Home Blog

EP36: What Actually Works when Raising Money

0

Getting it right the first time & setting up for success

(Recorded Live on Clubhouse November 12, 2021) 

We were joined by Lil Roberts, CEO and founder Fintech platform Xendoo, for insights into raising capital for your startup. We learned where to look and what to look for in an investor, preparing to meet with potential investors, plus Lil’s top tips for perfecting your pitch.

Moderators: Colin C. Campbell, Michele Van Tilborg, Rachael Lashbrook, Jeff Sass

Guest: Lil Roberts

Sign up to our email and never miss an update on our special events, guest speakers, and more: https://startup.club/

How to Scale a Startup: What Actually Breaks

0

Most companies don’t die from lack of demand. They die from getting it.

How to scale a startup is really one question: what happens when the thing that was working stops working? The cruelty of it is that nothing looks wrong from outside. Revenue is up. The team is bigger. The press is better.

Inside, four systems are failing on different timelines, and no two fail at the same moment.

Here’s what breaks, in order, and the warning sign for each.

1. The Founder’s Calendar Breaks First

It goes before anything else, and almost nobody notices, because it doesn’t feel like a system failing. It feels like being busy.

At five people you sit in every conversation and that’s an advantage. At fifteen you sit in every conversation and it’s a bottleneck. At thirty you are the reason decisions take four days, because everything routes through the one person holding context on everything.

Warning sign: your team stops bringing you problems and starts bringing you approvals. They’ve learned that deciding without you carries risk. The moment that happens, your personal throughput caps your company’s speed.

The fix isn’t delegation. It’s context transfer. Delegating a task moves work. Transferring context moves judgment, so your team makes the next twenty decisions without you.

Rule: If you’re the fastest way to get an answer, you’re the slowest part of the company.

2. Hiring Breaks Second

Your first ten hires came through your network. People you knew, or people known by people you trusted. They arrived pre-vetted, culturally aligned, and willing to do whatever the week demanded.

That well runs dry somewhere between fifteen and twenty-five people. Then you hire strangers, and the hit rate collapses.

Founders respond by hiring faster, which is exactly wrong. A bad hire at forty people doesn’t just underperform. They hire more people like themselves, and now a whole branch of the org chart doesn’t work.

Warning sign: you describe a new hire as “we’ll see how they work out.” You never said that about hire number three.

What works:

  • Write the scorecard before the job post. Five outcomes, ranked. Can’t name what success looks like in twelve months? You don’t know what you’re hiring for.
  • Let someone who isn’t you make the final call on at least one hire per quarter. It’s the only way to learn whether your standard transferred.
  • Fire in weeks, not quarters. The cost of a bad hire isn’t their salary. It’s the good people who leave because you tolerated them.

Rule: Slow to hire is not a virtue. Slow to decide is the mistake.

3. Cash Breaks Third, and Quietly

This one kills companies that were, by every other measure, succeeding.

Growth eats cash. You pay for inventory, headcount, and infrastructure before the revenue those things generate arrives. The faster you grow, the wider the gap — and profitable-on-paper businesses run out of money in the middle of their best year.

I’ve watched it happen to businesses with excellent margins and a full pipeline.

Warning sign: you check the bank balance more often than the P&L. That instinct is correct. Listen to it. Your P&L tells you a story about the past. Your cash position tells you about next month.

What to install:

  • A rolling 13-week cash forecast. Weekly, not monthly. Thirteen weeks is long enough to see a problem coming and short enough to stay accurate.
  • A hard cash floor. Pick the months of runway below which you will not go, and act at that line instead of past it.
  • Your cash conversion cycle. Days from spending a dollar to collecting the revenue that dollar produced. Shorten it by fifteen days and you’ve funded a hire.

Rule: Profit is an opinion. Cash is a fact.

4. Decision-Making Breaks Last, and Worst

The endgame failure. This is the one that turns a fast company into a permanently slow one.

Early on, decisions happen in hallways. Somebody asks, somebody answers, done. Nobody writes anything down and it works fine, because everyone shares the same context.

Past fifty people that shared context is gone. The hallway conversation now excludes six people who needed to be in it.

