Trigger.dev launches AI chat

Introducing chat agent from Trigger.dev

Why chat.agent is better
Most chat backends tie the work to the request, and a normal API endpoint is a poor fit for a chat agent (or any agent, but that's another story).

Request/response cycles normally have timeouts and are stateless. You have to fight this by writing everything to a database, using Redis for durable streams, and queueing slow work to a background worker you then have to coordinate.

Good luck if your model takes longer to answer than your function is allowed to run. Or if something fails and you want to retry it. Or if you want to spawn a sub-agent that does its own thinking. Or if you want to close the browser and come back days later.

A stateful machine is a much better fit:

A real Linux machine. Install what you want, run any CLI, pick the CPU and RAM.

Durable compute, durable streams. No timeout on a turn. A conversation you can close and come back to days later.

Fast first turns. The first LLM call runs in your own warm server while the agent boots alongside it, so durable doesn't mean slow.

Waiting costs nothing. An agent can stop, ask a person to approve something, and sit there for days without running up a bill.

Tracing and metrics built in. Every turn is a span, and there’s an AI metrics dashboard for cost, tokens and latency.

And it uses the AI SDK you probably already use.