Your Competitors Are Laughing at You. Good.
Why the best products start as jokes - and how to find the market nobody’s fighting for
In 2007, Steve Ballmer stood in front of a camera and laughed.
“$500? Fully subsidized with a plan?” He could barely hold it together. “That is the most expensive phone in the world. And it doesn’t appeal to business customers because it doesn’t have a keyboard.”
He was talking about the iPhone.
Nokia controlled 51% of the global mobile phone market at the time. Microsoft was everywhere. BlackBerry owned the enterprise. Apple had just 5% and a device that most industry experts called a toy.
Six years later, Nokia lost 90% of its market value. BlackBerry became a cautionary tale. And that “toy” redefined how 4 billion people interact with technology.
Here’s what I find fascinating about this story. It’s not that the experts were wrong. It’s that they were wrong because they were experts. They knew the phone market. They knew what customers wanted. They knew what worked. And all of that knowledge became the exact thing that blinded them.
Tony Fadell - the guy who built the iPod and co-created the iPhone - writes about this in his book Build. His core argument is simple: the first version of your product should be disruptive, not evolutionary. You’re not supposed to make a better version of what exists. You’re supposed to make something that changes how people think about the category entirely.
That idea has been living in my head for the past few weeks. Not as theory - but as a lens for what I see happening in the market right now.
Because we’re in a moment where disruption isn’t just possible. It’s easier than ever. And almost nobody is doing it right.
The Problem With How Most Founders Think About Products
Here’s the standard playbook in 2026:
You open ChatGPT. You type “give me a startup idea” or “what’s a good niche for a SaaS product.” The AI gives you something that sounds reasonable - habit trackers, finance apps, productivity tools. You think “great, that makes sense” and start building.
This is the most expensive mistake you can make. And I don’t mean expensive in money. I mean expensive in time - months or years spent in a market where the math doesn’t work in your favor.
Let me show you why.
The habit tracking app market is projected to reach $14.94 billion by 2026. Sounds massive, right? Now look deeper. Over 52% of users quit within the first 30 days. The market is so oversaturated that differentiation is nearly impossible. CPC for paid acquisition keeps climbing. Organic growth? Good luck ranking when there are hundreds of competitors with established SEO and millions in funding.
And here’s the trap: if you ask AI “is the habit tracking market a good opportunity?” - it will say yes. Because the market IS big. Because the data IS positive at a surface level. AI pulls from existing information, from articles that analyze these markets favorably, from optimistic projections. It doesn’t know what it’s like to actually try to acquire users in a space where every keyword costs $3+ per click and retention is garbage.
This is what I call the “AI research trap.” You’re not getting bad information. You’re getting incomplete information. And incomplete information in market selection is worse than no information - because it gives you confidence in the wrong direction.
The same pattern plays out in finance apps, subscription trackers, to-do lists, note-taking tools. Massive markets. Thousands of competitors. Brutal unit economics for anyone without venture capital.
Meanwhile, there are hundreds of niches where the opportunity is wide open. But nobody looks at them because they seem too small.
The Disruption Nobody Sees Coming
Here’s what most people miss about the current moment.
We have roughly 4.7 billion smartphone users globally. A huge chunk of them have never meaningfully used AI. Not ChatGPT. Not AI features in their apps. Nothing. When you show these people a product that uses AI to solve a real problem they have - something as simple as automating a workflow they do manually every day - their reaction isn’t “oh, another AI tool.” Their reaction is “wait, this is possible?”
That reaction - that genuine surprise - IS disruption. Not in the Silicon Valley “we’re disrupting the $50B market” sense. In the real sense. You’re fundamentally changing how someone thinks about what’s possible.
And this is where it connects back to the iPhone story. Apple didn’t make a better phone. They made a product so different that competitors literally couldn’t evaluate it using their existing frameworks. Nokia looked at the iPhone and saw a phone without a keyboard. They missed that it wasn’t a phone at all - it was a pocket computer that happened to make calls.
The same thing is happening right now with AI products. Incumbents in most industries look at AI features and see them through the lens of their existing product. “We’ll add AI to our dashboard.” “We’ll use AI for better recommendations.” They’re building better keyboards while someone is about to remove the keyboard entirely.
Tony Fadell has this concept in Build that I love: “The best ideas are painkillers, not vitamins.” Vitamins are nice to have. You forget to take them and nothing happens. Painkillers solve an immediate, urgent problem. You know instantly if they’re working.
Most AI products being built right now are vitamins. They make existing workflows slightly faster or slightly easier. The real opportunity is building painkillers - products that solve problems people didn’t even know could be solved.
Why “Too Small” Is Your Biggest Advantage
Now here’s where my thinking diverges from what most people teach.
Conventional wisdom says: find a big market. Total addressable market of $1 billion+. Growth rate of 20%+ year over year. That’s what investors want to hear. That’s what accelerators teach. That’s what every startup book recommends.
But there’s a math problem with big markets: big markets attract big teams. Big teams have big budgets. Big budgets mean they can outspend you on acquisition, out-hire you on engineering, and out-market you on brand.
Now flip it. What about a market that’s $10 million? $50 million? Too small for a venture-backed startup with 20 employees and $3 million in annual burn. Way too small for an enterprise team. Nobody writes TechCrunch articles about $10 million markets.
But for a solo founder? A market where one competitor has 60%+ market share and only a handful of other players exist? Where the market grows 15-20% year over year? Where the dominant player hasn’t innovated in years because the market isn’t big enough to justify their R&D budget?
