Why WebSockets Beat SSE for AI Streaming at Scale
Ably Realtime
SSE can stream AI text one way, but it can’t take a reply back mid-stream. That’s why approvals, cancels, and tool-call steering push teams toward WebSockets or managed messaging.
Based on reporting by Ably Realtime — read the original for the full story.
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A refund flow is a good way to see the problem. The agent has already pulled the order and flagged the tool call, but the user still has to approve it. With Server-Sent Events, that approval has nowhere to go on the same connection, because SSE only carries data from server to client. A WebSocket keeps the line open in both directions, so the approval can come back while the response is still in flight.
That’s the real divide here. WebSockets don’t just help with chatty UI updates. They let the client cancel a response, approve a tool call, or steer an agent without bolting on a separate HTTP request for every extra signal. They also keep messages ordered on one connection and handle binary frames natively, which matters once AI streaming includes audio chunks or structured tool data.
SSE still has a place, but it’s a narrower one. A single-turn assistant with no cancellation, no escalation, and no multi-device requirement can live with one-way delivery. The moment the interaction becomes bidirectional, though, the protocol runs out of road. That’s why frameworks built on SSE hit the same ceiling: Vercel AI SDK’s default transport, FastAPI’s StreamingResponse pattern, and LangChain’s streaming callbacks all inherit the same one-way model.
But WebSockets only solve the direction problem. They do not give you reconnection, fan-out, or delivery guarantees for free. If a connection drops mid-token or mid-tool-call, your app has to recover state. If the same session appears on a second device, you need your own layer to fan messages out. And if you care about exactly-once delivery or ordering across channels, you still have to build that yourself.
Self-hosted tools like Centrifugo and Socket.IO reduce some of that work. They bring client reconnects and pub/sub across nodes, but the broker and cluster still belong to your team, along with patching, on-call, and the rest of the maintenance grind. The article’s cost figures make the trade-off pretty blunt: building it yourself is slow, expensive, and easy to turn into a full-time hobby nobody asked for. Managed platforms like Ably are trying to sell the boring part back to you as a service, with delivery guarantees, uptime commitments, and compliance paperwork already in place.
My take — AI-written commentary, not fact-checked reporting
This is one of those cases where “we can probably wire it ourselves” is code for “someone will become the websocket janitor.” Open systems are great until the broker, retries, and failover start eating the product team alive. If an AI product needs live approvals and multi-step back-and-forth, the cheap option is often the expensive one in disguise.
Read more about this at: Ably Realtime