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Network Intelligence Research Center (NIRC)
Network Intelligence Research Center (NIRC)
Nov 7, 2025 · Artificial Intelligence

Introducing LangGraph: A Low‑Level Framework for Building Stateful AI Agents

This article explains why modern LLM‑based applications need agent capabilities, introduces LangGraph’s core features such as stateful execution, graph‑based orchestration, tool integration, human‑in‑the‑loop and multi‑agent support, and provides a step‑by‑step Python example that builds a simple chat‑bot agent.

Human-in-the-LoopLLM agentsLangGraph
0 likes · 11 min read
Introducing LangGraph: A Low‑Level Framework for Building Stateful AI Agents
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Nov 3, 2025 · Artificial Intelligence

How AI Agents Are Revolutionizing Technology: The New Engine of Innovation

This article explores the rise of AI agents—from their definition as intelligent digital assistants powered by large language models to their evolution through planning, memory, and tool use—highlighting real‑world applications, core technical mechanisms, code implementations, and future trends such as autonomy, multimodal fusion, standardization, and safety considerations.

AI agentLarge Language ModelMultimodal
0 likes · 24 min read
How AI Agents Are Revolutionizing Technology: The New Engine of Innovation
Goodme Frontend Team
Goodme Frontend Team
Nov 3, 2025 · Artificial Intelligence

Unlock AI Power with Model Context Protocol (MCP): Build LLM‑Enabled Servers in Minutes

This article introduces the Model Context Protocol (MCP) and Large Language Models (LLM), explains their core concepts, transmission mechanisms, lifecycle, and essential modules, and provides step‑by‑step code examples for creating an MCP server, adding tools, resources, prompts, and debugging workflows to accelerate AI‑driven development.

AILLMMCP
0 likes · 15 min read
Unlock AI Power with Model Context Protocol (MCP): Build LLM‑Enabled Servers in Minutes
Practical DevOps Architecture
Practical DevOps Architecture
Oct 14, 2025 · Artificial Intelligence

Master AI Agents: From Basics to Advanced Multi-Model Development

This comprehensive AI agent development course covers 18 chapters, ranging from fundamental concepts and architecture to large‑model integration, tool and browser control, memory, RAG self‑learning, sandboxing, database manipulation, multi‑agent architectures, code assistance, and a real‑world frontend automation project, complete with source code and documentation.

AI AgentsLangChainRAG
0 likes · 3 min read
Master AI Agents: From Basics to Advanced Multi-Model Development
DataFunSummit
DataFunSummit
Oct 7, 2025 · Artificial Intelligence

Deep Thinking in Large Language Models: Overcoming Domain Challenges

This presentation explores how large language models can transcend their general knowledge limits by developing domain‑specific deep thinking abilities, addressing challenges such as complex instruction execution, expert reasoning gaps, and tool integration, and proposes reinforcement‑learning‑driven frameworks, structured thinking pipelines, and tool‑calling mechanisms to achieve rational intelligence.

deep reasoningdomain adaptationreinforcement learning
0 likes · 27 min read
Deep Thinking in Large Language Models: Overcoming Domain Challenges
AI Cyberspace
AI Cyberspace
Oct 4, 2025 · Artificial Intelligence

Exploring OpenManus: A Deep Dive into an Open‑Source AI Agent Framework

This article provides a comprehensive overview of OpenManus, an open‑source, general‑purpose AI agent framework, covering its installation, configuration, core architecture—including BaseAgent, ReActAgent, ToolCallAgent, and Manus—its extensive tool collection, execution logs, and detailed code analysis for developers and AI researchers.

AI agentOpenManusPython
0 likes · 74 min read
Exploring OpenManus: A Deep Dive into an Open‑Source AI Agent Framework
BirdNest Tech Talk
BirdNest Tech Talk
Oct 2, 2025 · Artificial Intelligence

How Function Calling Empowers LLMs: A Step‑by‑Step LangChain Guide

This article explains how function (tool) calling lets large language models like GPT or Gemini invoke external APIs, walks through defining tools with LangChain, and demonstrates a complete Python example that fetches real‑time weather data and returns a natural‑language answer.

