Reads · saved 2026-06-06
The Anatomy of a Harnessed LLM Agent
A clean way to think about agent design: the model is deliberately thin, and intelligence gets pushed outward into memory, skills, and protocols that the harness composes at runtime. The useful question it hands you is where any new capability should live. Good conceptual scaffolding if agents still feel like a bag of tricks.
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A harnessed LLM agent, clearly explained!
Most people picture this as a model with tools bolted on. The real architecture inverts that relationship.
The model itself is deliberately thin. Intelligence gets pushed outward, and the harness composes it at runtime.
Three dimensions orbit the harness core:
Between the core and these modules sit the mediators, like sandboxing, observability, compression, evaluation, approval loops, and sub-agent orchestration.
They govern how the harness reaches out and how state flows back in.
The useful question this framing unlocks is: for any new capability, where should it live?
Harness design becomes a question of what to externalize, and how to mediate it.
I'm building a minimal agent harness from scratch and will open-source it soon.
In the meantime, my co-founder wrote an article about the anatomy of Agent Harness, covering the orchestration loop, tools, memory, context management, and everything else that transforms a stateless LLM into a capable agent.
Read it below.
**Quoted @akshay_pachaar:** http://x.com/i/article/2040732084843782144