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Most AI demos work great… until you try to run them in production.
Long-running tasks time out.
Retries break workflows.
Queues become a nightmare.
That’s exactly the problem Trigger.dev is solving.
It’s an open-source platform for building AI agents and workflows in TypeScript, designed to handle the messy reality of production systems like retries, queues, long-running tasks, and scaling.
Instead of wiring together fragile scripts, you can build durable AI workflows directly in your codebase.
Example concept:
You want an AI research agent that:
1. Takes a topic
2. Searches the web
3. Analyzes sources
4. Generates a report
5. Streams results to your UI
With Trigger.dev you can orchestrate that as a single task, with retries, logging, and real-time updates built in.
What makes it interesting for devs:
↳ TypeScript-first → fully type-safe agent logic
↳ No timeouts → long-running AI jobs actually work
↳ Real-time streaming → pipe LLM responses directly to your frontend
↳ Agent orchestration → prompt chains, routing, parallel tasks
↳ Runs your existing tools → Python scripts, browser automation, FFmpeg, and more
In other words:
You focus on AI logic.
The platform handles infrastructure, scaling, and reliability.
If you're building AI products in Node or TypeScript, this is worth checking out: fandf.co/4rmbopJ
—
Thanks to @triggerdotdev for sponsoring this post.

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