Two products can run the exact same AI model, and behave completely differently.
One stays a basic back-and-forth chatbot. The other works for hours on a real software task, with access to files and a terminal.
The difference doesn't live in the model. It lives in what wraps around it.
The industry already has a name for that: agentic harness. And it's not just a buzzword, Anthropic, OpenAI, and LangChain are each using it, independently, in their own production documentation.
This is the third and final piece in our series on agentic architecture. In it, I cover:
What a harness actually is (tools + memory + the agentic loop)
Why switching models shouldn't force you to redesign your governance from scratch
How everything we covered in the first two parts of this series — autonomy tiers, tool calling, idempotency, literally lives inside the harness.
Full article, with sources, on the original site → harnessIA
