讨论了为什么Agentic AI落地难，核心不是技术而是治理和流程变革，做AI架构的值得一看。
Perplexity创始人Arav Srinivas引用订阅者评论，指出Agentic AI在规模化生产中面临两大难题：一是需构建编排/路由、上下文工程、状态管理、多智能体协作、安全合规等新型系统；二是企业治理和文化转型更难，导致目前缺乏大规模成功案例。他强调持久价值在于安全的多模型编排框架（如Perplexity Computer）。
The durable value is in a secure multi-model harness that takes care of orchestration and model rout...
The durable value is in a secure multi-model harness that takes care of orchestration and model routing in a secure complaint manner. Aka Perplexity Computer. Cassandra Unchained @michaeljburry Great comment from a subscriber who commented in our Chat on his direct experience. Agentic AI is pretty difficult to implement at scale in production because (1) a bunch of new types of systems need to be built that have never existed before (orchestration /routing, context engineering, state management, multi-agent collaboration, security / compliance etc), and (2) an agentic enterprise requires completely new ways of thinking as well as new challenges in governance and culture. The second part is actually the much harder part, which is why there hasn’t been a ton of big success stories yet - every company is trying to figure it out. Anyway I don’t think the problem is at the demand layer. What’s happening at the finance layer is interesting and could be problematic. But time will tell. I would hope this is an open forum where people with different perspectives can share knowledge and discuss 🔗 View Quoted Tweet 💬 2 🔄 1 ❤️ 14 👀 1577 📊 3 ⚡