Can You Predict If a Startup Will Be Successful?

There is a line early in The Matrix that I have never been able to shake.

Morpheus leans forward in a dark room, looks Neo dead in the eyes, and tells him why he hasn’t been sleeping: “What you know you can’t explain, but you feel it. You’ve felt it your entire life — that there’s something wrong with the world. You don’t know what it is, but it’s there, like a splinter in your mind, driving you mad.”

If you are building a tech startup right now, I already know what that splinter is for you.

Peter Thiel famously likes to ask founders a single question to test their conviction: “What important truth do very few people agree with you on?”

Here is mine.

Startup growth is not random. It is not a lottery ticket. It is a deterministic science — and you can predict with mathematical certainty whether a startup will explode or die before a single dollar is spent on marketing.

Right now, almost the entire world disagrees with me. And that’s fine.

We have all been conditioned to believe that early-stage startup success is a giant casino.

The Eight-Hundred-Dollar Mistake

On April 12, 1976, a forty-one-year-old draftsman named Ronald Wayne walked into a county office in Santa Clara, California, and signed a piece of paper that surrendered his ten percent stake in a twelve-day-old computer startup.

In exchange for his shares, he was handed a check for eight hundred dollars. A few months later, he accepted an additional fifteen hundred dollars to forfeit any future claims against the business.

Wayne was not a fool. He was the only adult in the room. His two younger co-founders, Steve Jobs and Steve Wozniak, were erratic twenty-somethings with no money, operating out of a family garage. Jobs had just agreed to buy fifty thousand dollars worth of computer parts on credit to fulfill an order for a local store known for not paying its bills on time. Wayne had lived through a failed slot-machine business five years earlier. He had assets — a house, a car, a small savings account — and he realized that if this little computer company went bankrupt, the creditors would come after him.

He looked at the company, weighed the risk, and made a rational calculation. He could not see any way to predict whether two kids soldering circuit boards would ever sell more than a hundred machines.

Today, that ten percent stake in Apple would be worth roughly three hundred and fifty billion dollars!

Twenty-three years later, in the spring of 1999, two Stanford graduate students walked into the offices of Excite, then the second-largest internet portal in the world.

Their names were Larry Page and Sergey Brin. They were tired of running their fledgling search engine and wanted to go back to their academic studies. They offered to sell their entire company — the PageRank algorithm, the domain name, the servers — to Excite’s chief executive, George Bell, for one million dollars.

Bell wasn’t interested. Vinod Khosla, one of the sharpest venture capitalists in Silicon Valley and an investor in Excite, talked the two students down to seven hundred and fifty thousand dollars.

Bell still said NO!

Why?

Because Bell believed that an internet portal made money by keeping people on the website as long as possible so they would look at banner ads. Page and Brin’s search engine did the opposite: a user typed a word, and the engine sent them away to the right website in half a second. Bell could not see the future velocity of that transaction. He threw away a two-trillion-dollar monopoly for the price of a modest suburban house.

One year later, in the autumn of 2000, Reed Hastings and Marc Randolph flew to Dallas, Texas, and walked into the shiny glass headquarters of Blockbuster. At the time, Blockbuster was an empire with nine thousand stores and billions in revenue. Netflix was a tiny DVD-by-mail startup losing money. Hastings offered to sell forty-nine percent of Netflix to Blockbuster for fifty million dollars and run their online division for them.

Blockbuster’s CEO, John Antioco, barely suppressed a laugh. He rejected them on the spot. Ten years later, Blockbuster filed for bankruptcy, while Netflix grew past two hundred billion dollars.

Now look at the opposite side of that coin.

In 2017, an e-commerce app called Wish decided that it was going to buy its way to global dominance. Wish raised billions of dollars from elite venture capital funds. It signed a thirty-million-dollar deal with the Los Angeles Lakers to put its logo on Lebron James’s basketball jersey. At its peak, Wish was spending over one billion dollars a year on Facebook and Instagram advertisements, becoming the single largest advertiser on Meta’s platform.

Every conventional rule of modern startup advice said Wish should win. They had the capital. They had the engineers. They had the brand awareness. They had the aggressive paid acquisition machine.

