We’re introducing new APIs for connecting agents to realtime rooms and a new Feeds primitive. This unlocks new workflows where agents can act as native users of software.
Join thousands of companies using Liveblocks to build multiplayer experiences for people and agents.
AI agents are becoming native users of software, and today’s launch is about making that shift easier to build for. We’re introducing new building blocks for collaborative AI workflows: new APIs for connecting agents to realtime rooms and a new Feeds primitive. This unlocks new workflows where agents can act as native users of software.
Rooms are the core collaborative space in Liveblocks. They’re where people already work together in realtime, and starting today, agents and back end systems can participate more naturally too. We’re shipping new APIs that make agents feel like first-class collaborators inside a room, rather than something bolted on from the outside.
With ephemeral presence, an agent can now appear live in a room with a name, avatar, and custom presence data. That means your product can show what an agent is doing while it works, just like it would for a human collaborator.
To use it, call
setPresence
and pass your AI’s information and presence data.
We’re also introducing support for JSON Patch in our open-source sync engine, Liveblocks Storage. This is a powerful primitive which lets agents update your realtime data using a simple, structured format.
It works especially well for AI because it is easier and quicker for a model to generate a set of targeted changes than to rewrite an entire object.
Learn more in our guide on modifying storage data with JSON Patch.
Agents can now also read and analyze comment attachments, which opens the door to richer workflows where agents process files, leave contextual feedback, and work directly inside existing collaboration flows.
This is made possible with our new
getAttachment
method.
Together, these APIs make it possible for agents to work inside the same collaborative surface as the user. That is the real shift.
We’re also introducing Feeds, a new primitive for storing things like chat messages and agent activity logs.
As agents become more active, products need more than a prompt box. They need a timeline of what happened around the work itself. Feeds gives you a structured place to store things like chat messages, agent logs, and workflow events, all tied to the room where the work is happening.
Feeds contain lists of messages which update in realtime for all connected
users. In this Node.js example, we’re sending a status message to an existing
feed with
createFeedMessage.
On the front end, we can show this message in our UI as soon as it’s created.
This works using the
useFeedMessages hook;
it returns all messages in the feed, and automatically updates whenever a new
message is sent.
Once agents start updating state, leaving comments, or triggering workflows in the background, products need a clean way to store and display that activity. That is what Feeds is for.
We’ve set up a Feeds example that uses a workflow to analyze your comments and leave a response. Each realtime update you see (e.g. “Thinking…”, “Writing…”) is a new feed message sent from the back end.
Try it out by tagging @AI Assistant in a comment and asking a question.
Our AI Comments example
Alongside feeds, this example also uses:
To get started with Feeds, follow our new quickstart guide for Next.js.
Get started now
These building blocks make a new class of workflows possible. A user can @ mention an agent in a comment thread to trigger a workflow. The agent can review the context, update the document, and reply in the same thread. A user can also trigger an agent from outside the product, like in Slack or Microsoft Teams, to start a back end workflow connected to a Liveblocks room.
Agents are becoming native users of software. They need to be able to act as a user would, in context, on shared data, alongside people. We're building the building blocks to make this possible in any product.
Contributors include:
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