Anthropic's new "Agent Teams" feature moves beyond the single-agent paradigm by enabling users to deploy multiple AIs that work in parallel, share findings, and challenge each other. This represents a new way of working with AI, focusing on the orchestration and coordination of AI teams rather than just prompting a single model.

Early AI adoption by PMs is often a 'single-player' activity. The next step is a 'multiplayer' experience where the entire team operates from a shared AI knowledge base, which breaks down silos by automatically signaling dependencies and overlapping work.

Most AI tools are single-player experiences. Linear is designing its agent sessions to be shared, collaborative spaces. Multiple people, like a PM and a designer, can jump into the same chat with an agent, see its work, and give it feedback together, collapsing the collaboration loop.

The current generation of AI agents focuses on individual productivity. The next evolution will embed agents in shared team environments with common context and observable work, mirroring the collaborative nature of most knowledge work. This moves AI from a personal tool to a core team capability.

Using AI agents in shared Slack channels transforms coding from a solo activity into a collaborative one. Multiple team members can observe the agent's work, provide corrective feedback in the same thread, and collectively guide the task to completion, fostering shared knowledge.

The next frontier for AI isn't just personal assistants but "teammates" that understand an entire team's dynamics, projects, and shared data. This shifts the focus from single-user interactions to collaborative intelligence by building a knowledge graph connecting people and their work.

Surveys show up to 60% of knowledge work is "work about work": communication, coordination, and searching. While early AI focused on individual creation (the other 40%), the move to multiplayer agents in shared spaces targets this larger, collaborative overhead, promising massive efficiency gains.

OpenClaw's new "multiplayer" feature, allowing multiple users to interact with a shared agent session, is a leading indicator for the next wave of AI. Agents are moving beyond individual productivity to become shared, team-level assets, fundamentally changing how collaborative work is done.

The next wave of AI agents is moving beyond individual use ('single-player mode') to exist within shared team spaces like Slack channels. Tools like Claude Tag embed agents with full team context, transforming them from personal tools into collaborative resources that better mirror how organizational work actually happens.