Writing
Why Most AI Startups Look the Same
I analyzed the pattern behind generic AI products and found that sameness usually starts before the landing page.
Most AI startups do not look the same because founders lack taste. They look the same because they start from the same vague promise: save time with AI.
That promise is too broad to create a product. It produces similar landing pages, similar demos, similar pricing, and similar churn.
The sameness loop
The pattern usually looks like this:
- Pick a broad role like sales, support, recruiting, or marketing.
- Add a chat interface or generation workflow.
- Promise speed.
- Use generic productivity language.
- Avoid naming the painful edge cases.
The result is a product that sounds useful but not necessary.
Specificity changes everything
The strongest products tend to name the exact moment of pain. Not “AI for sales,” but “turn messy call notes into CRM updates before the rep forgets context.” Not “AI for support,” but “draft refund replies that follow policy and preserve tone.”
Specificity creates product boundaries. It also creates better distribution because the buyer recognizes themselves faster.
The signal
If a product cannot say what it refuses to do, it probably has not found its shape yet.
AI makes it easy to expand. That is exactly why good positioning matters more. Builders need a sharp first use case before they earn the right to become a platform.