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This article introduces the ReAct agent paradigm—combining reasoning and acting—explains its observation‑think‑act loop, showcases a step‑by‑step weather‑and‑clothing example, outlines essential components, provides pseudo‑code for the execution flow, and links to the Lynxe Func‑Agent framework on GitHub.
The AliGo travel platform upgraded its AI assistant by replacing a single‑agent workflow with a modular multi‑agent system, introducing dynamic prompt generation, real‑time reasoning chains, context sharing, observability, and a knowledge base, which dramatically improved accuracy, stability, and user experience.
This article explains how Chaterm's Agent Skills, powered by the Qwen large model, let you package operational expertise into reusable, executable skills that automatically diagnose and fix issues, turning a manual 20‑minute troubleshooting process into a three‑minute AI‑driven workflow.
This article explains the background of Claude Skills, details its modular prompt‑based architecture, shows the required file layout, walks through installing and configuring OpenSkills in Lingma, demonstrates creating a custom code‑review skill, and summarizes the benefits of AI skill modularization.
This article details how a low‑code e‑commerce workflow was migrated to a modular LangGraph architecture, introducing Agent Skills, an A2A protocol, and a Planner node to enable multi‑turn natural‑language scene creation, product matching, and persistent storage while leveraging AI coding tools for rapid development.
This article examines the core challenge of giving large‑language‑model agents many abilities while keeping context size limited, compares three common loading strategies, introduces a progressive‑disclosure skill mechanism with three loading layers, and details its implementation, benefits, limitations, and suitable use cases in AgentScope‑Java.
This article details how a production‑grade prompt system powered by large language models was designed to replace manual A/B experiment inspection, introducing a six‑level priority decision tree, robust data preprocessing, and systematic bad‑case analysis that lifted automation accuracy from 68% to over 80% while providing clear, explainable recommendations.
This guide walks you through quickly integrating Moltbot with Alibaba Cloud RDS AI to build an AI‑driven database operations assistant, covering why the combo matters, required preparations, step‑by‑step skill configuration, credential setup, verification commands, and practical usage scenarios.
This article explains how memory systems—both short‑term session memory and cross‑session long‑term memory—address the context‑window limits, token costs, and personalization challenges of AI agents, detailing core concepts, framework differences, integration architectures, context‑engineering strategies, technical components, challenges, and emerging industry trends.
This article walks through integrating an AI‑powered Agent into an internal BFF platform using LangGraph, detailing the architectural choices, state‑graph implementation, prompt engineering, knowledge‑base construction, tool integration, conversation handling, and context compression techniques to enable reliable script generation, execution, and validation.
