About the Instructor
Google Research & Princeton
ReAct was published at ICLR 2023 by Shunyu Yao, Jeffrey Zhao, and colleagues from Google Research and Princeton University. The paper and accompanying resources form the canonical reference for agent reasoning patterns.
First Principles
ReAct = Reasoning + Acting. The agent thinks through the problem, decides what tool to use, sees the result, and revises its plan. This is how humans solve complex problems.
AI Ecosystem Fit
Layer 5 (Applications) — The cognitive architecture for autonomous agents. ReAct is why agents can solve multi-step problems instead of one-shot tasks.
Prerequisites
What Paid Projects This Unlocks
Build reasoning agents: ReAct chains, tool-using agents for research, planning, and complex decision-making.
3 Client Projects You Can Get Paid For
Real businesses have this problem right now. Build it, pitch it, charge for it.
Stack This With → (Unlocks Higher-Paying Projects)
Combine with RAG for knowledge-aware agents
Build multi-step workflows
Deploy autonomous agents for SMBs
Why This Matters
This is the difference between a chatbot and an agent. Agents are 10x more valuable. ReAct is the framework that unlocks them.