03/09/2026
The underlying technology is becoming more powerful while access to that technology is becoming less differentiated.
If multiple companies can build on similar foundation models, improvements at the model layer can quickly compress differentiation at the application layer.
For AI startups, defensibility increasingly comes from what competitors cannot easily reproduce by accessing the same models: proprietary data, workflow ownership, distribution, customer integrations, trust, and accumulated product knowledge.
This also changes how we should think about speed. Shipping quickly is useful, but speed itself is not a moat.
Its value comes from what it allows a company to accumulate before competitors do:
👉usage
👉data
👉distribution
👉integrations
👉customer dependency
The strongest AI businesses may therefore be those where the product becomes progressively more valuable to the customer, and more difficult for a competitor to replace.
We explore these new sources of defensibility and what they mean for AI startups in our latest article 👇
AI makes building software easy, but defending it is harder than ever. Learn how moats are evolving and what it takes to build a lasting AI company. For a long time, building great software was hard. You needed time, capital, and a strong technical team just to get something off the ground. That fri...