I had primarily the issue, that when working only on one task at a time, I had nothing to do, when my AI was thinking or implementing a plan.
Just launching multiple AI instances does not scale because you loose the overview an context of each task. Also you need git worktrees to isolate the agent from each others work.
My solution was a tool around VSCode, handling worktree creation and notifications for idle agents. A MCP which can interact with VSCode allows the agent to prepare any outcomes for preview or show a notification what to test or to do next. That way I cycle through agents answer the questions it has or review its work. I regularly work with ~5 parallel task (sometimes up to 10).