I watched the I/O keynote this year and the live blogs all covered it as a product event. TPUs, a new model, a search redesign, an agent. I think they missed what actually happened. Every announcement was scaffolding for a single thesis: reactive software is ending, always-on agents are the new default. Three numbers from the keynote that each prove something different: 3.2 quadrillion tokens processed monthly across Google’s AI surfaces. That’s an existing user base already converted to generative AI consumption at a scale no competitor has. $180-190B in 2026 capex, roughly 6x what they spent in 2022. The infrastructure barrier for frontier AI is now structurally out of reach for all but two or three companies. Under $1,000 to build a working OS using a swarm of 93 subagents (a demo claim that deserves heavy skepticism, which I get into). The argument I land on: Google owns all six layers of the stack end-to-end. Silicon, model, developer harness, distribution, the proactive agent, and a physics-aware media model. Every competitor has at least two of those layers outsourced. Microsoft and OpenAI are the only plausible challengers inside 18 months, and the gap is silicon maturity. The cheap fast model (3.5 Flash) now beats what was the flagship a quarter ago, which is what a real production data flywheel looks like. I also wrote a whole section on why I might be wrong. The demos were demos, Google’s agentic track record is uneven (Astra), and “built an OS from scratch” is doing a lot of work in that sentence. Curious where this group lands on the 18-month question. Is the silicon lead actually decisive, or does it get arbitraged away by Nvidia’s roadmap faster than I think? Full piece if useful: The Day Google Stopped Selling Software submitted by /u/ash1794
Originally posted by u/ash1794 on r/ArtificialInteligence