What Is AI-Native Coaching: It's Not the Product You Keep—It's the Ability to Iterate

I coach business owners and CEOs on AI. The person who understands a business best is always the owner—AI is the framework, business is the content. What I teach is how to use their own understanding of their operations to build and deploy their own AI agents.

When an owner wants to bring AI into their company, the three usual paths all fail. Hire developers—even the simplest AI agent costs tens of thousands, sometimes over a hundred thousand yuan. And traditional development is a one-shot deal: once it’s live, the project is over. But AI agents in this era iterate by the day. My own product went through over seven hundred iterations in a single month. The developers finish and leave—who’s going to keep improving it? Video courses? You get stuck with nobody to help, and nobody tells you when you’ve done something wrong. Sign up for a class? Lectures can’t teach you anything real. When it’s over, you’ve got nothing in your hands.

I’ve built all of that. I turned a course into an online challenge—twelve days, one level per action. Owners bring their own AI and work through it. They submit their work, my AI reviews it on the spot, and the next level only unlocks once they pass. One student posted in our group: “It learned the material and then explained it to me… if it couldn’t find the answer, then I’d ask the teacher.” This is actually a new form of education.

My AI also keeps an eye on everyone—it logs into each student’s machine, reads their code, checks whether things are actually running. If someone in the group says they’re stuck, it investigates first. I don’t know if anyone else is doing this.

All I do is make the calls. On day nine, each student gets a quick consultation with me. The time is short, but the conversation goes deep—because my AI has already done a thorough read on where they stand before I even open my mouth. We sit down and immediately talk about what matters: is the direction right, which part to tackle first, which part doesn’t need to be done at all. What comes out of the consultation isn’t a to-do list for the owner—it’s a checklist for AI to execute on. The owner’s AI agent and my AI agent work together to keep iterating. In the final days, everyone follows that checklist and builds their own product. This is a delivery-focused model—the deliverable is secured, and it saves my time and energy.

Every day after the last level, I share my own version as a reference—just a framework. One student’s work was far more complete than mine: their entire program is over forty thousand lines of code, while my version is just over ten thousand. In a single day, they went through several rounds of iteration. That’s the student surpassing the teacher. Two other students already have their own business applications running on their machines.

When you pay someone to build it, you get a black box. When you’ve built it yourself, the moment your business changes, you can keep modifying it. It’s not a one-time build—it’s owning the ability to iterate. The students bring their own AI to learn; I bring my own AI to teach. That’s AI-native coaching.

EP0106 · 2026-09-26 · 03:33. The picture uses a digital human, and the voice uses my cloned voice. This is an English translation of the approved Chinese script used to create the narration.

I may have invented an entirely new kind of coaching—AI-native coaching.

Right now I coach business owners—founders, CEOs—on AI. The person who understands a business best is always the owner. How to structure the business model, the deeper layers of the operation—that all lives in the owner’s head. I always say: AI is the framework, business is the content. So what I teach is how to use their own understanding of their business to build and deploy their own AI agents.

Now, when a business owner wants to bring AI into their company, there are usually three paths—and none of them really work.

Hire developers? Even the simplest AI agent costs tens of thousands, sometimes over a hundred thousand yuan. And traditional development is a one-shot deal—once it’s live, the project is over. But AI agents in this era don’t iterate by the month; they iterate by the day. My own product had over seven hundred iterations in a single month. The developers finish and leave. Who’s going to keep improving it?

Watch video courses? Not having the time is the least of your problems. You can’t skip ahead to the part you actually need. It just goes on at its own pace. Nobody notices when you’re stuck, nobody tells you when you’ve done something wrong.

Sign up for a class with a teacher? Lectures can’t teach you anything real. When it’s over, you’ve got nothing in your hands. One-on-one teaching is more efficient, sure. But good teachers only have so many hours. Having them walk you through things one by one isn’t a great deal for business owners either.

So what’s the answer? Something that lets you keep iterating, doesn’t require sitting through video courses, and leaves you with a real working product when you’re done. I built all of that.

I never wanted to lecture in the first place—and I don’t have the time for one-on-one teaching either. So I just stopped lecturing entirely. I turned a course into an online challenge. It runs entirely online—twelve days. Each level is one specific action. The owner brings their own AI and works through it. They submit their work, my AI reviews it on the spot—pass, and the next level unlocks. One student posted in our group: “It learned the material and then explained it to me. When I didn’t understand something during the learning process, I’d ask it, and it would go look for the answer in the course materials. If it couldn’t find it, then I’d ask the teacher.” This is actually a new form of education.

My AI also keeps an eye on everyone. Each student’s work runs on their own machine. My AI can log in, read their code, check whether things are actually running. If someone in the group says they’re stuck, it investigates first, figures out what’s going on, and then reports back to me. I don’t know if anyone else is doing this.

So what do I do? I just make the calls. On day nine, each student gets a quick consultation with me. The time is short, but the conversation goes deep. Why can it go that deep? Because before I even open my mouth, my AI has already done a thorough read on where they stand. What’s running on their machine, where they’re stuck, how what they’ve built diverges from what they originally wrote up—it’s reviewed all of it and formed its own assessment. So we don’t waste time getting up to speed. We sit down and immediately talk about what matters most: is the direction right, which part to tackle first, which part doesn’t need to be done at all. I just make a judgment call—set the big-picture direction. What comes out of the consultation isn’t a to-do list for the owner; it’s a checklist for AI to execute on next. After the consultation, the owner’s AI agent and my AI agent even work together to keep iterating on the business’s AI. In the final days, everyone follows that checklist and builds their own product. This is also a delivery-focused model. The deliverable is secured, and it saves my time and energy too.

So how are the results? Every day after the last level, I share my own version for everyone’s reference. It’s just a framework, a baseline. A few days ago, I had my AI look through every student’s machine across two cohorts. One student’s work was far more complete than my version. Today I had my AI check in on their machine again—their entire program is already over forty thousand lines of code. My reference version is just over ten thousand. In a single day alone, they went through several rounds of iteration, all on their own. Now that’s the student surpassing the teacher! Two other students already have their own business applications running on their machines. That’s what I call a real deliverable.

When you pay someone to build it, you get a black box. When you’ve built it yourself, the moment your business changes, you can keep modifying it. It’s not about producing something once—it’s about owning the ability to iterate. The students bring their own AI to learn. I bring my own AI to teach. That’s AI-native coaching.

That’s all for today. See you tomorrow. Bye.