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It's been my experience too, already prior to support for sub-tasks/agents.

I've been exploring the ways in which I could "lazy load" context depending on the task at hand. I've approached this by defining an AI "receptionist", a set of roles and a set of tasks.

The receptionist is the entrypoint of the system. It knows where to find roles/tasks but only loads very basic information about the roles.

Depending on the role I ask for, it then loads the right role file, which in turn loads additional context. Then I ask for whatever i want to do, and it loads specific task files based on what I asked. And the task files load additional context etc.

This works quite well because I end up with just the right context for the task at hand. And each role/task can actually be executed as a sub-task/agent



You stumbled on to the solution before the tools caught up to you. really cool.




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