That’s not a bad market. That’s the perfect market.
Solo-founded startups now represent 36.3% of all new companies - up from 23.7% in 2019. And 38% of seven-figure businesses are run by solopreneurs. The reason is simple: AI has collapsed the cost of building. What used to require a team of 10 can now be done by one person with the right tools and workflow. Operating margins for AI-powered solo founders hit 60-80%, compared to 10-20% for traditionally staffed businesses.
This means the “minimum viable market” has shrunk dramatically. Markets that were economically unviable five years ago are now goldmines for solo founders. You don’t need millions of users. You don’t need venture capital. You need a niche where real pain exists, competition is thin, and you can build something genuinely different.
How to Find Your Disruption: A Practical Framework
Theory is great. But what do you actually do on Monday morning? Here are five steps.
Step 1: Stop Asking AI for Ideas. Start Giving It Parameters.
The biggest mistake is treating AI as a creative partner for market selection. It’s not. It’s a research assistant - and a good one - but only if you give it the right constraints.
Don’t ask: “What’s a good SaaS idea?” Ask: “Find me markets where one competitor holds 60%+ market share, there are fewer than 10 significant players globally, and the market has grown 15%+ year over year for the last 3 years.”
Don’t ask: “Is the habit tracking market saturated?” Ask: “What is the CPC for the top 20 keywords in the habit tracking space? What’s the average 30-day retention rate for the top 10 habit tracking apps? How many new habit tracking apps launched in the last 12 months?”
The difference is night and day. The first type of question gets you generic, optimistic answers. The second gets you data you can actually make decisions with.
Step 2: Use Sensor Tower to See What Nobody Else Sees
Most founders do their market research on Product Hunt and Twitter. That’s like trying to understand the ocean by looking at the waves on the surface.
Sensor Tower gives you the submarine view. You can see estimated downloads, revenue, user engagement, and retention by country, category, and platform. You can track how specific apps are performing over time. You can see which markets are growing and which are stagnating.
The key move: look for categories where the top app is making real revenue but hasn’t updated meaningfully in 6-12 months. Where user reviews mention the same complaints over and over. Where the market is growing but the product experience is stuck in 2020.
That’s your opening.
Step 3: Talk to Humans (And Watch Their Eyes)
This is the test from Build that I think about constantly. When you describe your product idea to someone - not another founder, not a tech person, a normal person - watch their reaction.
If they say “oh cool, interesting” and change the subject - you have a vitamin.
If they lean in and start asking questions - “wait, how does that work? Can it do X? What about Y?” - you have a painkiller. That curiosity, that pull toward wanting to understand more - that’s the reaction that predicts product-market fit better than any survey or market analysis.
Don’t skip this step. Don’t rationalize your way past lukewarm reactions. The humans will tell you the truth faster than any data set.
Step 4: Look Where Nobody’s Looking
The AI boom has created a gold rush mentality. Everyone is building AI-powered productivity tools, AI writing assistants, AI analytics dashboards. These are the habit trackers of 2026 - crowded, commoditized, and brutal for newcomers.
Meanwhile, entire industries are barely touched by AI. Think about markets where the users are 40+ years old. Where the existing software looks like it was built in 2012. Where “digital transformation” is still a buzzword, not a reality. Healthcare admin. Construction management. Local government. Small-scale agriculture. Trade services.
These aren’t sexy markets. They’re not going to get you on the front page of Hacker News. But they’re markets with real pain, low competition, and users who will be genuinely amazed by what AI can do - because they’ve never seen it applied to their problems before.
Step 5: Escape the Mediocrity Trap
This is the most dangerous part, and nobody talks about it.
You build your product. You launch. And the results are... mediocre. Not terrible. Not great. You get some users. Some of them stick around. Revenue trickles in. And your brain starts rationalizing.
“I haven’t run ads yet.” “I haven’t built feature X yet.” “People are looking at it - they just haven’t converted.” “I need to give it more time.”
This is the mediocrity trap. And it will eat years of your life if you let it.
Mediocre results are not a sign that you’re close to product-market fit. They’re a sign that you’re probably not. Real product-market fit feels like being pulled forward. Users tell other users. Growth accelerates on its own. People get angry when the product is down.
If you’re three months in and constantly explaining to yourself why the results aren’t better - stop. Go back to Step 1. Rerun your analysis. Find a different market or a different angle.
The courage to kill a mediocre product is worth more than the persistence to keep a mediocre product alive.
The Bottom Line
The best products in history started as jokes. The iPhone was a toy with no keyboard. The Nest thermostat was a “fancy temperature dial.” Airbnb was “who would sleep on a stranger’s couch?”
Competitor laughter isn’t a warning sign. It’s a leading indicator. If everyone in your space immediately understands what you’re building - you’re probably building something evolutionary, not disruptive. And evolutionary products in crowded markets are a death sentence for solo founders.
The opportunity right now is enormous. Billions of people who haven’t used AI for anything meaningful. Hundreds of niches too small for big teams but perfect for one person with the right tools. Markets where the dominant player is asleep at the wheel.
Don’t ask AI for ideas. Give it parameters. Use tools like Sensor Tower to see what others can’t. Talk to humans and watch their eyes. Build where nobody’s looking. And if the results are mediocre - have the courage to walk away and find a better fight.
The market is waiting for products that make people lean in and say “wait - how does that work?”
Go build one.
Inspired by Tony Fadell’s “Build: An Unorthodox Guide to Making Things Worth Making” - one of the best books on product thinking I’ve read this year.