Most AI Startups Will Die With Great Products. Here’s the Real Reason.

I got a call last month from a founder who’d raised $4.2 million for an AI startup. Great product. Clean UI. Genuinely useful technology that solved a real problem in healthcare documentation.

He called me because after eight months of being live, he had 340 users. Not 340,000. Not 34,000. Three hundred and forty.

His investors were getting nervous. His burn rate was $180K a month. And when I asked him what his go-to-market strategy looked like, he pulled up a Notion doc with the word "PLG" at the top and nothing underneath it.

He wasn’t stupid. He wasn’t lazy. He’d built something genuinely good. But he was about to become a statistic — and not because of the product.

The Graveyard Is Full of Great Products

Here’s something the tech world doesn’t want to hear: the AI startup graveyard isn’t filled with companies that built bad products. It’s filled with companies that never figured out how to make someone care.

The numbers are staggering. AI startups raised a record $238 billion in total funding during 2025 — 47% of all venture capital activity on the planet. The San Francisco Bay Area alone captured $122 billion. Money is not the problem.

But the failure rate for AI startups sits at 90%, significantly higher than the ~70% for traditional tech companies. And here’s the part that should terrify every technical founder reading this: 42% of them fail due to insufficient market demand. Not insufficient technology. Not insufficient funding. Insufficient demand.

They built it, and nobody came.

I think about this constantly. Because I work with AI startups every day, and I keep seeing the same pattern. Brilliant engineers who can build anything, who genuinely believe — and are often right — that their product is better than the competition. And they’re slowly dying anyway.

Everyone Can Build Now. That’s the Problem.

There’s a term that’s gone mainstream this year: vibe coding. The idea that you can describe what you want to build in plain English and AI handles the implementation. Non-technical founders are shipping paid products in two to four weeks. 92% of developers use AI coding tools daily. 41% of all code written globally is now AI-generated.

A solo founder named Marc Lou built a product in a single day using AI tools that generated more monthly revenue than his previous three projects combined. He shipped 16 products in two years and hit $50K a month.

This is incredible. It’s also the single biggest threat to every AI startup that thinks their technology is their moat.

Because here’s what vibe coding actually means for the market: the cost of building just dropped to near zero. When anyone can build anything, the thing you built stops being special. The barrier to entry that used to protect technical founders — "we can build this and you can’t" — is evaporating in real time.

Google’s VP of startups said it plainly last week: two types of AI startups are facing extinction — LLM wrappers and AI aggregators. "If you’re really just counting on the back-end model to do all the work and you’re almost white-labeling that model, the industry doesn’t have a lot of patience for that anymore."

The golden age of "raise money, figure it out later" is over. Welcome to the era of "figure it out, then raise money." And "it" isn’t the technology. It’s everything that happens after you build it.

The Trust Collapse Nobody’s Talking About

While founders were heads-down building, something happened to the world they’re trying to sell into. Trust collapsed.

Merriam-Webster named "slop" the 2025 Word of the Year — defined as digital content of low quality produced in quantity by artificial intelligence. A study of 65,000 URLs found that 52% of newly published articles are now AI-generated. YouTube deleted 16 AI slop channels totaling 4.7 billion views. Bandcamp banned AI-generated music entirely.

And the consumer response has been brutal. 97% of consumers say authenticity is a key factor in their decision to support a brand. 48% feel that heavy reliance on AI content reduces authenticity. And here’s the number that keeps me up at night: despite billions spent on AI-powered personalization, the percentage of consumers who say brands "don’t get them" jumped from 25% to 40% in a single year.

Read that again. We have more personalization technology than ever, and people feel less understood.

This is the environment your AI startup is launching into. A market drowning in AI-generated noise, where consumers are actively developing antibodies against anything that feels automated, mass-produced, or inauthentic. Where the word for AI content is literally a synonym for garbage.

And most AI startups’ go-to-market strategy is… more AI content.

The Real Moat

I’ve been thinking about this a lot, and I want to be precise about what I mean because I think this is the most important thing I’ve written.

I’ve talked before about how engineering thinking applies to marketing. About how the best marketing is a system, not a campaign. I still believe that. But I think the game has shifted underneath all of us, and the implications are bigger than most people realize.

In a world where AI can build the product, write the content, generate the ads, and automate the outreach — the only thing it can’t replicate is genuine human understanding of what makes people care.

That’s not a marketing platitude. It’s a structural argument about where value lives in the AI economy.

Think about it like this. There are now four layers to any AI startup:

1. The technology layer — the model, the infrastructure, the product itself.
2. The distribution layer — how people find out about you.
3. The trust layer — why people believe you’re worth their time.
4. The meaning layer — why people actually care.

Most startups pour everything into layer one and hope layers two through four just happen. They don’t. They never have. But in 2024, you could still brute-force distribution with enough funding and a decent growth hack. In 2026, the noise floor is so high and trust is so low that brute force doesn’t work anymore.

The startups that are winning right now — Cursor at $500M ARR, Harvey at $195M — didn’t just build great products. They built movements. They created genuine communities of people who identified with the product. Who felt like the company understood their specific pain at a level no one else did. Who became evangelists not because they were incentivized to, but because the product felt like it was made for them.

That’s not technology. That’s not even traditional marketing. That’s empathy at scale. And it’s the hardest thing in the world to manufacture.