AI AgentsFunction CallingLLM
0 likes · 9 min read
How Function Calling Empowers LLMs: A Step‑by‑Step LangChain Guide
phodal
phodal
Sep 29, 2025 · Artificial Intelligence

How AutoDev Leverages Google’s A2A Protocol for Cross‑Agent Collaboration

This article explains how AutoDev adds support for Google’s Agent‑to‑Agent (A2A) protocol, detailing its architecture, integration with the Model Context Protocol (MCP), configuration steps, debugging tools, and the benefits of a modular, open‑source AI programming ecosystem.

A2AAI AgentsAgent-to-Agent
0 likes · 6 min read
How AutoDev Leverages Google’s A2A Protocol for Cross‑Agent Collaboration
Data Thinking Notes
Data Thinking Notes
Sep 14, 2025 · Artificial Intelligence

How to Build a Robust Tool Integration Module for AI Agents

This article explains the architecture, core components, and step‑by‑step implementation of a tool usage module that enables AI agents to standardize, select, execute, and transform external tools, illustrated with a sales data analysis case and detailed code snippets.

AI agentLLMMetadata Management
0 likes · 9 min read
How to Build a Robust Tool Integration Module for AI Agents
JD Tech
JD Tech
Sep 3, 2025 · Artificial Intelligence

Launch a Multi‑Agent AI System in 20 Lines with OxyGent

This guide shows how to quickly build, configure, and deploy modular AI agents using the OxyGent framework—covering environment setup, minimal code initialization, tool integration, multi‑agent orchestration, and advanced deployment techniques—all illustrated with concise examples and screenshots.

AI AgentsDeploymentOxyGent
0 likes · 4 min read
Launch a Multi‑Agent AI System in 20 Lines with OxyGent
DaTaobao Tech
DaTaobao Tech
Sep 1, 2025 · Artificial Intelligence

Boost Business Automation with AI Agents and MCP: Real-World Insights

This article explores how integrating AI agents with the Model Context Protocol (MCP) and tools like Playwright can automate reporting and batch task creation, detailing practical implementations, challenges, performance comparisons with traditional solutions, and best practices for combining AI and engineering to achieve efficient, reliable business workflows.

AI agentMCPautomation
0 likes · 19 min read
Boost Business Automation with AI Agents and MCP: Real-World Insights
JD Tech Talk
JD Tech Talk
Aug 25, 2025 · Artificial Intelligence

Kickstart Multi‑Agent Collaboration with OxyGent: A 20‑Line Setup Guide

This guide introduces the open‑source OxyGent multi‑agent framework, walks through a quick 20‑line installation, demonstrates environment configuration, tool integration, visualization, and advanced features such as RAG, Reflexion, and distributed deployment for AI applications.

AIFrameworkOxyGent
0 likes · 4 min read
Kickstart Multi‑Agent Collaboration with OxyGent: A 20‑Line Setup Guide
JD Cloud Developers
JD Cloud Developers
Aug 25, 2025 · Artificial Intelligence

Kickstart Multi-Agent Collaboration with OxyGent: 20‑Line Setup Guide

This guide introduces the open‑source OxyGent multi‑agent framework, provides step‑by‑step installation, a 20‑line hello‑world example, tool integration via SSE, MCP and FunctionHub, deployment features like data persistence and distributed setup, and outlines advanced use cases such as multimodal agents and plan‑and‑solve paradigms.

AI FrameworkDeploymentOxyGent
0 likes · 5 min read
Kickstart Multi-Agent Collaboration with OxyGent: 20‑Line Setup Guide
Fun with Large Models
Fun with Large Models
Jul 30, 2025 · Artificial Intelligence

LangChain Tool Integration: Step‑by‑Step Guide to Built‑in and Custom Functions

This article walks through how to integrate LangChain's built‑in tools and user‑defined functions into AI agents, covering environment setup, installing dependencies, using the Python code interpreter tool, binding tools to a model, parsing tool calls with JsonOutputKeyToolsParser, and demonstrating both a data‑analysis example and a weather‑lookup function.

