Topic

A2A

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Why Your AI Agents Can't Talk to Each Other (Yet) — Vlad Luzin, BAND thumbnail

· 17:13

Why Your AI Agents Can't Talk to Each Other (Yet) — Vlad Luzin, BAND

The future of AI requires multi-agent systems (MAS) that communicate seamlessly across different platforms and services. The speaker argues that current methods—such as using messaging apps (Slack, Telegram) or low-level protocols (MCP, A2A)—are insufficient because they are built for human interaction, not machine-to-machine communication. Connecting agents requires solving complex distributed systems problems, including real-time ordered transport, persistence, runtime binding, and robust governance. BAND introduces its interaction layer as a solution, enabling agents (like Claude Code and Codex) to onboard and collaborate in a stateful, observable manner across users and platforms.

Key takeaways

  1. The Future is AI-to-AI Communication

    The speaker asserts that the future involves autonomous, always-on AI agents communicating to solve tasks, moving beyond the current manual process of running multiple sessions (e.g., planning and reviewing).

  2. The Single-Agent Bottleneck 5:29

    Relying on a single agent, even with large context windows (1M or 2M tokens), suffers from architectural limitations like confirmation bias, attention dilution, and context fragmentation.

  3. Limitations of Existing Protocols 6:58

    Messaging apps are designed for humans and actively block bot-to-bot communication. Low-level protocols like MCP and A2A are too simplistic, often resulting in stateless calls or requiring complex client/server implementations, which fail to address discovery, state, or queues.

  4. The Distributed Systems Challenge 12:32

    Connecting remote agents is fundamentally a distributed systems problem requiring solutions for ordered, real-time transport; persistence and hydration (handling microservice failures); and runtime binding (mapping thread IDs to session IDs to execution IDs).

  5. BAND's Solution 16:57

    BAND provides a global interaction and collaboration layer that solves these complexities, offering a registry, persistence, and channels that allow agents from different platforms (e.g., Claude Code, Codex) to connect and interact in a stateful, observable manner.

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