By 2024, Wish had lost ninety-nine percent of its value and was sold off for scraps.

Pause and look at those moments together.

Ronald Wayne was inside the garage with Steve Jobs and could not predict Apple. George Bell had the source code of Google on his desk for $750,000 and could not predict Google. And the investors who poured billions into Wish’s advertising furnace could not predict that the moment the ad spend stopped, the customers would vanish.

Why?

Because for the entire history of the technology industry, everyone — founders, venture capitalists, journalists, and executives — has operated under the same quiet assumption: that startup growth is measurable after the fact, but fundamentally unpredictable in advance.

We treat rapid growth like lightning. When it hits a company, we write books, substacks, articles, and do podcasts about the founder’s wardrobe. When it misses, we shrug and quote the statistic that ninety-seven percent of startups fail anyway.

Ask any startup founder today how many new users they will acquire next Monday. They will give you a number. Ask them how they arrived at that number, and the room goes quiet. They will give you a random number depending on who is asking. Ask them how they calculated that number, and they have no idea. It is a guess. A gut feeling. A prayer.

And that blindness is why ninety-seven percent of startups fail.

The Five-Day Trap and the Wrong Mountain

For the past few years, I have been obsessed with a strange pattern I notice when it comes to tech startups.

At first, when you look at the startups that reached one million users in record time, their success looks completely random. Then you line them up chronologically, and the hair on your arms stands up:

• Netflix (1999): 3.5 years to reach 1 million users.
• Airbnb (2008): 2.5 years to reach 1 million users.
• Facebook (2004): 10 months to reach 1 million users.
• Spotify (2008): 5 months to reach 1 million users.
• Instagram (2010): 2.5 months to reach 1 million users.
• ChatGPT (2022): 5 days to reach 1 million users.

Forget the names for a second. Just look at that compression. Years became months. Months became weeks. Weeks became five days.

Now imagine I sat across from you over coffee today and asked you, the ambitious tech founder: “Can you get one million users in the next five days — with zero funding, zero ad spend, and an incomplete product?”

How would you react?

Most founders would get angry. They would quit on the spot or accuse me of setting an impossible, unfair trap.

Because deep down, we have all bought into the lie that 5-day growth is a freak lightning strike reserved for Sam Altman, while the rest of us have to spend five years or more grinding in the startup trenches with endless pitches to uninterested VCs.

Because you believe slow growth is normal, you tolerate slow growth.

And tolerating slow growth is how you walk straight into the worst nightmare of a founder’s life.

Let’s be honest with each other. You are not actually afraid of your startup failing in six months. If you launch an app tomorrow, nobody buys it, and you shut it down by Christmas, you will survive. You lost a few months and a bit of ego.

What truly terrifies you at 3:00 AM is spending the next five to ten years of your life climbing the wrong Mount Kilimanjaro.

I was born in Zimbabwe and spent years in Britain, and I have always had a morbid curiosity about why fifty thousand tourists fly to Tanzania every year to climb Mount Kilimanjaro. Unlike Everest or K2, Kilimanjaro doesn’t look scary. It has no vertical ice cliffs. You just walk up a gentle dirt path.

Because the slope is so easy to walk, people keep marching upward, ignoring the headaches in their skulls, unaware that the oxygen pressure in the air is dropping to toxic levels. When you near the top, the trail is brutally unforgiving. World-record Polish kayaker Aleksander Doba reached the summit sign in 2021, sat down to rest for two minutes, and tragically died on the rock.

South African rally champion Gugu Zulu died on the ascent when his lungs filled with fluid.

Irish mountaineer Ian McKeever was struck dead by lightning on the plateau.

People die on Kilimanjaro because the gentle slope tricks them into climbing into a death zone.

In startups, slow growth and fake profitability are that gentle slope.

Founders love to brag, “We aren’t growing fast, Simba, but we’re profitable!”

Profitability in the early stages of any startup is a magic trick. You can fake profitability any month you want — just hire a bunch of people at the start and fire them one by one whenever revenues dip, or cut your own salary to zero.

Growth is the only true north for a startup.

