Make your own event-sourced agent harness using stream processors — Jonas Templestein, Iterate
Key Takeaways
Building an event-sourced agent harness using stream processors
Original Description
The abstraction is three things: state, a synchronous reducer that derives state from events, and an after-append hook for side effects. The split matters: when your program restarts after 100 events, you want to catch up state without replaying LLM requests. Everything that happens (streaming chunks, tool calls, errors, circuit breaker triggers) is an event in the log.
The interesting part is deployment. Jonas demos "dynamic worker configured," an event whose payload is a JavaScript string containing a processor. Append it to any stream and that stream becomes an AI agent without server or dependencies. The broader implication: processors from different authors on different servers can compose against the same stream, and a safety checker can inject context in a 200ms window before an LLM request without blocking the agent if it doesn't make it.
Speaker info:
- https://x.com/jonas
- https://www.linkedin.com/in/jonashuckestein
- https://github.com/jonastemplestein
Watch on YouTube ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: Agent Foundations
View skill →Related Reads
📰
📰
📰
📰
How to Use AI APIs Without Giving Up Your Privacy
Dev.to AI
AlterLab vs Apify: Best API for AI Agent Data Pipelines
Dev.to · AlterLab
Kevin Weil joins Stoke Space: why AI money is chasing rockets
Dev.to · Induwara Ashinsana
Why we're building PotenAI with adaptive AI instead of static assessments
Dev.to · Abdullah Huseynli
🎓
Tutor Explanation
DeepCamp AI