Why I Think About This Differently

I didn’t come to marketing through a marketing degree or a FAANG growth team. I came through building things and breaking them and rebuilding them 30 times until they felt right. I came through studying automotive engineering and realizing that the same systems thinking that makes an engine efficient makes a go-to-market strategy work.

But more than that, I came through being the person nobody was supposed to bet on. An immigrant kid from Egypt who moved to Canada at eight, studied engineering, and somehow ended up building a marketing firm while still in school. I know what it feels like to have something genuinely valuable to offer and have absolutely no idea how to make the world see it.

That’s the same feeling I hear on every call with an AI founder. "Our product is better. Why aren’t people using it?"

Because better doesn’t win. Better that people know about, trust, and feel connected to wins. And the gap between those two things is where most startups go to die.

The Agency Reckoning and What Comes After

This problem is compounded by the fact that the traditional marketing infrastructure is collapsing. Forrester predicts a 15% reduction in agency jobs in 2026. Omnicom just completed a $13 billion acquisition of IPG and immediately announced they’d cut $1.5 billion in costs, primarily through eliminating 4,000 positions. Entire legacy agency networks — FCB, MullenLowe, DDB — are being retired or absorbed.

The marketing agency model that existed for 50 years is dying. And what’s replacing it isn’t "AI agencies." It’s something that doesn’t have a name yet.

Here’s what I think it looks like: small, senior-led teams that combine strategic thinking with actual implementation. Teams that don’t just hand you a strategy deck but build the system alongside you. Teams that understand AI well enough to use it as infrastructure, not as a replacement for thinking.

I’ve written about why I changed Olunix’s model from traditional consulting to something that looks more like embedded systems engineering. That decision feels more right every month. Because what AI startups need isn’t more consultants or more agencies. They need someone who can sit at the intersection of product, market, and human psychology and build a bridge between them.

The Founder-Led Content Revolution

There’s one bright spot in all of this, and it’s worth paying attention to.

Creator content now outperforms brand-created content by 2.7x in controlled tests. 81% of marketers report that creator content outperforms brand assets. And the fastest-growing category isn’t influencer content — it’s founder-led content. Founders explaining tough decisions. Founders sharing real numbers. Founders being honest about what’s working and what isn’t.

The data is telling us something profound: people don’t want to hear from brands. They want to hear from humans.

And for AI startup founders, this is simultaneously the best news and the worst news possible. Best, because you have a massive distribution advantage just by being a real person with a real story building something you actually believe in. Worst, because most technical founders would rather debug a memory leak at 3 AM than post on LinkedIn.

But here’s the thing. The same way I argue that good content wins the trust game, founder-led content isn’t just a marketing tactic. It’s the only reliable way to build the trust layer in a world where everything else feels fake.

When you, the founder, explain why you built what you built, who it’s for, and what problem kept you up at night — that cuts through the noise in a way no AI-generated blog post or automated email sequence ever will. Because it’s real. And in 2026, real is the rarest commodity on the internet.

What I’d Tell Every AI Founder Right Now

I’m going to be direct because I think this matters.

1. Your product is not your moat. It might have been two years ago. It’s not anymore. When the cost of building approaches zero and every week brings a new competitor built by a solo founder with Cursor and a weekend, the technology stops being the differentiator. Your understanding of your customer, your ability to articulate why you exist, and the trust you’ve built with your market — that’s the moat.

2. Stop outsourcing your voice. Every AI founder I talk to wants to hire someone to "do the content." I get it. You’re busy. You’d rather be building. But the content that moves markets doesn’t come from a content agency. It comes from you. Your perspective. Your story. Your conviction. Nobody can outsource that.

3. Build the system before you scale the spend. I’ve seen too many startups go from $0 to $50K/month in ad spend without understanding their unit economics, their conversion path, or their retention mechanics. That’s how startups waste money on marketing. Build the machine first. Understand every step from awareness to activation. Then pour fuel on it.

4. Talk to your users like they’re humans, not personas. The biggest disconnect I see is founders who can describe their ICP in perfect marketing jargon but can’t tell me what their customer was doing the moment before they realized they needed this product. That moment — that specific, human, emotional moment — is where all great marketing starts.

5. Accept that this is your job now. Go-to-market isn’t a department you hire later. It’s a founder responsibility from day one. The best technical founders I’ve worked with are the ones who treated market understanding with the same rigor they applied to their codebase. It’s a system. It can be learned. It can be engineered. But it cannot be ignored.

The World Doesn’t Need More AI Products

I want to end with something that might sound contradictory coming from someone who works with AI startups for a living.

The world doesn’t need more AI products. We have plenty. What the world needs are people who can take genuinely transformative technology and make it mean something to real humans with real problems.

We need builders who understand that the gap between "this works" and "people use this" is not a marketing budget. It’s empathy. It’s storytelling. It’s the deeply human work of understanding what someone else needs and showing them you’re the one who gets it.

$238 billion went into AI last year. Most of it will be wasted. Not because the technology wasn’t good enough, but because the people behind it never learned the hardest skill in business: making someone who doesn’t know you, trust you enough to try.

That’s the work I do. That’s the work I believe in. And I think it’s the most important work in the AI economy right now.

If you’re building something real and you feel like the world hasn’t noticed yet — you’re not alone. And you’re not wrong that it’s hard. It is hard. It’s the hardest part. But it’s also the part that separates the companies that become footnotes from the ones that become forces.

The technology is handled. The funding exists. The only question left is: can you make people care?

I think you can. But not by building louder. By building closer.

- MM