So meetings appear. Then meetings to prepare for meetings. Then a process to manage the meetings.

Warning sign: two groups make the same decision and reach different answers. That’s not a communication problem. That’s a missing decision structure.

What to install:

  • A single owner for every decision. Not a committee. One name.
  • A split between reversible and irreversible. Make reversible decisions fast and alone. Give irreversible ones a week and a room. Most companies do this exactly backwards.
  • The “why” written down, not just the “what.” A decision with no documented reason gets relitigated every six months by whoever wasn’t in the room.

Rule: Speed doesn’t come from working faster. It comes from deciding once.

How to Scale a Startup: Replace Proximity With Systems

Every one of those four failures has the same root cause. Something that worked because of proximity stops working when proximity disappears.

So scaling is one job: replacing proximity with systems, on purpose, before you’re forced to. That’s the whole argument of the Scale chapter in Start. Scale. Exit. Repeat., and it’s the stage where founders resist hardest, because building systems feels like bureaucracy when you’re used to speed.

It isn’t. Bureaucracy is what you get when you build the systems late, in a panic, after something already broke.

Take the four above and ask which one is currently your constraint. Not which is most broken — which is holding back everything else.

Fix that one. Then look again, because it will be a different one.

Scaling isn’t a phase you complete. It’s a bottleneck you keep moving. Just make sure you’re the one moving it, and not the last person to notice it moved.

Focus on Something You and Others Love: A Founder’s Framework for the AI Era

0

Adapted for an AI world from Chapter 4 of Colin C. Campbell’s Start. Scale. Exit. Repeat.

In 1993, I made a decision that looked questionable on paper.

My partners and I had built ComputerLink, a profitable BBS company. The business worked. It had customers. It made money.

And we decided to shut it down.

Why?

Because we could see something much bigger coming: the internet.

We loved what we had built with ComputerLink—the community, the connectivity, and the ability for technology to bring people together. But we realized that the BBS itself wasn’t the thing we loved most.

It was the idea behind it.

The internet was becoming a vastly better vehicle for that idea.

So we took the assets of a profitable company and used them to start Internet Direct, venturing into an industry that was still largely uncharted.

More than three decades later, entrepreneurs are facing a remarkably similar moment with artificial intelligence.

AI is changing how companies are built, how work gets done, and what customers expect. New tools and business models seem to appear every week.

That creates enormous opportunity.

It also creates enormous distraction.

The founders who thrive in this environment won’t necessarily be the ones who chase AI the fastest. They’ll be the ones who understand what they truly care about, what their customers care about, and how AI can become a better vehicle for delivering it.

Here is a framework for doing exactly that.

1. Separate What You Love From the Vehicle Delivering It

One of the most important lessons I’ve learned as an entrepreneur is this:

Don’t fall so deeply in love with your business that you go down with it.

Fall in love with the purpose instead.

In the early 1990s, BBS operators had built thriving businesses. When the internet arrived, some couldn’t let go. They had fallen in love with the vehicle rather than what the vehicle accomplished.

The same danger exists today.

Maybe you love your SaaS product.

Maybe you’ve spent years building a marketplace, agency, app, consulting business, or software platform.

Then AI arrives and suddenly customers can accomplish part of what your product does with a prompt.

The wrong response is to protect yesterday at all costs.

Ask instead:

What did customers actually love about what we built?

Was it the software itself?

Or did they love saving time?

Making better decisions?

Feeling more creative?

Connecting with other people?

Growing their business?

Removing frustrating work?

Once you understand that, AI stops looking purely like a threat. It can become the next vehicle for delivering the thing people already value.

That leads to the first question in the framework:

What do we love about the problem we’re solving—and is there now a better way to solve it?

2. Don’t Confuse AI Excitement With Customer Love

There’s another problem with transformational technologies: entrepreneurs want to build everything.

I know this problem well.

I’ve joked that entrepreneurship should be classified as a drug. A new idea can produce an incredible rush, and serial entrepreneurs often don’t struggle to generate ideas.

They struggle to pick one.

AI has multiplied that temptation.

