The Narrative Everyone Accepted Without Questioning There's a story the AI industry has been telling itself for the past few years, and it goes something like this: bigger is better, and the biggest wins . More parameters. More data. More compute. The leaderboard rewards scale, venture capital rewards scale, and so the entire field marches in one direction — upward. But spend enough time in the trenches — dealing with real deployment constraints, real failure modes, and real questions about who controls what — and this narrative starts to look, at best, incomplete. What if scaling up is only half the story? What if the other half — scaling out — is not just a fallback for teams who can't afford the big model, but a fundamentally different architecture that solves problems the monolithic approach structurally cannot? The Internet Is Changing at the Infrastructure Level Here's something that doesn't get discussed enough: the internet itself is undergoing a quiet paradigm shift.…