Tagged articles

Reflexion

5 articles · Page 1 of 1

Jul 1, 2026 · Artificial Intelligence

How to Build Sustainable Claude Code Workflows with Loop Engineering: A Complete Guide

This article explains why designing autonomous loops for Claude Code supersedes manual prompting, outlines the three loop forms, compares open‑ and closed‑loop architectures, details the ReAct and Reflexion foundations, and provides a step‑by‑step end‑to‑end example for automating daily issue triage with code snippets, tables, and practical design principles.

AI AgentsClaude CodeGit worktree

0 likes · 21 min read

How to Build Sustainable Claude Code Workflows with Loop Engineering: A Complete Guide

Alibaba Cloud Developer

Nov 18, 2025 · Artificial Intelligence

How ReAct and Reflexion Boost Large Language Models for Complex, Real‑World Tasks

The article explains the limitations of large language models on multi‑step reasoning, real‑time information retrieval, and planning, then introduces the ReAct (Reasoning + Acting) framework and its Reflexion extension, detailing their mechanisms, examples, performance gains, practical applications, and future research directions.

Agentic AILLM reasoningLarge Language Models

0 likes · 16 min read

How ReAct and Reflexion Boost Large Language Models for Complex, Real‑World Tasks

Data Thinking Notes

Oct 12, 2025 · Artificial Intelligence

Mastering AI Agent Planning: Architectures, Strategies, and Real-World Implementations

This article provides a comprehensive guide to AI Agent planning modules, covering their core responsibilities, architectural designs, major planning paradigms such as ReAct, Plan‑and‑Execute, Hierarchical Planning and Reflexion, detailed prompt engineering, execution frameworks, and practical case studies in data analysis and intelligent customer service.

AI planningPrompt EngineeringReAct

0 likes · 25 min read

Mastering AI Agent Planning: Architectures, Strategies, and Real-World Implementations

Qborfy AI

Jul 11, 2025 · Artificial Intelligence

Building a Dynamic Agent Workflow with LangGraph: A Step‑by‑Step Guide

This tutorial walks through creating a full‑featured LLM Agent workflow using LangGraph, covering goal definition, task decomposition, execution nodes, state updates, re‑planning logic, and user feedback, while comparing ReAct and Reflexion approaches and providing complete Python code examples.

Agent WorkflowLLMLangChain

0 likes · 11 min read

Building a Dynamic Agent Workflow with LangGraph: A Step‑by‑Step Guide

Smart Era Software Development

Mar 29, 2025 · Artificial Intelligence

40+ Diagrams Uncover LLM Agents’ Core Components, Multi‑Agent Frameworks, and MCP Stack

This article breaks down the essential building blocks of LLM agents—including environment, sensors, effectors, short‑ and long‑term memory, tools, planning, and reasoning—while illustrating how Model Context Protocol (MCP), Toolformer, ReAct, Reflexion, and popular multi‑agent frameworks such as AutoGen, MetaGPT and CAMEL enable scalable, collaborative AI systems.

LLM AgentsPlanningReAct

0 likes · 11 min read

40+ Diagrams Uncover LLM Agents’ Core Components, Multi‑Agent Frameworks, and MCP Stack