𝐁𝐑𝐄𝐀𝐊𝐈𝐍𝐆: 𝐌𝐨𝐬𝐭 𝐀𝐈 𝐬𝐭𝐚𝐫𝐭𝐮𝐩𝐬 𝐰𝐨𝐧’𝐭 𝐟𝐚𝐢𝐥 𝐛𝐞𝐜𝐚𝐮𝐬𝐞 𝐭𝐡𝐞 𝐭𝐞𝐜𝐡 𝐢𝐬 𝐛𝐚𝐝. They’ll fail because they never had a moat. Let me explain. In my recent conversation with Nick Beim, one point kept resurfacing—quietly, but decisively: General intelligence is becoming cheap. Context is not. That’s the central mistake most founders (and investors) are making. They’re racing to build horizontal AI— models, copilots, wrappers, “smart” features. And wondering why differentiation evaporates. Here’s the paradox: The smarter AI gets, the less valuable intelligence alone becomes. Let that sink in. What actually compounds isn’t the model. It’s where the model lives. In workflows. In regulated environments. Inside messy, human, high-stakes decisions. That’s why vertical AI matters. Not because it’s sexier. But because it’s harder. Horizontal platforms want to win everything. But they can’t: • They don’t own the data • They don’t sit inside the workflow • They don’t have trust or relationships • And they can’t absorb infinite edge cases That friction is the moat. Here’s the reframing most people miss: Moats don’t come from intelligence. They come from context + distribution + trust. An AI that understands your business, your incentives, your constraints will outperform a “smarter” model every time. Practical takeaway for founders and investors: If your AI product can be replicated by a prompt, you don’t have a business. If your advantage disappears when the API price drops, you don’t have leverage. But if your product is embedded in decisions people can’t afford to get wrong? That’s where asymmetry lives. Thank you Patrick Ewers for the kind introduction! We’d like to thank @AlphaSenseInc for sponsoring this episode! #AI #Startups #Investing #Leadership #Founders