I'll take the contrary position and say that I think the "tokenmaxxing" we've previously seen was useful (but shouldn't continue indefinitely). My TLDR position is that TokenMaxxing was a way to force discovery of Product Market Fit.

The push by companies to incorporate AI into everything is (depending on the company) either hype and cargo-culting or it was an attempt by management to (1) try and discover if/what new workflows or tools could use it and (2) force the haters to use as it got better.

Where I work, there is an obvious split between people who have been willing to use AI, and those that hated it from day 1 and mocked the "stochastic parrots". Senior folks were disproportionately haters, and generally didn't see much productivity lift from early AI stuff. They strongly resisted the mandates to use AI, and completely missed the "agentic" inflection point that other colleagues experienced. The more willing users saw Claude Code/agents and were able to experience this as the genuine benefit it can be. Now that the more senior folks are using agentic programming, they're genuinely able to maintain code quality and see meaningful speed improvements in coding tasks.

Today, tokenmaxxing doesn't make sense because we found the product-market-fit of agentic coding. Now that most (?) employees are onboard with using it, the industry can shift focus to cost-effective usage and positive-ROI usage. For example, Uber shifting to a fixed per-employee token budget.