🦔Microsoft canceled its internal Claude Code licenses this week after token-based billing made the cost untenable, even for a company with effectively infinite cloud resources. Uber's CTO sent an internal memo warning the company burned through its entire 2026 AI budget in just four months. American AI software prices have jumped 20% to 37%, and GitHub (owned by Microsoft) is dropping flat-rate plans for usage-based billing across its products. My Take The AI subsidy era is ending in real time. The same company that put $13 billion into OpenAI and built the Azure infrastructure powering most of Anthropic's compute just looked at the bill from a competitor's coding tool and decided it was not worth paying. That is not a productivity failure on Anthropic's end. Token-based pricing is forcing every enterprise customer to confront the actual cost of running these models at scale, and the number turns out to be far higher than the flat-rate experiments suggested. This ties directly to my Gemini Flash post yesterday. Anthropic, OpenAI, and Google all raised effective prices in the last six months. Enterprises that built workflows assuming AI costs would keep falling are now watching annual budgets evaporate in months. Two outcomes look likely from here. Either enterprises scale back AI usage to fit budgets, which slows the revenue ramp the labs need to justify their valuations ahead of IPOs, or the labs cut prices and absorb the losses, which makes the unit economics worse at exactly the wrong moment. Both paths land in the same place, the numbers stop working, and somebody has to take the writedown. Hedgie🤗

🦔 A creator is running 150 TikTok accounts with just three interns, all posting AI-generated videos. The setup uses racks of phones running automated content generation and posting. One account alone showed a $7,000 payout request. My Take Engagement farms aren't new. They've been a huge industry for over a decade, particularly for social manipulation and content theft. What's changed is the economics. Previously you needed people to steal and repost content, or create something. Now three interns can manage 150 accounts because the content generates itself. This is where the AI video tools we keep covering end up. Not just deepfakes of celebrities or one-off viral clips, but industrialized slop production running 24/7. The platforms pay out based on engagement, and the algorithms don't distinguish between content a person spent hours making and content a script churned out in seconds. So the incentives push toward volume over quality, flooding feeds with generated noise. The creators making actual content are now competing against operations that can produce thousands of videos per day at near-zero marginal cost. I don't know how that competition ends well for them. Hedgie🤗