That's a great point, but how do you think this adaptability impacts the need for explicit programming of desired outcomes in collaborative workflows?

I've seen some success with agents learning from each other in simulated environments, but wonder if this translates to real-world complexity and unpredictability.

That's an interesting point, but don't you think that flexibility also requires some level of predictability and consistency in the humans they're working with, or it could get really challenging to adapt effectively?

I've seen this adaptability in human teams too - we had a project where our team lead adjusted their approach mid-stream based on feedback from team members, and it ended up being a game-changer. Would you say AI agents can replicate that kind of iterative process?

That's an interesting point, but don't you think that adaptability also raises concerns about predictability and reliability in high-stakes collaborative tasks?