Agent architecture

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

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

Jonas Huckestein introduces a novel, event-sourced architecture for building AI agents. The core abstraction consists of three parts: a state, a synchronous reducer that derives state from events, and an after-append hook for side effects. This design ensures debuggability and allows state to be rebuilt without re-running expensive operations like LLM calls. A key innovation is the ability to deploy an agent by simply appending a 'dynamic worker configured' event—containing JavaScript code for a processor—to an event stream, eliminating the need for servers or complex deployment pipelines. This enables a distributed and composable ecosystem where processors from different authors can collaborate on a single stream.

A Piece of Pi: Embedding The OpenClaw Coding Agent In Your Product — Matthias Luebken, Tavon

A Piece of Pi: Embedding The OpenClaw Coding Agent In Your Product — Matthias Luebken, Tavon

Matthias Luebken explains the core principle of building with coding agents: make things easy for them. This talk deconstructs the Pi SDK, showing how a simple loop of an LLM calling CLI tools can lead to emergent capabilities. Luebken presents a real-world B2B sales pipeline built on this principle, where agents handle incoming emails, query CRM/ERP data via simple tools, and generate draft responses, keeping the human in their familiar email client.

AI Agents in Practice • Henrik Kniberg • GOTO 2025

AI Agents in Practice • Henrik Kniberg • GOTO 2025

Henrik Kniberg shares practical experiences from over two years of AI agent development, defining agents as autonomous entities with missions, tools, and an LLM brain. He covers effective design patterns, architectural insights, and safety considerations, emphasizing the importance of human-in-the-loop collaboration and iterative development to build agents that are not just powerful, but genuinely useful in real-world scenarios.

When Agents Learn to Feel: Multi-Modal Affective Computing in Production // Chenyu Zhang

When Agents Learn to Feel: Multi-Modal Affective Computing in Production // Chenyu Zhang

This talk explores the frontier of affective computing in AI agents, proposing a new architecture where emotion is a first-class component. It covers the technical challenges of deploying multi-modal, emotion-aware systems in production—from memory and learning to multi-agent orchestration—and delves into the critical ethical considerations of privacy, manipulation, and scientific validity.

How Claude Code Works - Jared Zoneraich, PromptLayer

How Claude Code Works - Jared Zoneraich, PromptLayer

An unofficial deep dive into the architecture of modern coding agents like Claude Code. Jared Zoneraich of PromptLayer explains the shift towards simpler, model-centric designs, detailing the core components like the master loop, tool calling (especially `bash`), and context management strategies. The talk also contrasts Claude's philosophy with other agents like Codex, AMP, and Cursor, offering practical takeaways for building your own AI agents.