Nikita Bier says technical moats are mostly over, leaving proprietary data, network effects and a physical component as the only durable ones
Technical moats are mostly over at this point. If you’re building something that is meant to be durable, the only moats now are: • Proprietary data • Network effects • A physical component
Context
A widely followed product builder is arguing that AI has made software itself easy to copy, which changes what founders and investors should treat as defensible.
Nikita Bier is a consumer app builder known for the apps tbh and Gas, which were acquired by Facebook and Discord, and he has led product at X. A moat is a lasting advantage that keeps competitors from taking a company's customers. The argument that AI coding tools erode software moats has been building all year, including in a Forbes column in August.
Deep dive
Early on October 12, Nikita Bier posted that technical moats are mostly over at this point. If you are building something meant to be durable, he wrote, the only moats now are proprietary data, network effects and a physical component.
Bier did not elaborate in the post, which drew more than a million views. His three categories line up with a common argument this year: if coding agents can rebuild most software features quickly, then advantages based on hard engineering shrink, while data others cannot get, products that grow more valuable as more people use them, and businesses tied to hardware, logistics or other physical operations remain hard to copy.
A Forbes column by Boaz Sobrado in August made a similar case, arguing that the only startup moats left in the AI era are data and distribution. Bier's list leaves out distribution and brand, which many investors still count as advantages, and adds a physical component.
The claim is an opinion, not a measured finding. Companies such as frontier model labs and chip designers still compete heavily on technical depth, and it is not clear Bier meant his point to cover them rather than typical software startups.
Bier has long focused on consumer social apps, where network effects decide most winners.
What to expect next
Watch whether founders and venture investors shift toward startups built on unique data, network effects or physical operations, and whether pure software startups find it harder to raise money.
Also watch how incumbent software companies respond as AI coding agents get better, since if Bier is right, more of them will try to defend themselves through data access and ecosystem lock in rather than features.