AI AgentsFunction CallingLangChain
0 likes · 13 min read
LangChain Tool Integration: Step‑by‑Step Guide to Built‑in and Custom Functions
DaTaobao Tech
DaTaobao Tech
Jul 18, 2025 · Artificial Intelligence

Build a Minimal Java ReAct Agent in 200 Lines: A Hands‑On Tutorial

This tutorial walks you through constructing a lightweight ReAct agent using Java, explaining the Thought‑Action‑Observation loop, providing a 200‑line code example, and demonstrating a real‑world approval workflow with prompts, tool definitions, and step‑by‑step interaction logs.

AgentJavaLLM
0 likes · 21 min read
Build a Minimal Java ReAct Agent in 200 Lines: A Hands‑On Tutorial
Sanyou's Java Diary
Sanyou's Java Diary
Jul 3, 2025 · Artificial Intelligence

How MCP Standardizes AI Tool Calls with JSON‑RPC and Spring AI

This article explains the MCP framework that standardizes AI tool invocation using JSON‑RPC, outlines its client‑server architecture, details communication methods such as STDIO, SSE and streamable HTTP, and provides a Spring AI demo showing tool registration, discovery, and execution.

AIFunction CallingJSON-RPC
0 likes · 14 min read
How MCP Standardizes AI Tool Calls with JSON‑RPC and Spring AI
大转转FE
大转转FE
Jul 1, 2025 · Artificial Intelligence

Boost AI Development Efficiency: Integrating MCP with Cursor

This article explains the Model Context Protocol (MCP), compares it with traditional function calling, and provides a step‑by‑step guide for integrating MCP into the Cursor editor, including token generation, configuration, server setup, and practical examples that dramatically improve AI‑assisted development productivity.

AI developmentCursorMCP
0 likes · 14 min read
Boost AI Development Efficiency: Integrating MCP with Cursor
AI Large Model Application Practice
AI Large Model Application Practice
Jun 23, 2025 · Databases

How Google’s MCP Toolbox Simplifies Enterprise Database Access for LLM Agents

This guide explains Google’s open‑source MCP Toolbox for Databases, covering its core concepts, installation, configuration, two usage modes (native SDK and MCP), example LangGraph agent integration, security features, observability, and practical code snippets for building reliable LLM‑driven database tools.

LLM agentsMCP ToolboxObservability
0 likes · 11 min read
How Google’s MCP Toolbox Simplifies Enterprise Database Access for LLM Agents
Architecture & Thinking
Architecture & Thinking
Jun 23, 2025 · Artificial Intelligence

Building AI Assistants with Eino: A Go Framework for Large‑Model Applications

This article introduces Eino, an open‑source Golang framework for large‑model AI applications, explains its core capabilities, walks through creating a simple AI assistant with message templates and chat model integration, and demonstrates how to extend the system with tools and a modular architecture for future expansion.

AI assistantEinoFramework
0 likes · 17 min read
Building AI Assistants with Eino: A Go Framework for Large‑Model Applications
Tech Freedom Circle
Tech Freedom Circle
Jun 21, 2025 · Artificial Intelligence

How MCP + LLM + Agent Architecture Becomes the AI Agent’s Neural Hub and New Infrastructure

The article explains the Model Context Protocol (MCP) as a zero‑code bridge that lets large language models seamlessly access databases, external APIs, and execute code, detailing its benefits for developers and everyday users, its core components, step‑by‑step workflow, real‑world examples, and how it outperforms traditional APIs in modern AI agent systems.

AI agentLLMMCP
0 likes · 37 min read
How MCP + LLM + Agent Architecture Becomes the AI Agent’s Neural Hub and New Infrastructure
Instant Consumer Technology Team
Instant Consumer Technology Team
Jun 19, 2025 · Artificial Intelligence

Exploring II-Agent: An Open‑Source AI Agent Framework for Multi‑Domain Automation

II-Agent is an open‑source, multi‑domain AI agent framework that leverages powerful large language models, a rich toolset, planning‑and‑reflection mechanisms, and advanced context management to enable autonomous task execution, real‑time interaction, and seamless integration across development, data analysis, and enterprise workflows.

