@joshelman: The new moats are the same as the old moats Every few years, we fall in love with shiny new tech and forget the basic p…
Summary
The article argues that despite the hype around AI, the enduring competitive moats in consumer software are still network effects, marketplaces, and platforms, and AI products must evolve to incorporate multi-user dynamics for long-term retention.
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Cached at: 09/09/26, 01:55 PM
The new moats are the same as the old moats
Every few years, we fall in love with shiny new tech and forget the basic physics of consumer software.
We’re doing it again with AI.
The new moats aren’t new at all. They’re the exact same as the old moats: network effects, marketplaces, and platforms.
Right now, consumer AI is booming. New agents like Instinct, Bot, and Tomo are dropping mind-blowing experiences. The underlying tech is incredible, but almost every product being built today shares the exact same challenge:
They are completely single-player.
Single-player products are 100% tied to value - and in this case mostly agent : model performance.
If a competitor drops an agent tomorrow that books travel faster, tracks habits better, or handles life admin more reliably, everyone can switch overnight because leaving is easy and has nearly zero friction. Especially when it is so easy to onboard with just a new message.
The legendary consumer tech giants didn’t win because their underlying technology stayed marginally better forever.
They won because of structural lock-in:
Social Networks: You don’t abandon WhatsApp for a prettier UI if your friends aren’t there. Marketplaces: Airbnb, Doordash, and Uber hold supply and demand in a tight loop. Platforms: Apple and Android deliver you a complete device so you take advantage of the software on top of it (though this creates opportunities too)
Novelty gets you initial distribution.
Multi-user dynamics give you long-term retention.
If your consumer AI product doesn’t become exponentially more valuable to User A when User B joins, you don’t have a moat, just a temporarily superior feature set.
We are seeing this in the coding agents as people jump from tool to tool based on the best performance.
But… all is not lost. There are huge opportunities here. Agents will get better when more of our friends are on them and can help us coordinate and communicate to do more together. Agents that help us improve and strengthen our habits can get better as we add friends and hold each other accountable.
Data flywheels are great, but social and marketplace flywheels are what actually build enduring tech giants. It’s time to stop building isolated AI tools and start building the platforms where people connect, transact, and coordinate together.
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