The LLM is the brain; the harness is the body.

I mean, it can be that way. But it does't have to be. The Harness can be as much the brain as the LLM. You have nearly unlimited flexibility in what you do in the harness, and you can add as much of the overall "intelligence" of the system as you want in the harness.

To illustrate, you can:

1. Use multiple "brains" / LLM's, and do routing between them using a specialized model (a Jev like model, or something of your own design)

2. Use planning tools like pyperplan, jupyddl, pddl4j, etc.

3. Implement your own "memory" system using... pretty much anything you want. And I would argue that a lot of the apparent "intelligence" of a system involves how well memory works

4. Call classical machine learning models to solve specialized problems

5. Use reinforcement learning to improve performance in specific areas

6. Implement a blackboard for multiple knowledge sources to collaborate.

7. Use inference engines using forward/backward chaining, RETE, etc.

8. Use your own hand-rolled abductive inference strategy

9. Implement your own Bayesian reasoning techniques

10. Use custom causal inference code

... and so on.

Don't get me wrong. I'm bullish on what LLM's can do, but I posit that the overall expressed intelligence of a system can involve a lot more than just the LLM. In fact, I'd actually make the slightly stronger claim that, depending on what you're trying to do, an LLM might not even be required at all.