Cédric Lion

🦔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🤗

Introducing Open Collider: an open-source engine that mechanically improves LLM creativity. It generates non-trivial, high-quality ideas at scale, for any ideation problem. LLMs collapse on the same ideas. Sample the same brief 100 times → most outputs land in the same place. Researchers call it the Artificial Hivemind (Jiang et al., 2025). "Be more creative" moves the LLM's output by ~0.04 in embedding space. Forcing structurally distant domain collisions moves it by ~0.28. 7× more. Same model, same brief. So I built Open Collider: a pipeline based on the theory of bisociations (Koestler 1964), the same model that drives human creativity. 📊 Across 12 real-world ideation problems: •⁠ ⁠12/12 sign-test wins on embedding distance (p = .0002) •⁠ ⁠60%+ originality wins on 4,320 blind LLM-judge verdicts •⁠ ⁠4–13× further from the default cloud than "be original" prompts or longer context •⁠ ⁠Idea relevance holds (win rate >50% on overall quality) 💻 Engine: first reply 👇 📝 Launch study: pinned tweet Try it, Break it, Tell me what you find!

If you are a mathematician, then you may want to make sure you are sitting down before reading further.