Every week brings another model, agent, platform, capability, or startup category. Suddenly you can imagine dozens of businesses that weren’t technically possible a few years ago.

But possible doesn’t mean valuable.

And interesting doesn’t mean customers will care.

Instead of asking:

What can I build with AI?

Try asking:

What do people already desperately want that AI now allows me to deliver dramatically better?

That distinction matters.

Technology can create capability.

Customers create businesses.

Before committing significant time and capital to an AI opportunity, look for three overlapping signals:

Founder Love:
Would you still care about solving this problem after the novelty of the technology disappears?

Customer Love:
Do people genuinely want the outcome enough to change their behavior, recommend the product, or pay for it?

AI Leverage:
Can AI make the solution substantially faster, cheaper, easier, smarter, more personalized, or previously impossible?

The strongest opportunities sit at the intersection of all three.

Love it. Prove others love it. Then use AI to amplify it.

3. Avoid the Shiny-Object Trap

In previous technology revolutions, entrepreneurs could spend years riding a trend.

AI cycles can move much faster.

Today’s breakthrough can become tomorrow’s commodity.

That makes focus even more valuable.

When every founder can rapidly prototype ten ideas, the competitive advantage isn’t necessarily producing the eleventh.

It may be having the discipline to decide which one deserves the next ten years of your life.

Ask yourself:

If AI stopped being exciting tomorrow, would I still care deeply about this problem?

That’s a powerful filter.

Because building a meaningful company remains hard.

There will still be difficult customers.

Hiring mistakes.

Cash-flow problems.

Competitors.

Failed experiments.

Slow months.

Products that don’t work.

Strategies that have to be rewritten.

AI may accelerate parts of entrepreneurship, but it doesn’t eliminate the emotional roller coaster of building a company.

Which is why love still matters.

4. Build Something Humans Still Care About

The more capable AI becomes, the easier it is to become obsessed with what machines can do.

Founders should spend just as much time thinking about what humans want.

People still want to save time.

They still want to belong.

They want status, convenience, security, entertainment, health, wealth, connection, confidence, and meaning.

They want someone to understand their problems.

They want products that make their lives better.

Those human motivations don’t disappear because the technology underneath a business changes.

So don’t start your strategy with the model.

Start with the human.

Ask:

Whose life gets meaningfully better if we succeed?

Then ask:

How does AI allow us to improve that outcome by 10x?

That produces a very different company than simply attaching AI to an existing product because the market expects you to.

5. Make Sure the Idea Reflects Your Values

Love is difficult to quantify.

One useful way to evaluate it is through your values.

Write down the ideas you’re considering and ask what genuinely excites you about each one.

Then ask:

Does this idea reflect something I care deeply about?

If sustainability matters to you, how does the company contribute to it?

If education matters, how does the company help people learn?

If entrepreneurship matters, how does the company help founders succeed?

If you care about improving people’s lives through technology, where does that show up in the product?

This becomes especially important with AI because founders aren’t simply choosing what they can automate.

They’re choosing what they should automate—and what role they want technology to play in people’s lives.

Values can become a strategic filter.

Just because AI can do something doesn’t mean that’s the company you should spend a decade building.

6. Use Other People’s Excitement as Evidence

Loving your own idea isn’t enough.

Other people need to love it too.

Talk to potential customers. Show them prototypes. Explain the vision. Watch their reactions.

But don’t only listen to what people say.

Look at what they do.

Do they ask when they can use it?

Do they introduce you to someone else who needs it?

Do talented people want to join you?

Do potential partners start suggesting ways to help?

Most importantly:

Will customers pay?

Authentic enthusiasm has a way of spreading.

When the founder loves the mission, customers love the outcome, and talented people want to participate, you may have found something worth pursuing.

7. Let AI Change the Business Without Changing the Mission

This may be the most important lesson of all.

ComputerLink wasn’t our mission.

It was a vehicle.

When a better vehicle arrived, we moved.

Entrepreneurs in the AI era should develop the same willingness.

Your product may change.

Your interface may change.

Your pricing model may change.

Tasks that once required twenty employees may eventually require five employees working with AI agents.

Entire features may disappear.

