Скачать или смотреть ReAct Explained: Reasoning + Acting in Language Models-- Method 1

ReAct is one of the most important ideas behind modern AI agents.
This video explains how reasoning and acting work together in LLMs.
A deep, practical guide to ReAct from concept to production.


ReAct (Reasoning + Acting) is a foundational paradigm for building
intelligent agents with large language models.

In this video, I give a deep but practical explanation of ReAct —
how it interleaves reasoning (“Thought”), actions (“Action”),
and observations (“Observation”) in a single model trajectory.

Topics covered:
• What ReAct is and why it matters
• How ReAct differs from Chain-of-Thought and tool-only agents
• The Thought / Action / Observation loop
• Minimal ReAct agent loop
• Common failure modes and mitigations
• Real-world use cases and production considerations

This video is designed as a self-study and reference guide for:
• AI engineers
• Agentic AI builders
• Researchers and advanced practitioners
• Anyone building LLM-based systems with tools

Understanding ReAct is essential before moving to
advanced agent frameworks, planning, or multi-agent systems.