Agent Harnesses: The Engineering Infrastructure That Turns AI Models into Autonomous Work Engines
By
Vivek TrivedyMarch 10, 202612min
Summary
This article explores the concept of "agent harnesses" — the infrastructure, code, configuration, and execution logic surrounding AI models that transform raw models into functional, autonomous agents. It argues that an agent equals a model plus a harness, and that harness engineering is the critical discipline for building useful AI work engines. The piece defines core harness components including filesystems, sandboxes, memory systems, tool integration, and execution environments needed for both current and next-generation AI agents.
Source
Twitter / XAgent Harnesses: The Engineering Infrastructure That Turns AI Models into Autonomous Work Engineslangchain.comKey quotes
· 5 pulledAgent = Model + Harness
If you're not the model, you're the harness.
A harness is every piece of code, configuration, and execution logic that isn't the model itself.
A raw model is not an agent. But it becomes one when a harness gives it things like state, tool access, and execution context.
Harness engineering is how we build systems around models to turn them into work engines.
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