Your competitive advantage may move from software functionality to proprietary data, distribution, community, trust, workflow integration, brand, or customer relationships.

That’s okay.

Preserve the reason the company deserves to exist. Be willing to reinvent almost everything else.

The AI Founder Love Test

Before pursuing your next idea—or deciding whether AI should transform your existing company—answer these seven questions:

  1. What do I actually love about this idea?
  2. What outcome do customers love?
  3. Would I care about this problem if AI weren’t fashionable?
  4. Does solving it reflect my values?
  5. Does AI materially improve the solution rather than merely decorate it?
  6. Are customers demonstrating love through behavior, not just compliments?
  7. Am I willing to change the vehicle while protecting the underlying mission?

If you can’t answer those questions clearly, keep exploring.

If you can, focus.

Because the abundance created by AI makes focus more important, not less.

We’re entering a period in which entrepreneurs can build more, test faster, automate more, and pursue opportunities that would have required enormous teams and capital only a few years ago.

But that doesn’t mean you should pursue all of them.

Life is still too short to spend your time, attention, and resources building something neither you nor your customers truly care about.

Find the problem you love.

Make sure other people love the outcome.

Use AI to build a dramatically better way of delivering it.

Then focus long enough to make it matter.

And once you’ve found that idea, two timeless questions remain:

Can you scale it?

And can you defend it?

The #1 Skill for the AI Age: Learn How to Learn

0

The #1 Skill for the AI Age: Learn How to Learn

https://www.clubhouse.com/i/the-1-skill-for-the-ai-age-learn-how-to-learn/npX7t2E1

Global Startup Funding Has a Passport Now

0

Founders built 43.6% of the world’s new billion-dollar companies outside the United States this year. You don’t have to move anymore. Global startup funding came to you.

In the first half of 2026, 195 companies crossed a billion-dollar valuation — more in six months than in all of 2025. Eighty-five of them were built outside the U.S.

China produced 38. Last year it produced 10.

The Money Is Building Fences to Keep Founders In

The clearest signal landed on August 11. The European Commission launched the Scaleup Europe Fund, targeting €5 billion — about $5.7 billion — and selected the Swedish asset manager EQT to run it through an open call.

The first €1 billion has already closed, funded by the European Commission alongside institutional investors. The founding investor list reads like a map of European capital: Allianz, the Dutch pension manager APG, Santander’s Mouro Capital, CriteriaCaixa, Denmark’s EIFO and Novo Holdings, and a stack of Italian foundations. The ambition is to grow it to €25 billion.

Its first check co-led ICEYE’s Series F at a valuation above $11 billion.

ICEYE’s CEO said the purpose plainly: the fund “exists so companies like ours don’t have to leave Europe to compete globally.”

Read that again. A fund targeting five billion euros, built to stop the brain drain to Silicon Valley.

Europe watched its best companies grow up and move away for two decades. Now it writes checks big enough to make staying rational.

Not Where You Live. What Your Money Understands.

The old constraint was geography. You were near the money or you weren’t.

The new constraint is legibility — whether the capital that exists around you can understand what you’re building.

Look at where the new unicorns clustered: robotics, AI, AI infrastructure, defense, semiconductors, aerospace, financial services, healthcare, biotech. That isn’t a random spread. That’s a map of what sovereign-scale capital wants right now — strategic industries governments have decided they can’t afford to import.

Build in one of those categories outside the U.S. and more capital is available to you today than at any point in your career.

Build a consumer app in a market with no consumer-app funds and geography still bites. Then move.

Rule: Don’t ask where the money is. Ask what your money understands.

Speed Is the New Signal in Global Startup Funding

One number in the H1 data deserves more attention than it’s getting. Nineteen companies raised fast follow-on rounds that doubled their valuations, often inside six months. Etched went from $5 billion to $10 billion in half a year.

The whole cohort added roughly $440 billion in value against $80 billion raised across their entire lifetimes.

That ratio tells you something. Investors aren’t paying for years of steady compounding. They’re paying for evidence of acceleration.

