There's a growing divide in AI, and it's getting harder to ignore. On one side, you've got OpenAI snapping up finance apps and talk shows like they're building an empire. On the other, regular people are just trying to figure out what any of this means for their jobs.
The spending patterns tell the story. While most companies are still figuring out basic ChatGPT use cases, the big labs are making moves that suggest they see a very different future coming. A shoe company rebranding as an AI infrastructure play is the kind of thing that happens when money starts chasing a trend hard.
Then there's Anthropic's latest model, which they're calling too powerful for public release but apparently fine for select partners. That's the kind of gatekeeping that widens the gap even further. If you're not in the inner circle, you're working with yesterday's tools.
This matters because the people building AI tools are operating with information and capabilities the rest of us don't have access to. That asymmetry affects everything from which skills stay relevant to which companies survive the transition.
The vocabulary is shifting too. Terms like "tokenmaxxing" are emerging from power users trying to squeeze every bit of performance from these systems. It's the kind of jargon that separates people who live in this world from people who just use the tools.
For anyone using AI in their work, the takeaway is simple. The gap between what's possible and what's publicly available is growing, not shrinking. Staying competitive means paying attention to what the insiders are doing, not just what's in the marketing materials.
