heoretically, we should have a stellar AI agent for every problem in our lives by now. The talent is there, the capital is certainly there, and the models are increasingly capable. And yet, the results are lopsided. Why is it that we have agents that can prospect for sales leads and answer support tickets accurately, but we don’t seem to be able to consistently generate high quality slides?The simplest explanation might be complexity. Easier problems (e.g., answer a support question) naturally get solved first, and more open-ended problems like slide generation require more effort. That doesn’t quite hold up: Coding is obviously not a simple application area, and yet coding agents are some of the best that we have today – in fact, they are improving faster than any other single agent use case.How did this happen? Ease of adoption enabled data collection at scale that in turn helped coding agents improve rapidly.Every developer could switch to Cursor in 5 minutes without any approval. That created a data flywheel (more on this below) that allowed the Cursor team to build a better application experience over time