Nathaniel Whittemore

So is this all just about money and the IPO?

The answer is yes, but.

And I think it's worth pausing to note how frequently the investor class cannot imagine that anything that any company does is not specifically and primarily about impressing them, the investor class.

What's actually going on here is the embodiment of a much bigger trend, and the instantiation and extension of what we have discovered are the most valuable categories of use cases for AI, which are simply put, not about chat.

Now, what's very clear is that there is a major difference between power users of ChatGPT and regular users of ChatGPT.

In a recent interview, OpenAI CFO Sarah Fryer said, our free users do about seven turns or seven questions a day.

Our first paid tier does double that, about 15.

Our real paid tier plus, which is $20, is about 3x, and pro is about 11x over a free user.

In other words, the power users are using AI more.

But they're not just using AI more, they're using it differently.

It's clear at this point that OpenAI views Codex as their most successful product.

At least their most successful product with the type of success that they want.

And anyone who's living on the AI side of X can attest to the fact that there has been a major vibe shift towards Codex over the last few months.

Developer Ben Holmes recently did a poll on Twitter asking how people use coding agents right now, with 51.1% of nearly 2,100 votes going to Codex app, with the next highest, 30.9%, being CLIs in the terminal.

We're in the midst of a widening AI advantage gap.

the gap between the value that power users are getting out of AI and that casual users are getting out of AI is increasing fairly dramatically.

Now, for most of the early history of post-chat GPT AI, while there was a differential between the value that power users were getting versus casual users, I'd argue that the space between them was relatively consistent.

Over time, casual users got more value and power users got more value, as they learned better in more use cases.

But then agents actually became a viable thing.

And specifically, people figured out that coding tools weren't just for software engineers, but for any knowledge worker who could use code and bespoke applications to solve their problems and create opportunities.