Picture an AI agent subscribed to a real-time event stream, calling a large language model on every event that arrives. Over a weekend, across hundreds of thousands of events, it quietly burns through hundreds of dollars. Nothing is technically wrong: every event is valid, the agent is authenticated, and no alert fires, because every existing check was designed to monitor infrastructure, not how an autonomous agent consumes a stream.

As autonomous agents become primary API consumers, event streams are where this shift bites hardest. Developers build agent systems on raw event streams and they work. But in production, three things break. Agents can't discover what channels exist without hardcoded configurations. Any agent can subscribe to any topic because there's no channel-level access boundary. And there's no visibility into what each agent is consuming or what it costs when a high-throughput stream triggers LLM calls on every event.

This talk proposes three questions that define an agent-ready event platform: Is it discoverable? Is access scoped? Is consumption observable? This talk uses a primary scenario of agents consuming a WebSocket stream backed by Kafka to show what AsyncAPI v3 provides: describable channels, schema contracts, and security documentation that your gateway layer can enforce. We walk through a real spec snippet. We cover the governance patterns that address the failure modes above, what exists in tooling today, and what still requires custom implementation. And we look at where AsyncAPI fits alongside MCP and OpenAPI in the emerging agent stack.