w/ larger context windows and long horizon tasks, designing goals that support self-verification and continuous learning from human evals becomes the real constraint
we need higher-level primitives that make feedback on those goals cheap and transferable so agents can keep improving without constant re-prompting
as agents move towards working on goals, it becomes important to design those goals correctly
wrote with @mgarimella on some lessons learned at actively!