If you are not growing rapidly, your product does not have Product/Market Fit yet.

Yet every day, brilliant founders overestimate their market size, underestimate the opportunity cost of their youth, burn millions in venture capital, sacrifice their relationships, and spend a decade climbing — only to reach the summit at age forty and realize they climbed a barren hill that nobody cares about.

Why a Patent Clerk’s Four Symbols Changed the World

How do we turn startup growth from a deadly guessing game into a predictable science?

Think about the most famous formula in human history: E = mc²

Here is something funny that history books rarely mention: when Albert Einstein published that equation in 1905 while working as a third-class patent clerk in Switzerland, nobody cared. There were no parades. No newspaper headlines. For fourteen years, the formula sat in academic journals until British astronomer Arthur Eddington applied relativity to a real-world problem during the 1919 solar eclipse — and later, when physicists applied E = mc² to split the atom, unleashing nuclear power.

Why are formulas so magical?

Because a formula is not an answer.

A formula is a way of thinking about a problem in a specific domain.

You can’t use E = mc² to paint a portrait or cook a curry dish. What a formula does is strip away ninety-nine percent of the useless noise in a chaotic room, leaving you with the exact two or three variables that govern reality.

When I started asking why companies like ChatGPT, Instagram, YouTube, and Google Search grew with such violent speed — not “viral” hype that dies in a week, but relentless, compounding adoption — I realized they were all governed by the exact same physical law.

Here is the formula for predicting startup growth: Growth Velocity (Q) = Trapped Market Pressure (E) ÷ Friction (R).

Or, written simply so you never forget it: Growth = Trapped Pressure ÷ Friction

That’s it. Every billion-dollar breakout and every zero-dollar failure lives inside that fraction.

Let me show you how both halves of this equation work — starting with the bottom.

The Bottom Half: Friction (And Why Cal AI Was Inevitable)

We start with the bottom of the formula — Friction — because this is the only variable you, as a founder, can directly control and influence.

Every human being on earth has desired outcomes. We want to make money, lose weight, look attractive, be entertained, avoid embarrassment, or finish our work faster.

Between a human and their desired outcome stands Friction — which always comes in the form of money, time, physical effort, or mental confusion.

Let me give you a simple, everyday example: losing weight.

Hundreds of millions of people wake up every morning wanting to lose weight. Why don’t they? Look at the friction wall:

• You could exercise at home — which means spending $1,500 on a treadmill or Peloton bike, waiting for delivery, and sacrificing half your living room space.
• You could join a local gym — which means paying a monthly membership, buying gym clothes, packing a bag, driving twenty minutes through traffic, fighting for a machine, showering, and driving back. And quitting after one month anyway.

Eventually, most people realize a basic biological truth: 90% of weight loss comes down to diet — simply eating fewer calories than you burn.

So ten years ago, software founders built calorie-tracking apps like MyFitnessPal.

Problem solved, right?

No!

Have you ever actually tried to log a home-cooked meal or a restaurant plate in a traditional diet app? You have to turn the food package over, squint at the nutrition label, weigh your chicken breast on a kitchen scale, calculate how many tablespoons of cooking oil were in the pan, search a clunky database with twenty conflicting entries, and type it all in manually three times a day.

The friction was so exhausting that almost everyone quit after four days!

Now, ask yourself a question that drove “serious” software engineers crazy over the last two years: How did a couple of teenagers build an app called Cal AI and scale it to tens of millions of dollars in revenue in months?

Before you had the Growth Formula, Cal AI looked like pure, unfair TikTok-generated luck.

With the formula, Cal AI’s runaway success was almost 100% inevitable.

Those teenagers didn’t hold focus groups or spend two years doing market research. The desire to lose weight without doing math was already boiling in the market.

What did Cal AI do?

They used AI vision to collapse the friction to zero. Instead of reading labels, weighing food, and doing math, you simply point your phone camera at your plate, snap a photo, and the AI calculates your calories and macros in three seconds. It felt like magic!

And how did they unlock that latent demand so quickly?

