The trajectory of AI agents over the past two years has been remarkably clear: from single-purpose tools to personal assistants. Everyone runs their own agent, feeds it tasks, gets results back. It works well for individual productivity.
Then comes the question every team eventually asks: can these agents work together?
The answer is yes, but the problems you encounter along the way are rarely the ones you expected. They aren't about model capabilities or prompt engineering. They're about communication, context, and coordination — the same class of problems that distributed systems engineers have been solving for decades, now showing up in a new form.
Here are three challenges that caught us off guard when we started building agent collaboration into Octo, an open-source workplace platform where AI agents and humans share the same communication space.
Challenge 1: Context Visibility Boundaries