AI agentContext ManagementLarge Language Model
0 likes · 21 min read
Exploring II-Agent: An Open‑Source AI Agent Framework for Multi‑Domain Automation
Alibaba Cloud Developer
Alibaba Cloud Developer
Jun 11, 2025 · Artificial Intelligence

From Chat to Autonomous Agents: Architecture, ReAct, Prompt Engineering

This article chronicles the evolution from simple chat interactions to sophisticated autonomous agents, detailing stages of LLM development, ReAct reasoning, memory management, tool integration, and practical implementation using the browser-use project, while offering prompt design insights and future directions for AI agents.

AI agentLLMMCP
0 likes · 30 min read
From Chat to Autonomous Agents: Architecture, ReAct, Prompt Engineering
Data Thinking Notes
Data Thinking Notes
Jun 10, 2025 · Artificial Intelligence

Unlocking AI Agents: Architecture, Tools, and Real‑World Applications

This article provides a comprehensive overview of generative AI agents, detailing their core components—model, tools, and orchestration layer—explaining cognitive architectures, tool types, learning strategies, and practical development with LangChain and Vertex AI, while highlighting future prospects and challenges.

AI agentLangChainVertex AI
0 likes · 24 min read
Unlocking AI Agents: Architecture, Tools, and Real‑World Applications
DaTaobao Tech
DaTaobao Tech
Jun 6, 2025 · Artificial Intelligence

Redefining Business Core Assets in the LLM Era: Agent Evolution & Collaboration

This article examines how the rise of large language models reshapes core business assets, defines agents and tools, explores multi‑agent collaboration patterns, task allocation and conflict resolution mechanisms, and evaluates the MCP protocol and engineering requirements for building scalable, flexible agent platforms.

Agent ArchitectureLLMMCP protocol
0 likes · 9 min read
Redefining Business Core Assets in the LLM Era: Agent Evolution & Collaboration
Sohu Tech Products
Sohu Tech Products
May 21, 2025 · Artificial Intelligence

Beyond LLM Limits: Function Calling, MCP, and A2A Compared

The article examines the inherent knowledge cutoff of large language models, introduces function calling, Model Context Protocol (MCP), and Agent‑to‑Agent (A2A) as solutions for real‑time data access, compares their architectures, communication patterns, and use cases, and discusses their respective strengths and drawbacks.

A2AAI protocolsFunction Calling
0 likes · 17 min read
Beyond LLM Limits: Function Calling, MCP, and A2A Compared
DevOps
DevOps
May 13, 2025 · Artificial Intelligence

The Rise of AI Agents: Current Trends, Core Capabilities, and Future Outlook

This article surveys the rapid emergence of AI agents, outlining their projected 2025 breakthrough, market momentum, key frameworks such as Manus and MCP, the four core abilities of perception, planning, tool use, and memory, and the evolving landscape of multimodal and autonomous AI systems.

AI AgentsArtificial IntelligenceMemory
0 likes · 11 min read
The Rise of AI Agents: Current Trends, Core Capabilities, and Future Outlook
Sohu Tech Products
Sohu Tech Products
Apr 29, 2025 · Industry Insights

Why Claude + MCP Is Outpacing Traditional IDEs Like Cursor and Windsurf

The article analyzes how Claude combined with custom MCPs such as ClaudeCommander dramatically reduces the popularity of traditional IDEs by offering automatic codebase exploration, multi‑step task planning, and long‑running automation like video compression, while providing step‑by‑step installation and usage guidance.

AI automationClaudeIDE comparison
0 likes · 9 min read
Why Claude + MCP Is Outpacing Traditional IDEs Like Cursor and Windsurf
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 28, 2025 · Artificial Intelligence

How to Build an AI‑Powered MCP Server to Control a Snake Game

This guide explains how to set up a Model Context Protocol (MCP) server, define its resources, tools, and prompt templates, implement both manual and WebSocket versions of a Snake game client, create MCP clients in TypeScript and Python, debug with the inspector, and integrate the server with AI agents for autonomous gameplay.