Which changes what you measure. Not “are we growing?” — everyone is growing. Is our rate of growth increasing? A company going 20% → 30% → 45% tells a story. A company going 40% → 40% → 40% tells a much quieter one, even though the absolute numbers look better.

If You’re Not Building a Unicorn

Most of you aren’t, and shouldn’t be. So here’s the practical version.

1. Audit your local capital before you audit Sand Hill Road. Government-backed funds, regional development capital, strategic corporate investors, sovereign wealth programs.

This money is less glamorous and often less demanding. Founders skip it because it doesn’t come with a famous logo. Bad reason.

2. Find out what your government decided to fund. Every major economy publishes a list of strategic sectors. Sit on one and you have access to capital that has nothing to do with venture returns. Sit outside it and know that going in.

3. Build for a market, not a zip code. Remote work solved the team question. The harder question is where your customers are, and whether you understand them well enough to sell without being in the room.

4. Read the terms, not the headline. Public-private capital comes with strings — reporting requirements, domicile conditions, hiring commitments.

Some of those are fine. Some will constrain an exit later. Know which before you sign.

The Community Advantage

In Startup.Club sessions I hear from founders in Lagos, São Paulo, Tallinn, Bangalore, and Fort Lauderdale inside the same hour. Ten years ago that mix was impossible, and the founders outside the traditional hubs operated at a real information disadvantage.

That gap closed. The playbooks are public. The tools are identical everywhere. The conversations are open.

The remaining edge isn’t access. It’s judgment — knowing which advice applies to your market and which someone wrote for a different one.

Capital got a passport. So did knowledge.

The founders who win stop waiting for permission from a place they don’t live.

Record Startup Funding Is Not a Strategy

0

Venture capital just set a record, and almost none of it is coming to you.

July 2026 delivered $65 billion in record startup funding. Double last July. Fourteen companies raised billion-dollar rounds inside thirty-one days, the highest monthly count on record. AI took $35 billion of it, more than half of every venture dollar on the planet.

Read those numbers fast and you’ll conclude money is easy again. Read them slowly and you’ll see something else.

Fourteen Companies Took a Fifth of the Money

Do the arithmetic nobody does. Fourteen billion-dollar rounds inside a $65 billion month means a handful of companies absorbed at least a fifth of all the capital raised worldwide. Blue Origin took $10 billion by itself, July’s largest deal.

August opened the same way. In the first week alone, Hadrian raised $1.37 billion for manufacturing. Base Power raised $1 billion for energy storage. Valar Atomics raised $1 billion for nuclear.

Those are not startups. They are industrial programs wearing startup clothing.

Now look at who writes the checks. In 2025 the ten largest U.S. venture funds took nearly a third of all the money that limited partners put into U.S. venture. Andreessen Horowitz recently raised more than $15 billion across five funds — over 18% of all U.S. venture fundraising in 2025.

One firm. Almost a fifth of the market.

Meanwhile first-time fund formation fell to its lowest level in over a decade.

Fewer funds. Bigger funds. Bigger checks to fewer companies. That is not an open market. That is a concentrating one.

Record Startup Funding Is Real. It Just Isn’t Yours.

A concentrating market still produces euphoric headlines. Founders read them, decide the window is wide open, and go raise instead of going to sell.

Then they spend seven months in a process that was never available to them.

I’ve watched founders in Startup.Club sessions burn three-quarters of a year on a raise while a competitor spent the same seven months signing customers. Guess which one still owns their company.

The money did come back. It came back for a specific profile: category leaders, capital-intensive hard tech, and anything with AI in the first line of the deck and revenue behind it. If that isn’t you, the record numbers describe a party in a different building.

Revenue Is the Only Round Nobody Can Cancel

Term sheets get pulled. Diligence drags. Lead investors go quiet in December and reappear in March with a lower number.

I have lived every one of those.

A customer paying you does none of it.

Rule: Revenue is the only funding round nobody can revoke.

This is not anti-venture. Venture capital built companies I’m proud of.

It is anti-default. Raising money became the reflex answer to every problem, and the reflex is expensive. You give up ownership. You give up control. You take on a growth expectation calibrated to a fund’s return model instead of your business’s reality.

