And "education" is not limited to the classroom. How the world really works isn't always obvious from in front of a computer.

Alternative option, the writer did not fall for the scam, but is now in on the grift: https://www.cnbc.com/2026/02/06/google-microsoft-pay-creator...

That definitely happened with Uber, but I would argue that one key difference between the Uber situation and the AI situation is COST. How much can COGs be reduced via optimization and technology.

In Uber scenario, the cost is labor, there's a hard lower limit where people will find something else to do for work.

In AI scenario, we've already seen the labs make major reductions in cost-per-token. I think it's fairly uncontroversial to say they have more possible cost reduction levers than Uber.

So I don't agree that at some point VC money will run dry and the unit economics for tokens will dramatically change.

I am still waiting for a donut to save us.

In the case of a VC-subsidized service like Uber, the subsidization is utilized by the company until a a monopolistic or network effect takes hold and allows for price increases.

LLM economics are very different. If the tokens are being subsidized now, they must stay subsidized until some form of monopoly, network effect, or pure R&D advantage is achieved.

In the case of LLMs, the open weight models are nipping at the heels of the proprietary models, and this may be a fundamental condition. Perhaps subsidizing tokens enhances increases engagement, and thus, equity value of the company training the proprietary models, and they reinvest this value back into the energy costs needed to train them. Perhaps this dynamic gives proprietary models the performance distance they need in order to increase their margins.

Hasn't happened yet. It's not clear that it will happen.

Next time I read this take, I want to see eight to ten more paragraphs of analysis before it feels like a contribution to the discourse.

But don't we already have open source AI models which you can run on your own machine?

* Fully invested in those portfolio companies (no disclosures until IPO / acquired)

* Employees / Social Media Influencers at those companies with stock options which they are effectively paid boosters until they reach the vesting period.

* Frequently screaming the loudest and appearing on TV interviews, opinion articles spreading the scam further.

Just like the "Full Self Driving" scam that still requires a human behind the wheel, now we have "AGI" which still requires humans to supervise the AI agent to not make mistakes.

The tech folks don't question the euphoria and fall for it easily because they want to be on the next Google. But they could also be on the next Enron.

Only time will tell.