In the real world, token costs seem to be going up, as early stage pricing at a loss gives way to pricing that generates revenue.

Compute costs might go down a little over the next five years, but there's nothing coming along in hardware that leads to huge reductions in price. NVidia says don't expect better price/performance before 2030.

The models keep getting bigger, and people put loops around them which iterate, burning tokens.

Where is this cost reduction coming from?

From last month: https://peinsights.substack.com/p/apollo-and-blackstone-clos...

The fact that we aren't seeing an app explosion (I think) is evidence that building applications people will pay for is significantly more complex than just prompting claude/codex/etc

Now, on the first order point, I agree that non-tech companies seem to be taking longer to see results from AI, even if the argument was bad.

I work on SaaS for the logistics space, and I feel like prior to the end of 2025, almost all the discussion about AI for logistics was vaporware, starting this year, companies are actually trying to deploy agents, and we'll start finding out what the ROI is later this year or next.

And I don't think this is unusual. It took decades for previous technologies to be fully integrated into existing businesses. In the 80s you could see the IT revolution everywhere... except the productivity statistics, which didn't catch up until the 90s.

LLMs are still very new and have significant limitations (like prompt injection and high token costs) that are very likely solveable but will take time.

"The first chart below shows that so far there are no signs of profit margins rising outside the tech sector. This is ultimately what we are waiting for, because the value of AI companies today rests entirely on the promise that margins in the S&P 493 will eventually climb."

This is absolutely not necessary. The bull case is that AI will bring great efficiencies. The surplus profits from those efficiencies could easily be competed away by firms who have adopted AI. Those firms who do not adopt AI will have their margis crushed.

The market has clearly spoken. Knowing what you're doing is much more valuable than just the doing. That still requires humans. This AI winter has already begun.

The value shows up only after the boring part: wiring the model to the real data with real access control, and moving anything that has to be exact or repeatable out of the model and into deterministic tools it calls. That's an integration-and-permissions project, not an "adopt AI" project. It's slow, it's unglamorous, nobody demos it, so pilots skip straight to the chatbot and then report thin ROI. Tech companies see returns faster partly because their data and tooling are already reachable by the thing.

So I'd read the flat margins as "the actual work hasn't been done yet," not "there's no value there." The runway being long and the technology being real aren't in tension. The gap is that the useful version looks like plumbing, and plumbing doesn't get funded on the same timeline as a demo.

I've seen this in payment/API systems: the actual model integration takes weeks, but getting legal and security sign-off on the data pipeline takes months. Non-tech companies face the same pattern but with less internal tooling to manage it.

The margin signal might also be appearing at the wrong level. Gains in these sectors often show up first as headcount flatness or throughput improvements before they hit EBITDA. Measuring at the P&L level on a 2-year horizon is probably too early and too coarse - the operational metrics are moving, the accounting just hasn't caught up yet.