Before you raise, answer three questions honestly:

  1. What does the money buy that time cannot? If the answer is “speed,” ask whether speed is worth 20% of your company.
  2. Would this business work if nobody ever funded it? If no, you don’t have a business. You have a project that needs a subsidy.
  3. Can you name the specific milestone this round unlocks? Not “growth.” A number, a date, a proof point.

Miss any of the three and you’re not fundraising. You’re procrastinating with a pitch deck.

What Concentration Does to the Middle

There’s a second-order effect most founders miss. When capital concentrates at the top, the middle gets quieter, not louder.

I hear it constantly from founders in our sessions: the $2 million seed round that used to close in six weeks now takes months. The reason is structural. Funds that used to write $2 million checks either got much bigger or stopped existing, and a multi-billion-dollar fund cannot deploy $2 million efficiently. So it doesn’t.

That leaves a real gap, and a real opportunity. The businesses in that gap run on customer money instead of investor money. They grow slower. They also survive the downturns that erase companies holding eighteen months of runway and no revenue.

In Start. Scale. Exit. Repeat. I argue the Start phase exists to prove the thing works before you pour fuel on it. A concentrating capital market doesn’t change that. It enforces it.

Watch the Exits, Not the Entrances

Want a signal that actually matters to your business? Stop tracking funding rounds. Start tracking exits.

The $65 billion got the headlines. The number with real consequences was quieter: in the same month, twelve venture-backed companies listed publicly above $1 billion. Acquirers buying companies means acquirers will buy your company.

Funding rounds only tell you which competitor just got a war chest.

One is a market you can sell into. The other is a market you have to survive.

What to Do Monday

Pick the one that applies:

  • Pre-revenue: stop building the deck. Go get three paying customers. The deck writes itself afterward. You won’t need it.
  • Growing on revenue: resist the pull. A record funding month is not evidence you should raise. It’s evidence that the companies raising sit in a different weight class.
  • Genuinely raising: target the funds that still write your size of check. The mega-funds are not your market, no matter how loud they get.

The headlines will keep growing. Sixty-five billion will look small by December.

None of that builds your company. Customers do.

Build What You Love in an AI World or You’ll Probably Quit!

0

Build What You Love in an AI World or You’ll Probably Quit!

https://www.clubhouse.com/i/build-what-you-love-in-an-ai-world-or-youll-probably-quit/5szqwlnb

Decision fatigue, stress and workload – CE

0

Decision fatigue, stress and workload – CE

https://www.clubhouse.com/i/decision-fatigue-stress-and-workload-ce/xtJgd9bL

Catching the Next Tech Wave in an AI World

0

Catching the Next Tech Wave in an AI World

https://www.clubhouse.com/i/catching-the-next-tech-wave-in-an-ai-world/x69Qiir3

Catching the Next Wave Is Critical – CE

0

Catching the Next Wave Is Critical – CE

https://www.clubhouse.com/i/catching-the-next-wave-is-critical-ce/xtJgd9bL

Catch the Next Wave: Why AI Timing Matters More Than Ever

0
Part of Startup Club’s ongoing series exploring Colin C. Campbell’s Start. Scale. Exit. Repeat.—reimagined for the AI era. This post is adapted from Chapter 3: Catching the Next Wave Is Critical.

There’s an old saying in entrepreneurship about being in the right place at the right time. But after building multiple startups and watching countless founders succeed—or fail—it’s clear that success is less about luck and more about finding the right wave at the right moment.

Today’s wave is unmistakable.

Artificial Intelligence.

But just because AI is transforming every industry doesn’t mean every AI startup will succeed. The lesson from Chapter 3 is more relevant than ever: great founders don’t simply build great products—they build products that arrive when the market is ready.

Don’t Build Before the Wave

History is full of brilliant ideas that failed because they were too early.

The technology worked.
The founders were talented.
The execution was solid.

The market simply wasn’t ready.

Colin shares the story of Barpoint.com, an idea that let shoppers scan barcodes to compare prices and reviews instantly. Today that sounds obvious. In the early 2000s, before smartphones and QR codes became commonplace, it was simply too early. The surfboard was built—but there wasn’t a wave to ride.

