Concept · 7 episode(s)

ReAct Agent

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Definition

The ReAct agent pattern interleaves reasoning steps and tool-using actions in a single chain — “think, act, observe, think, act, observe” — and was one of the early templates that made LLM agents practical. Most modern agent loops are variations on this idea.

Episodes covering this

  1. 186
    How a Frozen Model Went From 2% to 77% on Physics Puzzles — Without Retraining
    Hierarchical Experimentalist Agents
    Chandra, Vaidyanathan, Dhanuka et al. · University of Massachusetts Amherst·22 min·Jun 30, 2026
  2. 168
    When Turning Experience Into Code Makes Your AI Agent Dumber
    Metis: Bridging Text and Code Memory for Self-Evolving Agents
    Dai, He, Li et al. · The Chinese University of Hong Kong·27 min·Jun 24, 2026
  3. 110
    How an Agent Got 44 Points Better by Mining Its Own Scratch Paper
    Inducing Reasoning Primitives from Agent Traces
    Lei, Yan, Momo et al. · Carnegie Mellon University·27 min·Jun 03, 2026
  4. 083
    Training the Translator: How a Small Communication Model Lets Agent Teams Outperform Themselves
    AgentFugue: Agent Scaling for Long-Horizon Tasks through Collective Reasoning
    Hu, Qian, Wang et al. · GSAI·24 min·May 26, 2026
  5. 047
    When Agent Benchmarks Lie: The Harness Problem in Open-Source AI
    Orchard: An Open-Source Agentic Modeling Framework
    Peng, Yao, Wu et al. · Microsoft Research·28 min·May 15, 2026
  6. 021
    Ten Thousand Examples Beat the Full Industrial Pipeline for Search Agents
    OpenSeeker-v2: Pushing the Limits of Search Agents with Informative and High-Difficulty Trajectories
    Du, Ye, Tang et al. · Shanghai Jiao Tong University·14 min·May 06, 2026
  7. 005
    Why a Debugger Designed for Humans Is the Wrong Tool for an AI Agent
    Empowering Autonomous Debugging Agents with Efficient Dynamic Analysis
    Xiang, Xu, Chu et al. · Southern University of Science and Technology·22 min·May 01, 2026

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