Well, the first cracks in the AI ​​economy are now becoming visible. A couple of significant events involving Anthropic and Microsoft have taken place over the last few weeks—if you follow the industry, you’ll find this interesting.

So, here’s the breakdown:

In marketing, there is a concept known as the “painted door test.” It involves gauging market reaction without actually altering the product itself.
You might add a button for a new feature, but when clicked, it merely displays a message stating that the feature is “coming soon.” Crucially, however, you track exactly how many times that button gets clicked.
Anthropic did something similar in April 2026. Two percent of their paying users—those on the $20/month plan—saw a notification stating that Claude Code (their most in-demand product) would henceforth be available exclusively on the “Max” tier, priced at $100/month.
A number of users actually upgraded to the more expensive subscription, unaware that the whole thing was merely a test.
Ultimately, due to the public outcry, Anthropic reverted everything to its original state; however, the company’s pockets are clearly not bottomless. Maintaining powerful models—such as Opus 4.7—comes at a very steep cost.
Now, let’s turn our attention to Microsoft, which recently announced that, effective June 1, 2026, GitHub Copilot will be switching to a token-based pricing model.
Simply put, the cost of a session will now depend on the computational power of the underlying model being utilized, rather than on the sheer number of queries submitted. Not all queries are created equal anymore.
Personally, I find this approach logical—though many developers beg to differ, largely because the previous pricing tiers were incredibly wallet-friendly. (Heh.)
Microsoft revealed that their weekly operational costs for supporting Copilot have doubled since the beginning of 2026 and continue to skyrocket. The company has been compelled to take action—even though, unlike Anthropic, Microsoft is a fundamentally profitable enterprise with ample financial reserves and liquidity to draw upon. Interestingly, Google currently finds itself in a winning position; the company invests over $100 billion annually in AI while remaining profitable—it doesn’t have to “dance” for investors just to secure new funding rounds, unlike OpenAI or Anthropic.
Oh, and by the way: a couple of weeks ago, OpenAI raised $120 billion in investment—capital that will last them only 18 to 24 months, as they are burning through $5–7 billion per month at their current operational loads.
This explains the aggressive marketing tactics employed by AI companies—including their constant claims that programmers are no longer needed, and so forth. Their primary objective is to attract capital, not merely to sell a product.
Yes, tokens are indeed ceasing to be free. And this marks just the beginning of the AI ​​industry’s transition toward realistic pricing models.
Cherish this moment, friends: right now, accessing high-level artificial intelligence is cheaper than it has likely ever been—or ever will be—in human history.
Furthermore, I would advise keeping an eye on projects focused on the decentralization of AI—initiatives that are actively pushing back against the monopolies that are already beginning to emerge. And if you were just thinking, “But what about the Chinese? They have free models! They’ll save us all!”—ho-ho, don’t be so naive!
I’m willing to bet that this year will be the very last year we see large-scale, high-performance open-source AI models coming out of China.

That’s the situation, folks.