And in addition to being the first AI product that we'd use that was useful, Code Pilot was also one of the most useful, if not the most useful dev tool we'd ever adopted, and that got us really excited. Another moment that got us really excited was the series of scaling on papers coming out of OpenAI and other places that showed that even if we had no new ideas, AI was going to get better and better just by pulling on simple levers, like scaling up the models, and also scaling up the data that was going into the models. And so at the end of 2021, beginning of 2022, this got us excited about how AI products were now possible, this technology was going to mature into the future. And it felt like when we looked around, there were lots of people talking about making models, and it felt like people weren't really picking an area of knowledge work and thinking about what it was going to look like as AI got better and better. And that set us on the path to an idea generation exercise, it was like, "How are these areas of knowledge work going to change in the future as this tech gets more mature? What is the end state of the work going to look like? How are the tools that we use to do that work going to change? How are the models going to need to get better to support changes in the work? And once scaling and pre-training ran out, how are you going to keep pushing for technological capabilities?"
Another moment that got us really excited was the series of scaling on papers coming out of OpenAI and other places that showed that even if we had no new ideas, AI was going to get better and better just by pulling on simple levers, like scaling up the models, and also scaling up the data that was going into the models.