Ng解释了为什么软件工程基础对AI工程必不可少，以及五大关键能力需要人工指导。
Andrew Ng指出，开发者常因缺乏软件工程基础知识而直接部署AI应用。他强调全栈开发、数据生命周期管理、系统架构设计、安全可靠性和生产运营五大技术能力需要人工指导。这些基础能力对构建高质量AI应用至关重要。
Everyone has done it: You build a new application with coding agents and love the toy version so muc...
Everyone has done it: You build a new application with coding agents and love the toy version so much that you wind up deploying it without first evaluating trade-offs like latency, uptime, and compute costs. And we all know vibe coders who do this every day and only discover the production consequences later. When a developer lacks the proper grounding in software engineering fundamentals, they can’t steer an agent to make the structural decisions needed for building great applications. In this week's letter, Andrew Ng outlines why understanding the full software development stack, from data management to user interfaces, remains essential for AI engineering. Here’s Andrew’s list of the key technical capabilities requiring a knowledgeable human’s guidance: 🏗️ Full-Stack Development: Planning out API design, session management, caching strategies, and asynchronous processing. 🗄️ Data Lifecycle Management: Picking data models and storage infrastructure to maintain consistency and clean feeds for downstream AI systems. 📐 System Architecture Design: Choosing everything from the monolith versus microservice dilemma to load balancing. 🔒 Security and Reliability: Building in smart failure-handling policies to ensure graceful degradation, unit and integration testing, and security and testing — early and often. 🚀 Production Operations: Configuring CI/CD pipelines, managing databases, and creating observability tools for understanding workloads. Read Andrew’s full letter to explore how software fundamentals shape effective AI engineering, and how those fundamentals fit into our overall map of AI Engineering Ski hubs.la/Q04vJ_V50 mAJzy 💬 0 🔄 0 ❤️ 0 ⚡