Eric Siu explains why AI loops outperform agents for running your business. Loops target a desired state, act, record traces, and learn from results. The difference: agents handle tasks, loops create repeatable leverage by automating entire business processes.
I'm going to switch my screen and then explain the difference between AI loops versus goal commands because many people still don't have it right. And I thought I had it right for a while and I didn't. Agents can help you with tasks. Loops run parts of the business. If I bring you to this diagram over here, this is the difference. An agent is maybe it's a prompt, which is prompts are usually one-off and it's hard to remember these prompts. Prompt library, like nobody wants to do that. A /goal command, you can spam /goal and a goal will get you to an outcome. But, you know, the thing is you have to, you still have to kind of be, it's still a little attended there, right? And the way I look at an agent is just, do you actually have the AI thinking in the workflow? Is it thinking? But, you know, oftentimes it's different than a loop because a loop involves looking at a target state and then you act and record trace and then you learn, stop, or escalate. So this is, we're talking about repeatable leverage here.
