I find this part the most interesting: "Since then, my focus has been on AI research, and part of that involves the design of planning systems that (maybe) can

I find this part the most interesting: "Since then, my focus has been on AI research, and part of that involves the design of planning systems that (maybe) can eliminate the need for most programming. You tell them what you want, as you might describe it to a smart grad student, they maybe ask some clarification questions, and then they go do it. That only works if they know enough about the world and have enough "common sense" to avoid blunders." I wonder what he's working on to enable that kind of environment. Thinking about how most of the programming I do (in high level languages) comes down to starting with a pretty rough idea and iterating on the idea while learning more about what's feasible / effective, typically refining what it is I'm building rather fluidly. I rarely know exactly what to build upfront, nor do the CEOs, product managers, designers or sales people I've worked with so far. I think this feed back loop goes far beyond "asking a few clarifying questions". Maybe the kind of task a professor would give to a grad student is entirely different from that kind of typical industry work?