It's not possible for this level of impact at the bottom to make no change on the net near the top, so I propose that effects may be delayed and not immediately apparent. LLMs are still a new thing in business timelines.
TL;DR: just wait a bit more.
One thing I can hint at, but can't go into details, is that I personally know of at least one enterprise-grade project whose roadmap and scoping - and therefore, funding - is critically dependent on AI speeding up significant amount of development and devops tasks by at least 2-3x; that aspect is understood by both developers, managers, customers and investors, and not disputed.
So, again: just wait a little longer.
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[0] - Except maybe for Aider, whose author always posts how much of its own code Aider wrote in a given release; it's usually way above 50%.
Mm. I can now see why, in your other comment, you want to keep up with the SOTA.
My use of LLMs isn't all that big, and I don't have any special early access or anything. It's just that the tokens are so cheap that, for casual personal and professional use, the pricing difference didn't matter. Switching to a stronger model meant that my average monthly bill went from $2 to $10 or something. These amounts were immaterial.
Use patterns and pricing changes, though, and recently this made some SOTA models (notably o3, gpt-4.5 and the most recent Opus model) too expensive for my use.
As for the project I referred to, let's put it this way: the reference point is what was SOTA ~2-3 months ago (Sonnet 3.7, Gemini 2.5 Pro). And the assumptions aren't just wishful thinking - they're based on actual experience with using these models (+ some tools) to speed up specific kind of work.
It's a thought terminating cliche.