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Microsoft recently announced major pricing changes for GitHub Copilot — changes that were drastic enough that a Reddit user said their company has started calling it the Tokenpocalypse.
On the latest episode of TechCrunch’s Equity podcast, Kirsten Korosec, Sean O’Kane, and I discussed what those changes might mean for the larger AI ecosystem. After all, as Anthropic and other big AI companies plan to go public, leading to awkward questions about profitability, we’re likely to see similar price increases for other AI products, and more usage restrictions as businesses try to keep costs under control.
“Can these AI labs collapse that cost [and] progress the tech enough in a way that it eventually meets in the middle with customers’ appetite for spending?” Sean wondered.
Kirsten, meanwhile, suggested that this also reflects “how quickly things are moving.” In just a few months, companies became obsessed with “tokenmaxxing,” then turned against it due to the high costs. So as AI companies write their IPO filings, she asked, “How do you even write these risks in, because they are evolving before our eyes?”
Keep reading for a preview of our conversation, edited for length and clarity.
Anthony: When we were planning for this, Sean, you called this the Tokenpocalypse. And I want to hear more about what you think about it, but there was an example of Microsoft deciding with GitHub Copilot that they’re going to start charging more per token [instead of a flat rate].
This whole ecosystem is heavily, heavily subsidized by investor money. And so stuff that seems like it has no cost is, in fact, incredibly expensive. And now we’re going to get to a point where more of that cost is going to get passed on to the end consumer, to the customer. How is that going to change behavior? I don’t think we know, but there’s going to be a lot of pain.
Sean: I mean, how many token-related risk factors do we think are going to be in Anthropic’s S-1? This is a big question. It’s something that I’ve mentioned a lot on this show and we seem to just keep running into it, where Uber has done like the full arc in the span of a month and a half of saying, “Boy, we kind of blew through our budget on this stuff way quicker than we thought this year.” And then, “Ooh, maybe this is going to be a little too expensive, we need to put caps on this, and we need to limit people’s usage inside the company.”
That’s just a little worrying. Imagine if you see that happen so quickly at a company like Uber, that is using this stuff a lot, and it’s just a question of: Can these AI labs collapse that cost [and] progress the tech enough in a way that it eventually meets in the middle with customers’ appetite for spending?
A funny thing to think back on is, I don’t think there was really any strategy involved in charging $20 a month [for ChatGPT Plus] when ChatGPT originally came out. It was just sort of like, “Let’s spit out a number.” And we’ve all been reckoning with that ever since. Clearly, people pay more for the more advanced models, but even that still isn’t enough to close that gap to the true cost. So that’s clearly the biggest question here.