Andrew Ng on the rise of AI agents and agentic reasoning

Why it matters

Andrew Ng — Coursera founder, former chief scientist at Baidu and Google Brain — is AI adoption's most patient evangelist. This Snowflake BUILD 2024 keynote is the canonical version of his 'agentic workflows' thesis: stop debating the definition of an agent and design workflows by degree of autonomy; the four design patterns — reflection, tool use, planning and multi-agent collaboration — often lift performance more than a bigger model would. In 27 minutes he shows why enterprises should start with agentic processes, not model parameters.

Key takeaways

• Stop debating 'what counts as an agent': design along an autonomy spectrum — fixed flows to highly autonomous, each with its place.
• Four design patterns: reflection (self-critique and revise), tool use, planning (step decomposition), multi-agent collaboration.
• Agentic workflows let smaller models beat bigger ones used naively: process design is the new performance lever.
• Non-technical teams benefit too: break repetitive knowledge work into reflective, iterable steps and AI can take it on.
• Adoption advice: pilot on well-defined, fault-tolerant scenarios first; expand autonomy only with data.