The reason I'm getting LLM burnout is from dealing with the obvious neutering and opaque downgrading of all the top models.

Prior to the last 12mos AI companies were hell bent on squeezing out the best results from mediocre models.

But... now that the top models have progressed, those same AI companies have switched their efforts into reducing the computation (cost of a producing a result) as much as possible without being too obvious.

What was an exponential slope in the quality of results over the last 36 months has now nearly flat lined.

Addendum: IMHO results have 'flat lined' not because the models aren't much more capable than a year ago, but because conserving the enormous processing cost (of an over subscribed user base) supersedes the goal of following the user's explicit instructions (e.g. especially if that means more processing cost) to generate the best results.

I feel the same way about consumer AI tools now. Gemini and ChatGPT have been abysmal lately. They can no longer be relied on to do multi-turn searching and thinking.

Before, they could stay in thinking mode for more than 7 minutes. For example, "find a source for this claim" would search, analyze, and self-adjust the query. Nowadays, even if I push for it, I cannot make these tools work for more than 30 seconds before they give generic answers, even in "Pro" mode.

You sure about that? Maybe it is reality hitting expectations after the initial “holy shit” wears off

This seems hilariously, extremely revisionist.

Hell, the Opus 4.5 moment was only last November, and that was when agentic coding and most coding CLI tools became truly first class options. That's a wild paradigm shift. Hell, GPT-5 wasn't even out (that's August of last year). Most people were using 4o. Their current offerings are wildly better for coding than 4o was.

Cannot relate, my expectations might just gone up, because when I compare what I was producing with agents a year ago vs now, it's night and day.