The value of a contrarian startup hypothesis

You start a startup when you believe you can find a viable solution to a valuable enough problem for a big enough market. Whether defined explicitly or not, behind every startup is a hypothesis like this. Some startup hypotheses are low risk because they contain confident assumptions. When a startup contains high-risk assumptions, believing in the undergirding theory is challenging. If your target market is tough to define and access, perhaps because nobody has targeted this market before, it won’t be easy to sell to them. If the problems they face are challenging to identify and understand, finding the most crucial problem to solve will be difficult. If novel, untested, and poorly understood technologies are required to solve your chosen problem, there is a high chance that you won’t be able to deliver a solution.

Conventional hypothesis Contrarian hypothesis
Market Easy to access. Tough to define and access.
Problem Obvious and common. Emerging or difficult to pinpoint.
Solution Obvious and achievable with off-the-shelf tech. Requires novel technology.
Competition Crowded markets; easy to copy. Nascent markets; difficult to copy.
Payoff if correct Mediocre. Extreme.

The less risky a startup strategy is, the more copyable it is. So, low-risk markets are crowded. Whether it’s the problem you tackle, the solution you offer, the market you target, or the technology you build, building a startup around a contrarian worldview will make your strategy look crazy to outsiders. They will think you are wasting your time; nobody will buy your product. For many startups, the outside perspective is correct, and they fail. But startups when these startups succeed, they succeed big. Peter Thiel claims that all great startups are founded around a secret:

Every great business is built around a secret hidden from the outside. A great company is a conspiracy to change the world; when you share your secret, the recipient becomes a fellow conspirator.

There are two kinds of secrets: those about nature and those about people. Natural secrets involve science, and their discovery can lead to important technological breakthroughs. Secrets about people are different – they involve things that people don’t know about themselves or what they want.

Startups with big secrets

Airbnb is the perfect example of a startup built on a seemingly ridiculous hypothesis. The “secret” hypothesis behind Airbnb is the realisation that people are willing to rent out their spare rooms or homes to strangers and that travellers are happy to stay in a strangers’ home. The founders of Airbnb discovered that there was untapped value in people’s unused spaces and that the conventional wisdom that people wouldn’t want to lodge in a stranger’s home was incorrect.

Of course, the idea behind Airbnb seemed ridiculous until it didn’t. And now, it is ubiquitous. Companies like Airbnb can thank their contrarianism for the following:

Conventional wisdom machines

Information has rapidly become cheaper to distribute, store, and consume thanks to the printing press, the telegram, radio, television, cable television, the internet, search engines, and social media. The implications of these technologies have driven many of the major world events in modern history. Today, information costs are effectively zero. You can download the entirety of Wikipedia onto your smartphone. You can even run a large-language model on your smartphone if you’re savvy.

Now that the world’s information is at our fingertips, it is incredibly easy to become acquainted with conventional wisdom on any topic. Wikipedia, where users aggregate and summarise the contents of the internet, was the first great conventional wisdom machine; ChatGPT is the ultimate one5. It can essentially generate a Wikipedia entry for any topic you want, even if the existing content on the internet hasn’t presented knowledge in the way you’ve requested before. Wikipedia is artisanal ChatGPT — a quaint attempt to manually create what LLMs can create automatically.

These tools are helpful because, most of the time, conventional wisdom is what you want. When seeking medical or legal advice, the best answer is usually the generally accepted answer. General expertise is now free.

Value of differentiated thinking

When you build a startup, you need more than just conventional wisdom. Conventional wisdom never contains those secrets that lead to significant innovations.

When most of the world was information poor, you could create big businesses by copying other people in other locations. An entrepreneur inspired by the New York Times could copy the New York Times without competing with it by simply launching in new geographies. This duplication was done by leveraging privileged access to conventional wisdom. Now, everybody has access to this knowledge. As the internet destroys space and time, many companies are digital, and digital companies are increasingly global because customers are easy to access from anywhere.

The globalisation and democratisation of knowledge and markets, coupled with AI Copilots, means divergent thinking is more valuable than ever. When everyone can be an expert on the conventional view of any topic, ideas that go against convention (and turn out to be correct) are even more advantageous. When anyone can ask an AI for the best way to achieve something, people with a better answer are precious. Most contrarians are wrong, but when they’re right, they’re rich.

There are a few implications for this:

“All models are wrong, but some are useful.”

— George Box

The current generation of AI tools cannot run every aspect of your startup. But in areas where conventions are good enough, AI can run the show. In areas where differentiation is required, AI will remain a useful tool, but defiance of the convention should be the goal. One day, AI models might be advanced enough to independently uncover the secrets that begat great businesses. Until then, they have only increased the value of the most important natural resource for innovation: secrets.

  1. This can backfire if you fail to recruit the best technical talent for your solution and competitors build even better technology. ↩︎

  2. Many Airbnb and Uber use cases do not overlap with hotel or taxi use cases. This untapped demand is why introducing these products expanded the overall market. Even if the founders and investors believe their goal is to disrupt incumbents, truly novel technologies often create new markets more than they disrupt what exists. ↩︎

  3. Another way of saying this: some technologies disrupt incumbents, while others disrupt whole industries and society. ↩︎

  4. Many startups change the world but leave others to capture the value they create. ARM, for example, is a world-changing company in the semiconductor industry. But most of the value they’ve created has been captured by TSMC and Apple. With a better pricing strategy, they could be a more successful business. ↩︎

  5. This is why articles written entirely by ChatGPT are not very compelling yet. They regurgitate information that readers can find elsewhere. For some purposes, that might be good enough, but differentiation is too valuable for many. ↩︎

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