AIMCPServer
0 likes · 45 min read
How to Build an AI‑Powered MCP Server to Control a Snake Game
Data Thinking Notes
Data Thinking Notes
Apr 27, 2025 · Artificial Intelligence

Step‑by‑Step MCP Demo: Build Server and Claude/DeepSeek Clients

This guide walks developers through creating a complete MCP application, covering the workflow, server setup with Python, debugging tools, and client implementation using both Claude and DeepSeek models, complete with code snippets, environment configuration, and testing procedures to demonstrate end‑to‑end LLM tool integration.

ClaudeDeepSeekLLM
0 likes · 10 min read
Step‑by‑Step MCP Demo: Build Server and Claude/DeepSeek Clients
Alibaba Cloud Developer
Alibaba Cloud Developer
Apr 25, 2025 · Artificial Intelligence

Unlocking AI Agents: Theory, Design Patterns, and Hands‑On Experiments

This article combines theoretical analysis and practical case studies to systematically explore the core components, design patterns, and future directions of AI agents, detailing the implementation of OpenManus, custom memory and planning modules, experimental evaluations, and insights for improving agent reliability and scalability.

AI agentLLMMemory
0 likes · 31 min read
Unlocking AI Agents: Theory, Design Patterns, and Hands‑On Experiments
phodal
phodal
Apr 14, 2025 · Operations

How to Debug and Test MCP Services with AutoDev MCP Debugger

This guide explains how to install AutoDev 2.0.8, configure .mcp.json files, and use the AutoDev MCP Debugger to test, debug, and execute MCP services and tools, including mock data generation, manual JSON input, and multi‑tool integration with model‑driven prompts.

AutoDevMCPdebugger
0 likes · 4 min read
How to Debug and Test MCP Services with AutoDev MCP Debugger
DevOps
DevOps
Apr 8, 2025 · Artificial Intelligence

Challenges and Opportunities in the Model Context Protocol (MCP)

The article examines the Model Context Protocol (MCP), highlighting its unnecessary complexity, security vulnerabilities across creation, runtime, and update phases, challenges in tool management, persistent connections, and the need for standardized gateways and server hosting solutions, while referencing recent research and roadmap proposals.

AIModel Context ProtocolServer Hosting
0 likes · 10 min read
Challenges and Opportunities in the Model Context Protocol (MCP)
Sohu Tech Products
Sohu Tech Products
Mar 26, 2025 · Artificial Intelligence

How OpenAI Agents SDK Stacks Up Against SmolAgents: A Deep Dive

This article examines OpenAI Agents SDK’s design principles, core concepts, and practical code examples, then compares its functionality, tool integration, handoff mechanisms, guardrails, and tracing features with the competing SmolAgents framework, highlighting strengths, weaknesses, and suitable use cases for each.

AI Agent FrameworkOpenAI Agents SDKSmolagents
0 likes · 13 min read
How OpenAI Agents SDK Stacks Up Against SmolAgents: A Deep Dive
DeWu Technology
DeWu Technology
Mar 24, 2025 · Artificial Intelligence

Understanding Multi‑Agent AI Systems: ReAct Architecture, MCP Protocol, and OpenManus Implementation

Understanding multi‑agent AI systems, this article explains how ReAct’s tightly coupled reasoning‑action loop, the Model Context Protocol, and the open‑source OpenManus implementation enable autonomous task planning, tool invocation, and memory management, contrasting traditional chatbots with delivery‑centered agents while highlighting current limitations and future optimization needs.

AI AgentsMCPOpenManus
0 likes · 24 min read
Understanding Multi‑Agent AI Systems: ReAct Architecture, MCP Protocol, and OpenManus Implementation
Architect
Architect
Mar 21, 2025 · Industry Insights

Can Model Context Protocol (MCP) Transform AI Agent Tooling?

The article examines Model Context Protocol (MCP), an emerging open standard that lets AI agents interact with external tools and services, outlines current use cases such as IDE‑centric workflows and consumer‑focused clients, and discusses technical challenges and future directions for widespread adoption.

AI AgentsAgent-native architectureMCP
0 likes · 18 min read
Can Model Context Protocol (MCP) Transform AI Agent Tooling?
Architect
Architect
Mar 18, 2025 · Artificial Intelligence

2025 AI Agent Technology Stack: Layers, Core Functions, and Future Directions

The article outlines the 2025 AI Agent technology stack, detailing its five layered architecture—model serving, storage & memory, tooling, framework orchestration, and deployment—while discussing current trends, challenges, and future directions such as tool ecosystem expansion, self‑evolution, and edge‑cloud hybrid deployments.

