Why 95% of AI Startups Are Doomed
The Brutal Truth MIT Didn’t Sugarcoat
Let’s stop pretending. The latest MIT report didn’t tell us anything new. 95% of AI startups are failing. Not struggling, not pivoting — failing. Burning money, losing users, and drowning in hype they can’t deliver on. And the reason isn’t “bad timing” or “lack of funding.” The reason is far uglier: we don’t understand the machine, and we don’t understand each other.
The False God of Prompts
Everyone is worshipping at the altar of prompt engineering. Influencers sell courses, trainers give workshops, and LinkedIn gurus post books with “100,000 prompts guaranteed to change your life.” It’s a circus.
Here’s the reality: writing long, refined prompts isn’t prompt engineering. It’s noise. Sometimes shorter, simpler prompts give better results because the machine doesn’t get lost in your poetry. Models don’t “understand” prompts. They don’t care about your adjectives. They predict text. That’s it.
A real prompt engineer doesn’t write magic spells. He studies the model. He learns its quirks. He adapts his language to its behavior. ChatGPT, Claude, Gemini, MidJourney — each speaks with a different accent. If you don’t listen, you don’t get results.
The Token Scam Nobody Talks About
You think you’re clever writing 4,000-token masterpieces? All you’re doing is burning money. Tokens are the hidden tax of AI. Every word you type, every instruction you add — it all costs.
Startups hide this truth. They layer their own hidden prompts on top of yours. So what looks like a simple request can balloon into thousands of tokens. Costs spiral, scalability collapses, and users get fed up.
This isn’t innovation. It’s incompetence dressed up as progress.
The Blind Race of Builders and Users
Here’s the ugliest part: both sides are blind.
- Users think every tool works like ChatGPT. They expect Gemini, Claude, or some random SaaS wrapper to act the same. When it doesn’t, they quit.
- Builders think users already understand models and tokens. They assume people will magically “get it.” They don’t.
So the whole industry is running in circles. Startups chasing hype, users chasing illusions. Nobody stopping to ask: do we even know how this machine works?
Influencers and Fake Masters
Look at Facebook. A guy posts: “Send me your photo, I’ll make you a custom artwork for cheap.” Behind the scenes? He’s using Nano or MidJourney with a generic template.
In the comments, some “prompt guru” drops a long cinematic prompt — fire on one side, water on the other. Sounds impressive, right?
But upload a 50 year old’s photo and you’ll still get a wet-haired superhero. Because the prompt wasn’t about him. It was about the guru showing off. This is the scam. Influencers acting like masters, trainers pumping out shortcuts, startups building wrappers. Everyone pretending. Nobody teaching.
Why ChatGPT Won (And Gemini Didn’t)
Let’s be blunt: ChatGPT isn’t better than every other model. But OpenAI played the game right. They gave people a frictionless experience. A chatbox. A personality. Something that felt human. It went viral because it was relatable, not because it was technically perfect.
Gemini? Overcomplicated. Claude? Safe but soulless. MidJourney? Brilliant, but buried in Discord. OpenAI built a movement. The rest built tools. That’s why ChatGPT owns the mindshare.
The Rare Example: Make.com
Now look at Make.com. Why do they thrive where others die? Not because their flows are magical. Not because their interface is prettier than Zapier’s. They thrive because they educate. They built an academy, a library, a culture. They don’t throw users into the deep end. They teach them how to swim.
That’s the difference. That’s why they grow while AI startups burn. They understand that tools without literacy are useless.
The Brutal Bottom Line
- AI startups fail because they don’t educate.
- Users fail because they don’t learn.
- Influencers cash out while everyone else drowns.
We’ve mistaken prompts for mastery. We’ve mistaken wrappers for innovation. We’ve mistaken hype for progress. And until we fix that, 95% of projects will keep dying.
The survivors won’t be the ones with the shiniest demos or the longest prompts. They’ll be the ones who build literacy, who teach tokens, who guide users. The ones who stop the blind race and start building clarity.
So let’s be clear: If you’re launching an AI startup without educating your users, without teaching them how to think with the machine, you’re already dead. MIT didn’t need to say it. We all knew it. We just didn’t have the guts to face it.