Everyone in Silicon Valley seems to be obsessed with the quick flip. Build a feature, get some traction, and sell to a tech giant for a nice, tidy exit. I’ve done it twice, with RemoteTeam getting acquired by Gusto and MovieLaLa by Gfycat. Those were great outcomes, but I’m here to tell you that the obsession with acquisitions is a mistake, especially in the world of AI. If you’re building an AI company, you should be building for the long game: an Initial Public Offering (IPO).
I get it. The allure of a fast exit is strong. It de-risks your life and gives you a great story to tell. But aiming for an acquisition from day one fundamentally limits your vision. You build a company that’s designed to be a feature, a bolt-on to someone else’s platform. You’re not building a self-sustaining institution. When I look at my most successful angel investments—companies like Anthropic, OpenAI, and Scale AI—they aren’t thinking about which tech giant will buy them. They're thinking about how to fundamentally change the world and build a company that will last for decades. That’s the IPO mindset.
The Problem with Building for Acquisition
When your goal is to be acquired, you start making compromises. You might avoid entering a market segment because a potential acquirer is already there. You might build your tech stack to be easily integrated with a specific company’s platform, rather than what’s best for your product. You’re essentially building a very expensive resume for a job interview with a corporate development team.
I saw this firsthand. In the early days of one of my companies, we had a potential acquirer show a lot of interest. For a few months, our product roadmap started to subtly shift. We’d prioritize features they mentioned in passing, and we’d spend less time on the bolder, more ambitious ideas that got us excited in the first place. We caught ourselves just in time. We realized we were building their company, not ours. We walked away from the talks and refocused on our own vision. It was the best decision we ever made.
Building for an IPO forces you to think differently. You have to build a real business, not just a cool product. That means focusing on three key areas: a durable competitive moat, a massive market opportunity, and a path to profitability.
Your Competitive Moat in AI is Not the Model
So many AI founders I meet think their model is their moat. They’ll say, “We have a proprietary model that’s 2% more accurate on this specific benchmark.” Here’s the hard truth: in six months, a new open-source model will likely surpass yours. Your model is not the moat. Not in the long run.
So what is? I look for a few things when I’m doing due diligence on an AI startup:
- Proprietary Data: Do you have a unique, compounding data asset that no one else can easily replicate? This is the single most important factor. If your model gets better with every new user and every new piece of data, you have a powerful data flywheel. This is the kind of moat that gets investors excited.
- System Integration: How deeply is your product embedded in your customers’ workflows? If ripping you out would be a massive headache for them, you have a strong moat. This is less about the AI itself and more about building a complete solution to a painful problem.
- Brand and Trust: In a world of black-box algorithms, trust is a huge differentiator. If you can build a brand that stands for accuracy, reliability, and ethical AI, customers will choose you over the faceless competition. This is especially true in regulated industries like finance and healthcare.
Don’t just tell me about your model. Tell me about your data flywheel, your customer lock-in, and the trust you’re building in the market. That’s your real competitive advantage.
Sizing the Market: Go Big or Go Home
When you’re building for an IPO, you need to be playing in a massive market. Public market investors want to see a path to billions of dollars in revenue, not millions. This is where many founders get tripped up in their pitch decks. They’ll present a Total Addressable Market (TAM) slide that’s either laughably small or completely unbelievable.
Your TAM isn’t just the current market size. It’s about how your AI solution will expand the market. You’re not just taking a piece of the existing pie; you’re baking a whole new one. You need to articulate a clear vision for how the world will be different once your product is widely adopted.
Here’s a practical tip: don’t just use a top-down number from a Gartner report. Build your market size from the bottom up. How many potential customers are there? What’s a realistic price point they would pay? How does that multiply out? This shows you’ve done your homework and have a credible plan to capture that market. It’s the difference between saying “We’re targeting the $100 billion cloud computing market” and “There are 500,000 companies in our target segment, and we believe we can capture 10% of them at an average contract value of $50,000 per year, creating a $2.5 billion opportunity for us.” See the difference? One is a fantasy, the other is a strategy.
The IPO Path: It’s a Marathon, Not a Sprint
Building a company worthy of an IPO is not easy. It requires a different level of discipline and long-term thinking. You need to build a management team that can operate at public-company scale. You need to have your financials and metrics dialed in. You need a story that will resonate with public market investors, which is a very different audience than a VC partner.
This is the long game. It’s about building a company that will outlast you. It’s about creating a platform for innovation that will define an entire industry. The financial rewards of an IPO can be far greater than an acquisition, but more importantly, the impact you can have is an order of magnitude larger.
So, my advice to AI founders is this: stop thinking about the quick flip. Start thinking about the long game. Build a real business with a durable moat. Go after a massive market. And set your sights on ringing that bell at the New York Stock Exchange or Nasdaq. It’s a harder path, but it’s the one that leads to building something truly meaningful. It’s the path that pays off.
Frequently Asked Questions
Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.
How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.