They tapped directly into two forces from what I call Simba’s Five Forces: the Power of Content Creators and the Power of Internet Users. When hundreds of fitness influencers and everyday users showed a 3-second video of snapping a photo of a burger and seeing the calories pop up instantly, millions of viewers felt their friction wall vanish in real time.

Look across the entire history of tech, and you will see that Marc Andreessen was right when he said “software is eating the world” — because software is a machine for eating friction for breakfast:

• Gaming (From Consoles to $5M/Day Mobile Whales): When people are bored, their desired outcome is fun. Years ago, PCs couldn’t run games well. Then came gaming consoles, which cost $500 and chained you to a TV. Then smartphones put a console in every pocket, and freemium games dropped the price friction to $0. That is how Supercell’s Clash of Clans exploded — and because they paired zero entry friction with an uncapped business model where passionate “gaming whales” gladly spent thousands of dollars upgrading their bases, at some point in time they raked in $5 million per day!
• Movies (Blockbuster to Netflix): Before Netflix, watching a movie meant getting dressed, driving to a Blockbuster store, walking down long aisles, paying per tape, and getting slapped with late fees when you forgot to drive back. Netflix deleted the drive, the aisles, and the late fees.
• Information (The Library to Google): Before Google, answering a question meant walking to a municipal library, flipping through index cards, and reading ten chapters of a dusty book. Google reduced a two-hour library trip to a 0.2-second search box.

And today, AI has collapsed the friction of building software itself.

Before AI, to build a tech startup, you either had to be a prodigy like Bill Gates or Mark Zuckerberg coding at age twelve, or get a computer science degree and pay developers hundreds of thousands of dollars to write code for a product you had no clue anyone wanted. Today, with AI coding assistants, you can erase friction in days instead of months.

But here is the trap that kills 97% of coders today:

Because coders have fallen so deeply in love with the bottom half of the formula (reducing friction with code), they completely ignore the top half!

It is like going to the gym seven days a week and making every single day leg day. You end up with massive, Olympic-sized quads and a chest so weak you can’t lift a grocery bag.

You can write the cleanest code on earth to reduce friction — but you must know WHICH desired outcome you are dealing with first.

The Top Half: Trapped Pressure (The Spindletop Gusher)

Look at the top half of the formula: Trapped Market Pressure.

To understand what “pressure” actually means, lets take a walk down history memory lane to East Texas at the turn of the 1900s.

Dozens of prospectors were desperate to strike oil. Because if you struck the oil you struck untold riches. People bought heavy steam drills, picked random plots of land, and started digging. They dug fifty feet, a hundred feet, three hundred feet. Nothing but dry rock and mud. So they worked harder, bought sharper drill bits, and eventually all went bankrupt.

Only one man succeeded on a massive scale: an engineer named Anthony Lucas at a hill called Spindletop.

Why did Lucas succeed where dozens of hardworking men failed?

Because Lucas didn’t start by drilling. He spent months doing a geological survey. He looked for underground salt domes and gas seepage that proved an ancient ocean of oil was trapped beneath a thick seal of rock, under millions of pounds of subterranean pressure.

When Lucas finally drilled his hole on January 10, 1901, he didn’t have to pump the oil out. The moment his drill bit broke through the rock seal at 1,139 feet, the trapped pressure blasted a geyser of crude oil 150 feet into the sky, gushing 100,000 barrels a day all by itself!

Now burn this truth into your mind:

Demand, desires, wishes, passions, and bleeding problems live inside the market. As a founder, you CANNOT create demand. You can only extract it.

• The Oil Reservoir = Trapped Market Pressure.
• The Dirt and Caprock = Friction.
• Your Product / Code = The Drill Bit.

Look at the basic math of our fraction: Growth Velocity (Q) = Trapped Market Pressure (E) ÷ Friction (R).

What happens if you build an incredible AI drill bit that reduces friction to almost zero ($0.1$), but you drill into a market where Trapped Pressure is Zero?

Growth = 0 ÷ 0.1 = 0

Zero divided by anything is still ZERO! That is why CB Insights and every startup post-mortem archive show the exact same #1 cause of startup death: “No market need.”

They drilled a pristine hole into dry rock.

