WRT “Claude learns over time” - this is the biggest gap for me in the current system. As I scale my usage of Claude at work, I observe that it’s quite bad at distinguishing what it should “learn” (memorize) from experimental or just wrong data. It builds and builds on a foundation of sand, making sometimes hidden assumptions and turning them into actionable insight thats just not correct.

It recently wrote an entire dissertation for an epic, assuming it was related to some other project, where it had earlier made the wrong guess about a vendor capability (from their marketing materials, no less), and it all had to be thrown away. I cleared the memory, but it appears to be still pulling from some corporate data source i cant control or locate.