Make your own event-sourced agent harness using stream processors — Jonas Templestein, Iterate

AI Engineer · Beginner ·🤖 AI Agents & Automation ·55m ago
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

Related AI Lessons

Publish your AI agent as a paid callable tool — passive USDC income
Learn to publish your AI agent as a paid callable tool to generate passive USDC income
Dev.to · x711io
Microsoft Copilot Studio Multi-Agent Runtime | Orchestration, Identity and Governance at Scale | R.A.H.S.I. Framework™ Analysis
Learn how Microsoft Copilot Studio's Multi-Agent Runtime enables orchestration, identity, and governance at scale using the R.A.H.S.I. Framework
Dev.to AI
I Built the Missing Trust Layer for AI Agents on Base (Stake, Escrow, Reputation, Discovery)
Learn how to build a trust layer for AI agents using stake, escrow, reputation, and discovery mechanisms
Dev.to · Grandionn
Structured Output in .NET Agents
Learn to implement structured output in .NET agents for more effective automation and integration
Dev.to · Lukas Walter
Up next
Next Stage of AI Scientist: NanoResearch (Skills, Mem, RL)
Discover AI
Watch →