Now look at the flip side. What happens when Trapped Pressure is massive (say, 1,000), and you shrink Friction from 100 down to 0.1?

Because you are dividing by a fraction approaching zero, growth doesn’t just add up — it multiplies by an order of magnititude from 10 to 10,000!

Testing the Formula on the Icons (And the Future)

Suddenly, every “miracle” startup in history makes complete logical sense.

It was never luck:

• Google Search: The trapped pressure to find information on the web without wading through Yahoo’s cluttered directory trees was immense. Google gave the world a blank white screen with one text box. Friction hit zero; growth went vertical.
• Facebook: College kids have a deep, biological desire to know who is single, who is in their classes, and what their peers are doing. Before Facebook, that meant looking at a paper freshman book or clunky anonymous forums. Zuckerberg digitized the real-name campus directory. One school hit 80% adoption overnight.
• Instagram: Millions of people had iPhones in 2010 and desperately wanted to share cool photos, but mobile cameras took blurry, ugly pictures and transferring them to a PC was a chore. Instagram added a one-tap vintage filter that made ugly photos look like professional art, and uploaded them in the background. 1 million users in 10 weeks.
• Stripe: Every internet business needed to accept credit cards, but banks forced founders through 5 weeks of paperwork, fax machines, and compliance audits. Patrick and John Collison reduced a 5-week banking nightmare into 7 lines of copy-paste code.
• ChatGPT: Over a billion workers and students wanted an intelligent machine to write emails, summarize docs, and debug code.

How did ChatGPT reach 1M users in 5 days? Two friction walls collapsed.

First, in 2017, ex-Google researchers published “Attention Is All You Need,” inventing the Transformer architecture, which collapsed the compute friction of training massive AI models.

Second, in November 2022, OpenAI took that intelligence out of complex Python API terminals, made it 100% free, and put it inside a simple chat box. Sam Altman tweeted the link to an audience of early adopters on X, and the pressurized ocean erupted.

• Nvidia: Every AI company needed massive parallel computing to run those Transformer models, but programming graphics chips was a nightmare. Nvidia built CUDA — software that let any AI researcher tap GPU supercomputing with standard code. That friction collapse turned Nvidia into a multi-trillion-dollar titan.

Can We Predict the Next 5 Waves Using the Formula?

Use the equation to look ahead. Where is the pressure boiling right now, waiting for the rock to be removed?

Forward-Testing: 5 Startup Waves from the Future

A real formula does not just explain the past; it predicts the future. Where is the subterranean pressure building right now, and where is friction about to collapse?

1. Autonomous Software Engineering Agents (Beyond the IDE): The Pressure: Companies have decades of legacy code debt and backlogged software ideas, but senior engineers cost $250,000+ a year. The Friction Collapse: Moving from AI autocomplete (where a human still types and debugs) to autonomous agents that take a plain-English ticket, spin up a sandbox, write the codebase, pass the tests, and deploy to production while you sleep.
2. Agentic Commerce (Business-to-Agent / B2A): The Pressure: Consumers hate opening thirty browser tabs, reading fake reviews, comparing shipping times, and typing their credit card and address into twenty different checkout forms. The Friction Collapse: AI shopping agents that know your size, budget, and preferences, negotiate directly with merchant APIs via machine-readable directories, and complete purchases autonomously with a single voice confirmation.
3. Zero-Latency Deterministic Inference Silicon: The Pressure: Every enterprise wants conversational voice AI for sales, support, and education, but waiting two seconds for an AI to “think” ruins human conversation.The Friction Collapse: Custom chips hardwired for language models that generate 500+ tokens per second, dropping voice latency under 100 milliseconds so talking to software feels indistinguishable from talking to a human.
4. Ambient Clinical Operating Systems: The Pressure: Doctors and nurses spend three hours every night typing patient notes and insurance billing codes into clunky hospital software — the #1 cause of medical burnout. The Friction Collapse: Ambient audio intelligence that listens quietly to the doctor-patient exam and automatically populates the medical chart, orders prescriptions, and clears insurance prior-authorizations in zero clicks.
5. General-Purpose Physical Robotics Brains: The Pressure: Aging populations and severe labor shortages in warehouses, Elder care, manufacturing, and home chores. The Friction Collapse: Universal foundation models for physical dexterity that allow a robot to learn a new physical task by watching a human do it once — eliminating months of custom industrial programming.

