You Built a Tool. Where’s the Moat?
In the early stages of any tech shift, it’s easy to obsess over the innovation—faster models, better APIs, smarter predictions. But lately, a pattern’s emerging: most AI tools don’t fail because the tech isn’t good. They fail because no one sticks around. We’ve seen this before. During the NFT boom, countless projects launched with high production value, but when the hype faded, only a few survived. The ones that did—early DAOs, open-source collectives—endured not because of a better roadmap, but because of a committed base that believed in the mission and brought others in.
Some AI projects today feel like they’re heading down the same path. A launch tweet, a few hundred signups and then silence. Unless the product becomes part of something larger—a movement, a shared belief, or even just a space where users feel like contributors—it quietly dies.
Would love to hear from others building in this space:
Is community a distraction, or a pillar for what you’re building?
If you’ve invested in it, what’s worked for you?
Replies
This is happening because AI is a bubble: founders confuse people's attraction to something new with having actual PMF.
Doing a big, impressive launch is good because it allows you to get your first hundreds of users, but very few people do the necessary work afterward to find true PMF: one-on-one sessions with users, tracking metrics daily, rapidly iterating on recurring patterns, and once all that's done, leveraging network effects.
What's currently happening:
- People launch with a fantastic video on social media that gets tens of thousands of views → attracts hundreds of users drawn by the excitement of novelty and AI FOMO → Founders try to add new features instead of listening (and truly listening) to their first users (i.e The Mom Test) and iterating based on feedback → Users become less and less active → Founders think their project is no good anymore → Project flops