AI软件护城河依赖垂直领域数据

AI软件的护城河基本上都是依赖垂直领域数据 靠先发优势积攒优质数据 将数据转化成Agent Loop的优质结果 AI可以很快做一个60分的功能 但如果你希望它交付你80分 就依赖经验数据 这些是需要...

AI软件的护城河基本上都是依赖垂直领域数据 靠先发优势积攒优质数据 将数据转化成Agent Loop的优质结果 AI可以很快做一个60分的功能 但如果你希望它交付你80分 就依赖经验数据 这些是需要时间和世界交互不断获取的 60到80分可能需要几个月 80到90分可能需要半年 90到92分可能需要一两年 如果这个事情更关注最后一公里 那么数据就更值钱 如果这个事情的容错性很高 那么它基本只会剩下分发的壁垒了 所以如果你构建的软件 无法为你带来时间窗口置换回来的数据积累，使AI做的更好 那么你构建的软件就不会有长期壁垒 Josh Elman @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 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. 🔗 View Quoted Tweet 💬 0 🔄 0 ❤️ 1 👀 658 ⚡