The Feature Paradox: Why Writing More Code Shrinks Your Growth

What does this formula mean for you tomorrow morning?

Does it mean you should memorize the formula like a schoolboy studying for a physics exam?

No.

It means you must completely reverse where you spend your energy — and avoid the fatal trap that kills technical founders.

When most technical founders see their growth stalling, their knee-jerk reaction is to open their code editor and ship more features. They add a new dashboard. They add custom permissions. They add seventeen settings toggles. They think that more code equals more value.

Now look at the formula and see what adding more features actually does:

THE FEATURE-BLOAT DEATH SPIRAL
              
  More Code & Features Added
             │
             ▼
  Product Becomes Complex (Needs Onboarding Modals, Wiki Docs,
  YouTube Tutorials, Live Chat, Email Support Tickets)
             │
             ▼
  Denominator (Friction / R_I) Multiplying ──► UP ↑
             │
             ▼
  Growth Velocity (Q = ΔE_L / R_I)         ──► PLUMMETS ↓

Every single time you add an unnecessary feature, you are increasing the denominator (Friction)

Because your app is now complex, the user cannot figure it out in ten seconds. Now they need an interactive onboarding tour. Then they need a five-minute YouTube tutorial. Then they need a help-center wiki. Then they get stuck and have to open a live chat widget or send an email to customer support.

You thought you were building a better product. Mathematically, you were piling rocks back into the borehole.

The formula teaches you the exact opposite discipline:

• Find a massive market with immense, pre-existing pressure underneath (Pressure).
• Write only the code that deletes steps, deletes clicks, deletes waiting, and deletes thinking (Friction).

How to Actually Extract Growth

Let me ask you one last honest question: Can you stop reading this essay right now, use the formula, and magically have 100,000 users by Monday?

No.

And I would be lying to you if I said you could.

Think back to Einstein’s E = mc². Knowing those four symbols on a piece of paper did not mean you could walk into your garage and build a nuclear power plant. To actually harness the formula, scientists had to learn what each component was made of, how to build a Geiger counter to locate uranium in the earth, and how to construct the reactor core without blowing themselves up.

A formula is the compass.

You still need the seismic instruments to find the oil.

Since you cannot manufacture market pressure out of thin air, how do you actually scan the internet to find where the pressure is hiding? How do you know if a market reservoir holds 100 billion barrels or just a shallow puddle before you waste three years of your life coding? And once you build the drill bit, how do you get the market to notice it in an internet controlled by noisy algorithms?

That is the exact reason I created The Startup Growth System.

I didn’t build it to be a 14-hour academic lecture series padded with fluff. I built it as a 90-minute operational cockpit that hands you the six specific instruments you need to apply the Growth Formula to your startup today:

• Thesis Theory & Customer Ikigai: Your seismic survey radar. Before you waste months writing code, these two frameworks test the top half of the formula — revealing where massive market pressure lives, why customers truly buy, and how to lock in a superior business model with uncapped “whale” clients.
• Simba’s Five Forces: How to map the hidden power dynamics of the modern internet — including the power of content creators, internet users, and platform dependencies — so you can turn user-generated momentum into a distribution moat.
• Content/Market Fit & Simba’s Content Matrix: Even the sharpest drill bit needs to reach the fault line. These frameworks show you how to engineer content that bypasses expensive ad auctions and captures the 97% of your market that is suffering in silence right now.
• Internet Presence Optimization (IPO): How to wire your startup into the fabric of search engines, AI answer engines, and algorithmic feeds so the internet routes high-pressure demand straight to your product automatically.

For years, you have been told that building a breakout startup requires being in Silicon Valley, burning millions on ads, or praying for a lucky lightning strike.

Now you see the code behind the Matrix.

Growth was never random. The pressure is already waiting beneath the ground. Stop shoveling dirt into dry holes — pick up the instruments, locate the fault line, collapse the friction to zero, and let the market erupt.