This has been my best way to learn, put one agent on a big task, let it learn things about the problem and any gotchas, and then have it take notes, do it again until I'm happy with the result, if in the middle I think there's two choices that have merit I ask for a subagent to go explore that solution in another worktree and to make all its own decisions, then I compare. I also personally learn a lot about the problem space during the process so my prompts and choices on us sequent iterations use the right language I need to use.