Best practices for managing multi-agent conversations with shared memory?

[ew251991-beep]

Hi everyone,
I've been experimenting with AutoGen for a multi-agent setup where several agents need to collaborate on a task and share context across turns. So far it's working well for simple two-agent conversations, but as I scale up to 3-4 agents, I'm running into some challenges keeping the conversation history clean and relevant for each agent without hitting context limits too quickly.
A few things I'm curious about:

Are there recommended patterns for summarizing or pruning conversation history in longer multi-agent sessions?
How do others handle scenarios where one agent's output needs to be selectively shared with only some of the other agents, rather than the whole group?
Any tips on debugging when agents start looping or repeating themselves?

Would love to hear how others have approached this, or if there are examples/docs I should look at that go beyond the basic tutorials.

[Charles (charlesedward23400-ui)]

This is an excellent discussion about managing multi-agent conversations with shared memory. Clear context management, efficient memory handling, and well-defined communication between agents are essential for building reliable AI systems. On a different note, I recently found a helpful Necklace Lengths Chart that makes it much easier to choose the right necklace length for different necklines, outfits, and occasions.

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