It’s very tempting to imagine that AI turns everyone into a tool-builder - now everyone can just ask the model to make the software they need, and apps as we know them are dead. I think that misunderstands how most people think and where software actually comes from, and more importantly, it isn’t a path to change how companies actually work.

AI is in a supply crunch today, but what happens when we come out of it? How and where will supply, demand, price, capacity and capex get back into equilibrium? Today, model labs can name their price, but why won’t they end up as low-margin commodity infrastructure?

Many people would like to analyse which jobs, companies and industries are most exposed to AI, and assign scores, build charts, and map that against the progress of LLMs. I think this is mostly impossible: you don’t know how the jobs will change, you don’t know what else will change around this, and you can’t measure work like that anyway.

OpenAI has some big questions. It doesn’t have unique tech. It has a big user base, but with limited engagement and stickiness and no network effect. The incumbents have matched the tech and are leveraging their product and distribution. And a lot of the value and leverage will come from new experiences that haven’t been invented yet, and it can’t invent all of those itself. What’s the plan?

How far do LLMs give us a step change in how good a search and recommendation system can be? Do they let you build one without needing a vast user base of your own?