I follow the AI governance news closely, and recently I have been hearing a lot of chatter about AI governance harnesses. I think the enterprise industry is slowly waking up and realizing that Large Language Models (LLMs) need a cage.
I actually like the idea of thinking about AI governance in terms of harnesses. SAFi is technically a harness itself, but the way the rest of the industry is approaching the problem is completely backward.
Take a tool like Claude Code. It is an agentic harness, it has a software layer built around the LLM to give it tools, memory, and execution capability. But in that setup, the LLM is still the star of the show. It executes and makes decisions on its own.
SAFi, on the other hand, makes the LLM a substrate of its thinking process. In SAFi, the LLM is just another step in the execution pipeline. The LLM is not in charge; it is simply a component in the loop.
Because the LLM is the reasoning module, it can propose an action. But that action must first be approved by an independent module. That approval module is pure Python, it is completely blind. It cannot reason; it just executes based on deterministic rules.
