economists define productivity as gdp per hour worked. Like a lot of other economic measurements, its mostly a bogus number people use as an argument on why their politics are better than someone elses politics. You can have an efficient business located in a poor country making the same product and same quality as that same business in a rich country, the rich country will be more "productive" because local cost of goods is higher there (i.e. a restaurant in NYC is more "productive" than a restaurant in bangladesh).

There is an observational study that was published in March 2026 that followed 4000 teams over 2 years. It shows, in my view, exactly that the productivity gains don't translate into economic value.

Here is the report:

https://www.faros.ai/blog/ai-acceleration-whiplash-takeaways

And my commentary:

https://unessays.substack.com/p/talk-is-cheap

Its funny, I've noticed the same thing, but did not come to the same conclusion.

I currently don't have work access to Claude Code, but most of my teammates do. Watching from the outside, the cycle seems to look like this:

1. Experience some success, which hooks you into relying on AI.

2. The AI keeps failing at some task, but you don't want to stop. Keep trying over and over again.

3. Run out of tokens and take a break.

Now, sometimes 1 doesn't happen. Sometimes 2 doesn't happen. 3 is a certainty though.

Now, if you told me that the productivity gain from 1 is enough to offset the loss from 2 and 3, I could believe you. But I also wouldn't be surprised if it didn't.

I’m going back to being a holdout, but it’s nuanced - My theory into why LLMs don’t lead to the colloquial definition of productivity would be something like - if code was never the bottleneck than generating code faster doesn’t result in more meaningful output.

Even if you take for granted that AI is as good as the best people say in writing code. And Ive spent a lot of time generating codes, I won’t disagree - Then the question becomes - does this change your daily incentives such that you reach for code as the solution to your problems rather than something else (coordinating with your colleagues? Product management? Planning and Design?

So from a holistic perspective, I think intentionally limiting your own AI usage is the best approach for maximum long-term productivity.

Yep.

Code acceleration is great, but.... something precedes that. Vision and strategy re. expansion of offerings and businesses. Once a firm reaches maturity in what it offers and is only touching the edges - this code acceleration is literally useless when you factor in all of the trade-offs.

This is a good thing - it means fat and slow incumbents are sitting ducks to be out-witted by creative and imaginative founders, which is healthy for a well-functioning economy.

Now the economics of existing frontier models are not sustainable - its looking like a mix of the airline (supersonic vs subsonic) and EV industry with China in the background providing decent offerings at much lower prices.

Interesting data, thanks.