a16z：模型持续升级下 AI 应用如何守住价值
a16z 这篇讲了个扎心现实：模型每次升级都在帮客户替代你。文中 Harvey 和 Notion 买 Decagon 的案例挺实在，做 AI 应用的可以看看。
a16z 的 Tugce Erten 发文分析模型升级对 AI 应用层的影响：模型进步让应用运行成本更低，也让客户更容易用自建方案替代。调研显示 94% 的企业 LLM 买家预计支出会继续增长。文中给出三条规则：比客户更好地运营工作流、让租用上下文比重建更便宜、先证明价值再定价。案例包括 Harvey 在盲测中击败通用 AI 助手和能源公司 Repsol 的自研工具，以及 Notion 放弃自研、采购 Decagon 的 AI 客服智能体。
Every model upgrade makes AI apps cheaper to run, and easier for customers to replace. Still, 94% of enterprise LLM buyers expect their spend to rise. Three rules for winning that spend over the build-it-yourself option: 1. Operate the workflow better than the customer can 2. Make context cheaper to rent than to rebuild 3. Prove the value, then price to capture it Who's doing it: - Legal AI platform Harvey beat a general-purpose AI assistant and energy giant Repsol's own in-house tool in a blind test - Notion considered building its own support AI, then bought Decagon’s AI support agents so its team could stay focused on the core product "Model progress continually improves the customer's alternative. Your advantage must widen faster for the application to keep earning its premium." Full piece from a16z's Tugce Erten: a16z.news/p/how-ai-appli… Tugce Erten @TugceErten2022 x.com/i/article/2117… 🔗 View Quoted Tweet 💬 45 🔄 25 ❤️ 249 👀 28673 📊 70 ⚡
- Notion11-02 17:48原文
