Do AI Agents Have Group Chats?

When people picture AI agents working together, they often imagine a quiet exchange of private messages, one agent asking another for help and waiting for a reply. That picture is real, but it is only half the story. Increasingly, agents do not just message one another one-on-one. They gather in shared conversations that look a great deal like the group chats on your phone, and the difference matters more than it first appears.

The most common way agents coordinate today is through a central orchestrator. A single manager agent holds the conversation and delegates pieces of work to specialists, collecting each result and deciding what happens next. Frameworks such as LangGraph and CrewAI lean on this hub-and-spoke design, where the workers rarely talk to each other directly and may not even know their peers exist. It resembles a project manager running a row of separate private threads, forwarding the relevant parts between them. The arrangement is orderly, and that order is much of its appeal.

The genuine group chat exists too, and here the comparison to WhatsApp is almost literal. Microsoft's AutoGen includes a construct named, plainly, GroupChat, in which several agents share one conversation while a manager decides who speaks next. Every participant reads every message, exactly as everyone in a group thread sees the whole history. Other systems build debate chambers and committees, where agents argue toward a consensus in a common transcript rather than reporting privately to a boss. When several minds can see and respond to the same running dialogue, new behavior becomes possible. Agents build on one another's ideas, catch one another's mistakes, and reach conclusions no single agent would have found alone.

The most consequential shift is that these conversations are moving out of individual frameworks and onto open protocols. Google's Agent2Agent protocol, usually written A2A, was introduced in 2025 so that agents built by different companies, running in different systems, can discover and talk to one another over a shared standard. Anthropic's Model Context Protocol does something complementary, standardizing how an agent reaches out to tools and data. Together they form the connective tissue that lets agents from separate organizations join the same interaction. Once that happens, the group chat stops being a tidy in-house feature and becomes something closer to a public channel that strangers can enter.

That openness is exactly why the shape of the conversation is not a mere technical detail. It determines how influence, and trouble, travel. In a strict one-on-one system, a misbehaving agent can mislead the orchestrator, but the manager in the middle acts as a checkpoint that contains the damage. In a shared group chat, a single message is read by everyone at once, so one compromised or manipulated agent can attempt to steer all the others in a single turn. Malicious instructions hidden in one agent's output can replicate into the shared transcript that every participant consumes, spreading the way a rumor races through a group thread. Security researchers have begun cataloging these cross-agent infections precisely because shared and cross-vendor channels are multiplying, and the collaborative power that makes group chats useful is the same property that makes them efficient at spreading anything harmful.

So do agents chat one-on-one or in groups? Both, and the field is steadily drifting toward the group end of the spectrum. Private delegation remains common and relatively contained, while shared and open conversations grow more capable and more exposed at once. The organizations building on agents will need to treat these gatherings the way we treat any group chat that outsiders can join, as spaces where collaboration and risk arrive together.