AI will kill most startups — and that’s a good thing
When anyone can build the product, only authority differentiates the outcome.
Picture an ordinary person working in tech — a designer, developer, or product manager — who stumbles onto a genuinely good idea. Not a moonshot. Not a revolution. Just something that solves a real problem.
In the past, bringing that idea to life required capital, a team, and time. Today, it requires a laptop and a collection of AI tools. With AI filling the gaps, a working prototype can be vibe coded in weeks, if not hours. The product is tested, refined, and launched, and for a brief moment it appears successful.
Then reality intervenes.
Within months, near-identical products emerge, copied and shipped at machine speed. What began as a solo effort quickly becomes a crowded category, and any early differentiation disappears. Soon after, a large technology company notices the pattern. Without meaningful distribution or a loyal audience to defend it, the idea is absorbed into an existing platform as a feature. A few months later, the startup is effectively gone.
This outcome is no longer unusual. It is becoming the norm.
What this reveals is uncomfortable but important. AI does not kill startups. It exposes ideas that never earned credibility. If a product can be imagined, built, and shipped by almost anyone, it can also be copied by almost anyone. That is not a failure of innovation so much as a stress test — one that reveals how thin many ideas were to begin with.
I saw this firsthand early in my career.
My first startup experience was at a publishing company building a new journal and news platform for advanced practitioners in oncology. On paper, it was an extremely narrow niche. But the niche alone was not what made the product work. Plenty of people could have identified the same market and built a similar platform.
What mattered was credibility.
We had a well-established advanced practitioner in oncology serving as editor-in-chief — someone deeply respected in the field, with years of lived experience and professional trust behind their name. That credibility changed everything. It shaped how the content was framed, how the platform was perceived, and whether practitioners were willing to engage with it at all. The product succeeded not because it existed, but because people trusted who it came from.
That distinction is where many modern startups will fail.
AI makes it easy to build products. It does not make it easy to justify them.
What will survive in this new AI environment are products with real moats. And a moat is not clever functionality, a polished interface, or speed to market. It is whatever does not collapse under replication — distribution, trust, proprietary data, embedded workflows, regulatory friction. AI has a way of stripping away the illusion and revealing which products actually possess these advantages.
This dynamic feels brutal, but it is ultimately corrective. AI eliminates products that existed largely because building used to be hard. In doing so, it creates space for work rooted in context, relationships, and accumulated judgment. The bar has not necessarily been raised — it has been clarified.
Some of the most durable moats are not technical at all. They are human. Trust earned over time. Expertise in a narrow, underexplored domain. Lived experience that shapes how a problem is understood. Perspective refined through accountability. Features can be copied. Credibility cannot.
AI excels at reproducing outputs. It struggles to reproduce identity, reputation, and judgment. Products that are extensions of who someone is, rather than just what they have built, are far harder to erase.
So what does a viable strategy actually look like?
It is not building faster, shipping more features, or out-executing competitors. AI has already neutralized those advantages. Competing on speed or efficiency is no longer a strategy when execution itself has been commoditized.
The real shift happens upstream. Founders must stop asking what they can build and start asking what they are uniquely positioned to justify. That justification does not come from novelty. It comes from credibility accumulated long before the product exists. From being embedded in a domain deeply enough that the solution reflects judgment, not just capability.
In practice, this means fewer generic products and more opinionated ones. Products that make tradeoffs. Products shaped by experience rather than tooling. AI can help build them, but it cannot supply the authority behind them.
It also means that trust, reputation, and distribution are no longer problems to solve after launch. They are part of the product itself. If an idea can be detached from its creator and absorbed by a platform without resistance, it was never defensible to begin with.
The startups that survive this era of AI will not look like traditional startups. They will resemble institutions, disciplines, or professions — things with continuity, authority, and accountability. Their advantage will not be speed. It will be standing.
AI is not ending startups. It is forcing them to justify their existence. That correction, however uncomfortable, is overdue.
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AI will kill most startups — and that’s a good thing was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.