AI founders should ask themselves the same question: Is the market ready for what I’m building?

AI Has Crossed the Chasm

One of the biggest concepts in entrepreneurship comes from Geoffrey Moore’s Crossing the Chasm.

New technologies are first embraced by innovators and early adopters. The real opportunity comes when they cross into the early majority and become mainstream.

For years, AI lived mostly with researchers and technical enthusiasts.

Today, that’s changed.

Millions of people use ChatGPT, Claude, Gemini, Midjourney, Cursor, Perplexity, and countless AI-powered products every day. Businesses aren’t asking whether they’ll adopt AI anymore—they’re asking how quickly.

That means the opportunity has shifted.

It’s no longer enough to build an AI model.

The winners will build businesses that make AI easier, faster, and more valuable for everyday users.

Winning Isn’t About Being First

Many founders obsess over being first to market.

Chapter 3 argues something different.

Being first matters far less than being ready when demand explodes.

We’ve seen this repeatedly in AI.

OpenAI wasn’t the first company researching language models.

GitHub Copilot wasn’t the first coding assistant.

Perplexity wasn’t the first search engine.

Cursor wasn’t the first IDE.

They won because they delivered exceptional products at precisely the moment customers were ready.

Timing compounds execution.

Don’t Force New Behaviors

One of the biggest mistakes startups make is trying to convince customers to behave differently.

People rarely change habits just because your startup exists.

Instead, the best products fit naturally into workflows customers already have. Colin points out that companies like Uber and Airbnb transformed industries without forcing customers to learn entirely new behaviors—people already took taxis and booked accommodations.

The same principle applies to AI.

Ask yourself:

  • Does this replace work people already do?
  • Does it save time?
  • Does it remove friction?
  • Does it integrate with existing tools?

If the answer is yes, you’re surfing the wave.

If you’re asking users to completely rethink how they work, adoption becomes much harder.

Make AI Invisible

One of Colin’s recurring themes is simple:

Make it easy. Market easy.

This may be the biggest opportunity in AI today.

Customers don’t actually want AI.

They want faster hiring.

Better marketing.

Cleaner code.

More sales.

Better customer support.

Less paperwork.

The companies that win won’t necessarily have the smartest models.

They’ll remove the most friction.

Great AI products make complex technology feel effortless.

Focus Before You Expand

Another key takeaway is to strive for depth before breadth.

Rather than solving everything for everyone, dominate a single niche first. Geoffrey Moore’s “bowling pin” strategy emphasizes winning one focused market before expanding into adjacent ones.

AI makes this easier than ever.

Instead of building “AI for everyone,” build:

  • AI for dentists
  • AI for real estate investors
  • AI for construction firms
  • AI for accountants
  • AI for podcast creators

Depth creates trust.

Trust creates referrals.

Referrals create momentum.

Momentum creates scale.

Every Wave Creates New Opportunities

When Colin first wrote this chapter, AI was already appearing as one of the next major technology waves entrepreneurs should pay attention to.

Just a few years later, that prediction has become reality.

But the biggest opportunities are no longer in building foundational AI models.

They’re in applying AI to industries that haven’t yet been transformed.

Healthcare.

Education.

Legal.

Manufacturing.

Construction.

Government.

Financial services.

Every major shift creates thousands of startup opportunities—not because the technology changes, but because entrepreneurs discover new problems worth solving.

Final Thought

Entrepreneurship has never been about predicting the future perfectly.

It’s about recognizing when the future has finally arrived.

AI is no longer a distant trend.

It’s today’s wave.

The founders who succeed over the next decade won’t simply build with AI—they’ll understand timing, reduce friction, solve real problems, and deliver exactly when the market is ready.

That’s how companies don’t just launch.

That’s how they scale.

Read the Book Series

This article is part of Startup Club’s series on Start. Scale. Exit. Repeat. by Colin C. Campbell, adapted for an AI-first world. In each chapter, we’re revisiting timeless startup principles through the lens of today’s rapidly evolving technology landscape—helping founders build businesses that are ready for the next wave. Check out our Chapter 2 article about taking ideas to business reality.