Also another place where having it change out from underneath you can drastically alter the quality of your work in unexpected ways.

Like most things - assume the "20/100/200" dollar deals that are great now are going to go down the enshitification route very rapidly.

Even if the "limits" on them stay generous, the product will start shifting to prioritize things the user doesn't want.

Tool recommendations are my immediate and near term fear - paid placement for dev tools both at the model level and the harness level seem inevitable.

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The right route is open models and open harnesses, ideally on local hardware.

> Like most things - assume the "20/100/200" dollar deals that are great now are going to go down the enshitification route very rapidly.

I don’t assume this at all. In fact, the opposite has been happening in my experience: I try multiple providers at the same time and the $20/month plans have only been getting better with the model improvements and changes. The current ChatGPT $20/month plan goes a very long way even when I set it to “Extra High” whereas just 6 months ago I felt like the $20/month plans from major providers were an exercise in bouncing off rate limits for anything non-trivial.

Inference costs are only going to go down from here and models will only improve. I’ve been reading these warnings about the coming demise of AI plans for 1-2 years now, but the opposite keeps happening.

At this point subsidizing Chinese open-weights vendors by paying for them is just the right thing to do. Maybe they too might go closed-weights when they become SotA, but they're now pretty close and haven't done it.

The harness is effectively the agent's 'body'. Swapping the brain (model) is good, but if the body (tools/environment) is locked down or inefficient, the brain can't compensate. Local execution environments that standardize the tool interface are going to be critical for avoiding that lock-in.