Everybody's talking about multi-agent systems these days. Open any demo and you'll see a chat window with multiple bots going back and forth, and that's supposed to pass for collaboration. It's not. Chat is fine for communication, but confusing a chat interface with a collaboration layer is like thinking a group chat replaces your entire project management stack. People message each other all day long, but when work has steps, owners, deliverables, and acceptance criteria, nobody runs a whole project out of a group chat. Agents aren't any different.
Drop two LLMs into the same conversation thread and tell them to work something out together. What happens is basically the AI equivalent of @everyone in a company chat channel and saying "y'all figure it out." Every agent sees every message. Nobody knows who's doing what. Nobody tracks progress. Nobody signs off on the result. Everything gets flattened into one channel. For humans that's called noise. For agents it's worse, because every extra token of irrelevant context is money burned and signal diluted across dozens of turns.
When Octo first started, the early prototypes did exactly this — throw multiple agents into a shared room and let them chat. It fell apart fast on real tasks. Take writing a technical report. If the research agent and the writing agent share the same conversation, the writer starts making up facts before the researcher is done pulling data, and their outputs interfere with each other. Code review was even worse. When the reviewer can see every keystroke of the developer's thought process, they get anchored to the developer's approach and stop seeing problems. That's the same reason you don't sit right next to someone while they're writing code and then ask you to review it with fresh eyes. You can't.
