Generally I think this happens anytime you try to use too much compute/inference at once. It happens to me everytime a new model comes out; I get excited and want to see what it can do.

You have to carefully manage the project scope, and catch the ai getting stuck. There is a stars aligning point where you are matching the model to its scope on a clearly defined goal to iterate towards and its mind-blowing. And then if you go even a bit over that point it's perf falls off a cliff.

And it changes with each model with each new release.

For example, I wasted a bunch of usage today giving Fable 5.2 8 sub-orch opus high agents that each were given bunch of chatgpt subagents. It was fun watching all the churn, and I'm trying to find some way to use up all my openai usage.

But in the end I made much less progress/made a bunch more slop code than if I had just narrowed project scope and gave fable a smaller easier task with less agents under it. And now my weekly usage is gone in 2 days.