Hey Founder, What are you building today? Great post by Itamar Novick of Recursive Ventures on what (not) to build with AI add-on 👇 If you are raising or planning to raise a Series A round, check how G+QUANT can help you with warm #investor introductions and connect you with the right #investors and VC funds. ▶ Please use G+QUANT's website link for inquiries, or send your inquiry to info@gplusquant.com #VentureCapital #VentureFunding #VentureDebt #Fundraising #Innovation #Technology #Entrepreneurship #Investing #Network #Investors #LPs #GPs #FamilyOffice #Markets #Economy #Business #Founders #Startups #StartupFunding #ai #artificialintelligence #unicorn
The week before Thanksgiving, I met with 12 AI startups. All had impressive tech. 11 of them will fail. Here's why... TLDR: Most AI startups are building features, not companies. Here's the pattern that separates winners from losers. The Trap: Every day, another founder shows me their "AI-powered solution." Their eyes light up as they demo their GPT-4 integration. Then I ask one question that makes the room go quiet: "What happens when OpenAI (Meta, or Google) releases this as a feature next month?" The uncomfortable truth: The Feature Fallacy Your entire product can be replicated with a few prompts. That's not a moat. The "AI-Washing" Problem "We use AI" isn't a value proposition. It's table stakes. The Data Desert Without unique training data, you're building on sand. But here's where it gets interesting... Last month, I invested in an AI startup that broke all the "rules." They showed me: - A proprietary data set no one else had - A specific problem that costs companies millions - A solution that gets better with every user The Lesson: The winners aren't building "AI companies." They're building companies that solve massive problems and happen to use AI. Want to know how they're doing it? Stay tuned for next week, when I break down one of my recent AI investments. #VentureCapital #AI #Startups