I wrote this after running a forensic analysis on the unit economics of current frontier models. The underlying math looks structurally identical to the collateralized debt loops of 2008. The hyperscaler revenue is effectively the CapEx of the startups they are funding. Happy to debate the mechanics of the round-tripping here.

I'd suggest starting with citations, you have zero right now.

Then move on to visuals after that.

Token velocity is great, but the industry is hyper-fixated on speed while completely ignoring the blast radius. If we push to 17k tokens/sec for autonomous agents, we are just accelerating how fast an agent can hit an infinite loop and drain an API budget. Before we make AI ubiquitous, we need deterministic, network-level circuit breakers. Speed without governance is just a faster way to burn capital.

This was the inevitable endpoint of the current AI unit economics. When inference costs are this high and open-source models are compressing SaaS margins to zero, companies can't survive on standard subscription models. They have to subsidize the compute by monetizing the user's context window. The real liability isn't just ads; it's what happens when autonomous agents start making financial decisions influenced by sponsored retrieval data.

Thing is there are OSS models that are near as good. So I don’t see why you’d stay for ad flop when you can just point openrouter one to the left.