't, then why are you building whatever is it you are in the first place?

By far one of the biggest changes I think we'll see in things being built by agents is reducing the gap between code and value. The first stage is to start making it possible to measure quality (evals) and the second stage is to more closely align measurable equality with value. The business value of the tokens spent on my team was discussed my first day.

> Once the landgrab-stage flat-pricing goes away

Aside from the above point, I'm already running local LLMs on my homelab that, while not quite what I want for truly production work, have been able to iterate on and solve real, non-trivial research tasks for effectively zero cost (energy cost was roughly on par with running an old light bulb).

The way open, local models have been developing there will be many cases where if proprietary providers over-charge it won't be a deal breaker to just switch to local models. Not to mention that there are plenty of open, but non-local models that are already 5x cheaper and roughly on par with the mainstream model providers.