AI Loops Are Useless Unless They Do This artwork

AI Loops Are Useless Unless They Do This

Leveling Up with Eric Siu

June 23, 2026

๐Ÿ‘‰ Growth Newsletter for top marketers: https://levelingup.beehiiv.com/subscribe Everybody technical is talking about loops right now. But almost nobody is asking the real question: how do you apply loops to your business if you're a founder, operator, or marketing leader instead of an engineer?
Speakers: Eric Siu
**Eric Siu** (0:00)
Everybody's talking about loops right now. You have the creator of OpenClaw talking about it, you have the creator of Claude Code talking about it.

**SPEAKER_2** (0:05)
So loops are sort of like as big as the step from source code to agents was, loops are the step from agents to the next thing. It's just as important and as big a step.

**Eric Siu** (0:13)
Keep in mind, all of these people are technical. And so how do you think about this if you are not an engineer, if you are a CEO, you are a founder, or let's say you're an operator, let's say you're a marketing leader or an operator, how do you actually apply this to business? And so in this video, I'm going to deconstruct how it actually works. I'm gonna give you a practical example on how we actually use it and how we think about it for one process around AEO and SEO, and you can even steal that if you want to. I even have some artifacts that I'm gonna show you as well. So stay till the end of this video, and by the end of this, you're gonna fit out the right framework into applying loops, not just for building, but actually building your business. Okay, so this is a business loop artifact here. And basically, now you know that winning with AI is not about prompting better anymore, okay? So we are looking at the old ways, basically, you're chatting, you're prompting, right? People get assessed over what's the prompt library that you should have, right? And then you have to be, you have to attend the session, meaning that you have to be paying attention to the session itself. And then over time, you have to just continue to just repeat this over and over. Now, the system doesn't compound this way, right? At the very least, if you're putting together some type of goal or some type of workflow and you're just repeating it over and over, and in many cases, it could be you're setting up an automation in Codex, for example, or you're setting up a routine or a loop inside of Cloud Code, that's really what it is. And people are like, oh, well, how's that different than the slash goal command? And in many cases, I don't really think it's that different. I think a lot of people are just kind of spamming these commands now to get things done. And just keep in mind, these will be, typically will be token intensive. But if you're using something like the newest version of GLM, which people have been raving about it, maybe you can run that on a local model and you can just spam the crap out of these things, right? This is the old way of doing things. And so these are the four traps, keeping AI stuck in demonstration mode, which again, you have to kind of stay on top of it. The new way is you find, you detect the recurring workflows and you look for fresh market signals, right? So an example of this is we actually have one where every single week, it's mining all of our customer calls and figuring out, hey, what are the things that should be made, that should be created into workflows, right? So look for calls, they'll look for kind of the gaps because we're talking about building the services as software firm, like this AI native firm, but why in the world do we still continue to sell re-chainers the same way? And this forces the muscle, this forces leaders to, sure, it can cite all this data, but once you find this stuff, and assuming that you have the right leadership in place, well, then you're going to be able to build the next step, right? So generating the first useful asset or action from the signal. For me, when we generated one of these, we basically looked at the GONG calls and I was like, oh, well, it looks like these clients right now are really healthy right now because they do really like the way in which you are helping them on the AI side. These are AI native conversations, and these are some of the single brain clients that we've had, right? Versus on the other side, you can also see the ones that maybe aren't so happy right now and why they aren't so happy. And this is how we can figure out the workflows that we need to be building for them, right? So again, this is where we start to build things, right? Whether it's pages, content, or outbound tests, or even just changing workflows for our team, or just building these workflows out and say, hey, Mr. Client, we're going to do this for you for free, but if you want more stuff like this, just let us know, right? And then we're compounding our workflows.

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