What Universal Substack Growth Advice Overlooks

A look at why strategies that work individually don’t always scale collectively.

A recent post from Strategy Shots comparing “how to grow your Substack” advice to a pyramid scheme sent me back to my early days on the platform.

When I first started, most of what I saw were posts promising rapid growth: how to get subscribers fast, how to reach six figures, how to “make Substack work.” Over time, I noticed a pattern. These posts behaved less like guidance and more like fishing nets. People skimmed them, posted a link or two, and drifted away. Very few stuck around. Nothing really took root.

There’s another category of advice that looks more promising. Fewer guarantees, more frameworks. Less hype, more community. These posts still promote programs meant to help with growth, but they also cultivate networks of people who stay engaged. The data behind their claims isn’t always airtight, but heuristically, the approach feels grounded.

So this isn’t an argument against teaching, storytelling, or marketing. Those are necessary. I wouldn’t invest a dime in a marketing campaign built around explaining statistical distributions to consumers—though, as an experiment, it might be entertaining.

But the necessity of persuasion on the seller’s side doesn’t erase responsibility on the buyer’s.

As readers, we still have to look under the hood. What is the claim actually saying? What assumptions does it rely on? What kind of system is it operating inside?

This is where the pyramid-scheme comparison becomes interesting—not structurally or morally, but logically.

Two assumptions have to be true before the argument even starts:

• People tend to aggregate, mimic one another, and gravitate toward the same things—pulled by psychological biases and amplified by algorithms.

• Human attention and reading time are limited.

If either assumption feels wrong, the rest won’t land.

Take the six-figure Substack claim. Let’s be generous and say 5% of writers make six figures. That number isn’t low simply because the other 95% failed to follow the right protocol. That might be part of it—but it’s not the main driver.

The deeper reason is structural.

Everyone is operating inside a system constrained by limited attention, uneven trust dynamics, and psychological bottlenecks that funnel most readers toward a small set of familiar voices—before we even factor in algorithms.

Those voices aren’t necessarily the most rigorous, data-impeccable, or truthful. They’re the ones that captured attention and learned how to hold it by triggering things people are already inclined to respond to. That dynamic—not logic, truth, facts—often determines who rises to the top.

Protocols and blueprints can move the 5% slightly. They can improve odds at the margin. But they can’t turn a scarce outcome into a universal one without breaking the math.

When someone broadcasts a method and implies that everyone can reach a six-figure outcome by applying it, they’re making an impossible claim—even if they don’t intend to. If everyone could apply the same technique and get the same result, then everyone would end up in the top 5%. That’s not how math works.

This is where the pyramid-scheme logic sneaks in—not in mechanics, but in the structure of the promise: a universal method paired with a scarce outcome.

And even when a method genuinely provides an edge, that edge doesn’t survive scale. If a technique works and everyone adopts it, it stops being an advantage. It becomes the baseline. The next group of successful people will be the ones doing that technique plus something else.

That’s not unfair. That’s how competitive systems behave.

We’ve already seen this dynamic play out in formal education—and felt the frustration it produces.

When college degrees were rare, they were tied to employability and job security. Not because the degree itself caused employability, but because it placed its holder in a small, advantaged group. As degrees became common, the differentiating power disappeared. The promise didn’t hold—not because anyone lied, but because the causal story was wrong.

The degree didn’t create value by itself.
The rarity of what it signaled did.

When 30 people apply for 200 jobs requiring a certain skill, the degree selects.
When 200 people apply for 30 jobs and all have degrees, the diploma stops selecting. It becomes a filter—necessary, but no longer sufficient.

Employers then look for what’s rare now. As people catch on, that new differentiator becomes common too, and the cycle repeats.

The same logic applies to Substack advice.

Even if certain techniques work today—and many probably do—their differentiating power shrinks as adoption grows. The underlying forces don’t change. Attention remains limited. Trust remains uneven. People still gravitate toward a small group doing the method plus something else.

Because the real issue isn’t whether methods work.

It’s what happens when they work too well for too many people.

Methods aren’t limited because they’re bad—though some are—or because people apply them incorrectly—though that happens too. They’re limited because once they scale, they stop differentiating.

When I see a program that claims it can help with growth, these are the questions that come up for me:

• How early am I in this process, really?
  Am I early enough that tactics still differentiate—or am I arriving once they’ve already become the baseline?

• How many other people in my niche are applying the same approach?
  Not in theory, but in practice.

• What does this strategy depend on that I don’t control?
  Platform dynamics, attention cycles, timing, network effects.

• How does the program talk about failure cases?
  Are limits acknowledged, or does everything collapse into “you didn’t commit”?

• And most importantly:
  What does this teach me to do when the tactics stop working?

Programs that ignore that reality end up selling certainty where probability would be the honest framing. That doesn’t make them evil. But it does make the promise of universal scaling structurally untenable.

Which is why I’m skeptical of “secret blueprints” broadcast to everyone, and far more interested in teaching that helps people figure things out for themselves—methods for thinking, not formulas for copying.

Methodology can survive scale.
Universal shortcuts rarely do.

And pretending otherwise doesn’t help the people trying to decide what to do next.