Let me start with a strong opinion.

If you're a software engineer or a data scientist, nothing you can learn today will do more for your career than learning to design agent harnesses.

It took me a little while to actually hit, but when I found out researchers at top firms hadn't written code in the last 8 months, it struck me.

We aren't going to be writing code anymore.

Let's clearly define what a "harness" is in the context of AI

There's a lot of confusion, buzzwords and conceptual conflation in the current state. Thus, we need a collective conceptual agreement on what a harness actually is.

You may have seen this equation before:

Agent = LLM + Memory + Tools + Planning + Action \text{Agent} = \text{LLM} + \text{Memory} + \text{Tools} + \text{Planning} + \text{Action}

The LLM is the base. Stateless, unchanging, perhaps swappable.

The rest is the "harness".…