I’m a DIY (or, less generously and not altogether inaccurately, NIH) type who thinks he could do a good job of smarter context management. But, I have no particular reason to know better than anyone else. Tell me more. What have you seen? What kinds of approaches? Who’s working on it?

I'm optimistic most people can, given the time and resources

In the CCC video, you may enjoy the section on how we are moving to eval-driven AI coding for how we more methodically improve agents. Even more so, the slides before on motivating why it gets harder to improve quality as you go on.

One big rub is it's one of those areas where people grossly misunderestimate what is needed for the quality goals they're likely targeting, and if a long-living artifact to be maintained, the on-going costs. It's similar to junior engineers or short-term contractors who never had to build production-grade software before and haven't had to live with their decisions: These are quite learnable engineering skills, and I've found it useful to burn your fingers before having confidence in the surprising weight of cost/benefit decisions. The more autonomy and expectations you are targeting for the agent, the more so.