<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ReAct-Agent on MyVar.dev</title><link>https://gibbok.github.io/myvar/tags/react-agent/</link><description>Recent content in ReAct-Agent on MyVar.dev</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Thu, 23 Apr 2026 17:43:18 +0000</lastBuildDate><atom:link href="https://gibbok.github.io/myvar/tags/react-agent/index.xml" rel="self" type="application/rss+xml"/><item><title>ReAct Agents Synergizing Reasoning and Acting in LLM Workflows</title><link>https://gibbok.github.io/myvar/ai-agents/react-agents-synergizing-reasoning-and-acting-in-llm-workflows/</link><pubDate>Thu, 23 Apr 2026 17:43:18 +0000</pubDate><guid>https://gibbok.github.io/myvar/ai-agents/react-agents-synergizing-reasoning-and-acting-in-llm-workflows/</guid><description>&lt;h2 id="react-agents-synergizing-reasoning-and-acting-in-llm-workflows"&gt;ReAct Agents: Synergizing Reasoning and Acting in LLM Workflows&lt;/h2&gt;
&lt;h3 id="overview"&gt;Overview&lt;/h3&gt;
&lt;p&gt;A &lt;strong&gt;ReAct agent&lt;/strong&gt; is an AI agent employing the &amp;ldquo;reasoning and acting&amp;rdquo; (ReAct) framework to combine chain of thought (CoT) reasoning with external tool use. This framework enhances large language models (LLMs) to handle complex tasks and decision-making in agentic workflows. Introduced by Yao et al. in 2023, ReAct represents a significant advancement in generative AI, enabling LLMs to move beyond mere conversational capabilities towards robust problem-solving.&lt;/p&gt;</description></item></channel></rss>