Compute is the binding constraint now, even for the giants.

Google reportedly capped Meta's access to Gemini models after Meta asked for more capacity than Google could supply, delaying some of Meta's internal work (BuildFastWithAI). Same week, TSMC posted record Q2 revenue of ~$39.62B, up 36% year over year, and pinned it directly on AI demand. Put those together and the throughline is clear: it's not talent or capital that's scarce at the frontier, it's raw compute, and even Meta with its budget can get rationed. Cross-lab model access just became a scarce resource you can't assume. If your product depends on a single hosted frontier model, that dependency is more fragile than the SLA suggests.