I’m building an AI-native product and the hardest problem hasn’t been the tech, it’s the pricing model. For the last few decades the SaaS model was effectively: “Make something that you build once and can sell again and again at 0 marginal cost with monthly subscriptions” AI products don’t have that luxury. Every interaction uses tokens. Tokens use energy & cost money. Light & power users burning tokens at different rates in the same pricing tiers is an analysts nightmare. So what’s the solution and right pricing model? TAAS: “Software that adds value to tokens and is resold directly to users as a service.” AI video creation, research tools, chat bots. They are all effectively placing a value layer over an API key and selling the tokens for massive markups. The extent to which a company can add value to an AI token is the extent to which they can markup their service. And ironically the way to do that is to lean 90% into software and 10% into AI. You want to offload as much of the costs of value delivery onto free executable code and use AI tokens as sparingly as possible. The application that throws AI bluntly at a solution will fail. The application that effectively solves the problem with code and uses AI to make it magical as a layer above will succeed. submitted by /u/DavidCBlack
Originally posted by u/DavidCBlack on r/ArtificialInteligence