Zhang Pinpin · Hands-On AI Coach
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Playing with AI—have you actually made money? Three paths, and the precondition most people skip

Long-Form Video · EP0074 July 30, 2026 02:47
What this episode covers

An uncomfortable topic: after all this time playing with AI, have you actually made any money?

I break it into three paths—cut cost, copy, take it apart and rebuild. Each one is harder than the last, and each one has a higher ceiling. But what decides the outcome isn't which path you pick. It's the precondition under all three: you have to be making money already. AI is an amplifier, not an engine.

The short version

There are really only three ways to make money with AI: cut cost, copy, and take the business apart and rebuild it.

Each path is harder than the one before, and each has a higher ceiling. But more important than which one you pick is the precondition sitting under all three—

You have to be making money already.

AI is an amplifier, not an engine. It can make something that already earns faster, bigger, and more automatic, but it does not conjure a business out of nothing.

Path one: cut cost

The easiest one to see. Work that used to take ten days now takes one.

For an individual, the time you free up can be reinvested: learn something, deliver more value, turn it into a promotion and a raise. Even the spare hours you save can go into something on the side.

For a company, the drop in headcount cost is real. Across the clients I work with, whenever AI replaces a business process, it takes out roughly 60% of the headcount cost.

But there’s a trap here. The moment that cost drops, a company’s first instinct is usually “can I run with fewer people.”

Going down the layoff road is a vicious cycle. The savings never turn into new capacity—you just made the operation smaller. Next round of cost-cutting, the only lever left is another cut. The end of that road is shrinking yourself out of existence.

Path two: copy

One level up from cutting cost: take the thing, the process, that already monetizes repeatably and turn it into an automated product—or serve and follow up with more clients on the same headcount.

This path is hard in two places, and both are real:

Most companies right now are short on orders, not efficiency. With no demand, extra efficiency has nowhere to go.

Everything looks the same. If you’re a one-person business, you’ll find that once AI is behind everyone, 99% of what people deliver isn’t fundamentally different. It turns into a bidding war, and very few people genuinely command a premium for the level of what they deliver.

So for a company, the more valuable use on this path isn’t on the production side at all. It’s upstream:

  • expanding the lead pool
  • lifting the conversion rate
  • following up, at a decent standard, on all the leads nobody was ever going to touch

That last one gets underrated. Those leads went untouched because they couldn’t be afforded—not enough hands, and the expected return per lead didn’t cover the labor. AI changes that premise.

Path three: take it apart and rebuild

The hardest path, and the one with the highest ceiling: use AI to pull the whole business apart and put it back together.

It tends to show up in three shapes:

  1. The conversion path gets shorter — steps in the middle get eaten.
  2. What you deliver changes — what used to be a course becomes hands-on coaching with AI behind it. The vehicle changed, and so did what the client walks away with.
  3. You meet demand that was previously impossible — serving newly created needs in a way that couldn’t have worked before.

The third shape is the one worth sitting with. I’ve talked in an earlier video about using AI for personalized, gene-level nutrition management—something there were previously neither the resources nor the means to do, and now it’s easy.

The point isn’t just “one more product.” Inside my existing pool of users, when I hand them a product I can add value on top of it and raise what a single customer is worth.

Same pool, higher value per customer. It’s genuinely harder to pull off, but it’s the only one of the three that changes the shape of the business.

The precondition under all three

All three come with one precondition: I’m making money right now.

Everything I’ve done and everything I’ve learned over this past stretch was to make the way I already made money faster, more scalable, more automated.

Not this: see a new technology, go learn it. See a skill, go install it. That’s not it.

The difference looks small and it decides where you’re standing a year from now. The first is multiplication on something already proven. The second is addition—and you’re adding in someone else’s direction.

I do the same thing when I work with a client: find the point of highest value in the business they already have, and put AI behind that one point. Not roll out a whole new toolkit.

So

You can genuinely stop watching the videos about how the sky has fallen again.

Spend that time settling down and taking a hard look at how you can actually make money right now—and move from there.

This episode is me on camera, 2 minutes 47 seconds, with the bottom half of the frame showing a live screen recording of me driving CC from my phone. The full transcript is under the “Transcript” tab.

Everything I've done and everything I've learned over this past stretch was to make the way I already made money faster, more scalable, more automated.