How to Design an OpenHarness Style Agent Runtime with Tools, Memory, Permissions, Skills, and Multi-Agent Coordination
In this tutorial, we build OpenHarness from scratch to better understand how a practical agent harness works. We recreate the major building blocks that make an agent system useful, including tool use, typed tool schemas, permissions, lifecycle hooks, memory, skills, context compaction, retry logic, cost tracking, and multi-agent coordination. Instead of treating an agent framework as a black box, we expose the full control flow and watch how the harness receives a user task, lets the model dec
This is a tutorial that builds an agent runtime system from scratch to demonstrate how practical AI agent frameworks function. The tutorial covers major components including tool usage, memory management, permissions, skills, retry logic, cost tracking, and coordination between multiple agents. The approach exposes the full control flow rather than treating the framework as a black box, showing how a harness receives tasks, allows models to decide actions, validates and executes tool calls, and continues processing until completion.
Explainer: The 90% That Matters: Why Your Agent's Harness Beats the Model
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