Introduction
I’ve been thinking a lot about AI lately—not just the models or the breakthroughs, but how it all fits into the real world. Last October, I was at an Italian restaurant in San Francisco when I bumped into one of the cofounders of Cursor, an AI-powered code editor I use daily. We chatted a while, and as we spoke, I couldn’t help but wonder: why do some AI tools stick while others fade away? Cursor had been my go-to for months, but recently, I saw a wave of developers on Twitter raving about Windsurf, a new tool with a slicker interface. It made me realize something unsettling: in the AI space, loyalty is fragile. People chase what’s best, and “best” changes fast.
This isn’t just about code editors. It’s a pattern I’ve seen across the industry. One day, one company feels like the frontrunner in the AI race; the next, a new model drops, and the tide turns. I’ve watched this ebb and flow on platforms like Polymarket, where people bet on future outcomes—it’s like a live snapshot of the hype cycle. But it’s also a reminder that in this world, attention is fleeting. Users jump to the next big thing without hesitation. So, how do you build something that lasts when everything feels so temporary?
The Paradox of Low Switching Costs
Startups face a peculiar challenge. To win users, they need to make it easy to switch from competitors. But that same ease means users can leave just as fast. It’s a paradox: low friction is your hook, but it’s also your Achilles’ heel. I’ve seen this play out with tools I’ve tried—some add AI features that feel more like shiny toys than solutions. You test them, shrug, and move on. The problem isn’t the tech; it’s that it doesn’t solve something you need. In AI, where the noise is deafening, users don’t stick around for “nice”—they want what works.
So, how do you hold on to them when the next flashy tool is always lurking? I’ve been mulling this over, and I keep coming back to the idea of niche. Not trying to be everything, but being the best at one thing. It feels almost rebellious in a world where AI can do so much, but the more specific your focus, the less replaceable you become.
The Allure—and Danger—of Going Broad
There’s this pull in AI to go big, to build something that tackles every problem under the sun. Look at ChatGPT—it can code, write emails, even play trivia. But here’s what I’ve noticed: most of us don’t need a do-it-all tool. We need something that nails one job. I use ChatGPT myself, but mainly for quick coding fixes or rephrasing sentences. It’s like owning a jet plane and only using it to taxi down the street. The power’s there, but without focus, it’s just potential.
This is where I see a disconnect. The industry’s obsessed with bigger, better models, but the real trick is crafting applications that channel that power into something precise. I was talking to a CTO the other day who said it better than I could: too many companies cram AI into their products for the buzz, not the user. They build it because they can, not because it’s needed. And users see through that. They don’t want AI for the sake of AI—they want it to make their lives easier.
The Cost of Chasing Hype
Then there’s the money side of things. So many AI startups are pouring VC cash into cheap services, trying to grab users before the well runs dry. It’s a gamble, and I wonder how long it can last. Acquisition costs are climbing—higher than ever, I’d bet—and yet users still churn. Why? Because when your product’s generic, there’s no glue. People use it until the next thing shines brighter, which in AI is always tomorrow.
But a niche flips that script. Solve a specific problem, and you attract people who need you. They stick around because no one else does it quite like you do. Plus, a smaller market means sharper marketing—less waste, lower costs. It’s not just about a better product; it’s about a better fit.
AI as a Wildfire: Powerful, but Needing Containment
Lately, I’ve been picturing AI models as wildfires—raw, wild, full of energy. ChatGPT’s like that: incredible, but most of us just poke at the edges. We ask it simple stuff, ignoring the vastness of what it could do. That’s not a flaw in the tech—it’s a gap in how we use it. People don’t need a wildfire; they need a campfire. Something manageable, purposeful, close.
This is where I think startups can shine. Find a niche, and you’re not just building a tool—you’re bridging AI’s chaos to human need. You’re taming the flame into something people can sit by. And that, to me, feels like the real win.
A Call to Focus
So where does this leave us? I think the AI revolution isn’t about the tech itself—it’s about what we do with it. It’s about solving real problems, not riding hype waves. It’s about building for tomorrow, not just the next pitch deck. And it’s about knowing that users don’t care about AI—they care about what it gives them.
If you’re in this space, I’d ask yourself: what’s the one thing I can solve better than anyone? Not a dozen things—just one. Because in a world where everything’s shifting, focus might be the only thing that sticks.
Acknowledgements
I want to thank Grok 3 for helping me polish this article.