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Andrew Ng reveals why most successful AI agents start with simple linear workflows—not complex autonomous systems—and shares the "Lego brick" approach that's accelerating agent development. In this fireside chat with Harrison Chase, Andrew explains the challenge businesses face in breaking down existing processes into sequential micro-tasks and why he sees more opportunities in linear workflows than complex autonomous systems. He also unveils the two key predictors of AI startup success and why everyone should learn to code in the AI era.
What You'll Learn:
- Why Andrew advocates for 'agentic' systems" or "Andrew's framework for agentic systems.
- How voice applications reduce user friction and why they're massively underrated by developers
- The two critical predictors of AI startup success: speed and deep technical knowledge
- Why MCP (Model Context Protocol) will transform data integration but needs to evolve
- Andrew's perspective on "vibe coding" and why AI coding assistance creates more developers, not fewer
Andrew demonstrates how successful agent builders think like Lego brick assemblers—quickly combining specialized tools (RAG, evals, guardrails, memory systems) rather than building everything from scratch. From linear business workflows to voice stack applications, learn the practical framework that's driving real production deployments.
Featured Products: LangGraph for agent orchestration, LangGraph Platform for production deployment, and LangSmith for observability and evaluation.
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