AI agentDeploymentObservability
0 likes · 12 min read
2025 AI Agent Technology Stack: Layers, Core Functions, and Future Directions
Alibaba Cloud Big Data AI Platform
Alibaba Cloud Big Data AI Platform
Mar 13, 2025 · Artificial Intelligence

From Chain‑of‑Thought to Self‑Evolving Agents: Lessons from AI Agent Engineering

This article traces the evolution of large‑model agents from a simple chain‑of‑thought design through tool and agent instantiation, structured PEER patterns, and self‑evolving architectures, highlighting practical challenges, middleware solutions, and open‑source resources for building robust AI agents.

AI AgentsAgent Architecturelarge language models
0 likes · 16 min read
From Chain‑of‑Thought to Self‑Evolving Agents: Lessons from AI Agent Engineering
Architect
Architect
Mar 11, 2025 · Artificial Intelligence

OpenManus: Design, Architecture, and Future Directions of a Multi‑Agent System

OpenManus is an open‑source, plug‑in‑friendly multi‑agent framework that combines planning, tool‑driven ReAct agents, dynamic task allocation, and memory management, detailing its design principles, code structure, workflow, technical components, and future research directions within the AI agent ecosystem.

AI PlanningAgent ArchitectureOpenManus
0 likes · 18 min read
OpenManus: Design, Architecture, and Future Directions of a Multi‑Agent System
Architect
Architect
Mar 6, 2025 · Artificial Intelligence

Analysis of the Manus Multi‑Agent AI System Architecture and Workflow

Manus is a general‑purpose AI agent that bridges thought and action through a multi‑agent architecture comprising planning, memory, and tool‑use modules, enabling autonomous task decomposition, execution, and result delivery across diverse scenarios such as travel planning, financial analysis, and education support.

AI agentAutonomous PlanningMemory Management
0 likes · 15 min read
Analysis of the Manus Multi‑Agent AI System Architecture and Workflow
Infra Learning Club
Infra Learning Club
Feb 7, 2025 · Artificial Intelligence

Understanding LLM Agents: Architecture, Capabilities, and Key Challenges

This article explains what LLM agents are, their core components—brain, memory, planning, and tool use—illustrates how they handle complex queries through task decomposition, surveys notable frameworks, and discusses key challenges such as limited context, long‑term planning difficulties, output inconsistency, and prompt dependence.

AI ArchitectureLLM agentsMemory
0 likes · 15 min read
Understanding LLM Agents: Architecture, Capabilities, and Key Challenges
Alimama Tech
Alimama Tech
Dec 11, 2024 · Artificial Intelligence

Engineering Architecture of Alibaba's AI Digital Employee "AI XiaoWan"

Alibaba’s AI digital employee “AI XiaoWan” uses a native multi‑agent architecture where a Controller Agent interprets intent, plans tasks, and orchestrates execution while an Executable Agent performs domain‑specific operations, communicating via a standardized Agent Communication Protocol, leveraging a centralized Tool Center, a retrieval‑augmented knowledge base, and a data‑flywheel feedback loop to continuously improve and evolve toward memory‑based reasoning and self‑learning.

AIKnowledge BaseLarge Language Model
0 likes · 14 min read
Engineering Architecture of Alibaba's AI Digital Employee "AI XiaoWan"
JavaEdge
JavaEdge
Jun 17, 2024 · Artificial Intelligence

Build Simple LLM Agents with LangChain: A Hands‑On Tutorial

This guide explains what AI agents are, how they combine large language models with planning, memory, and tool use, and provides a step‑by‑step LangChain implementation—including environment setup, tool integration, and a runnable example that solves math and performs web searches.

LLMLangChainPython
0 likes · 6 min read
Build Simple LLM Agents with LangChain: A Hands‑On Tutorial
DaTaobao Tech
DaTaobao Tech
Jun 7, 2024 · Artificial Intelligence

Exploring AI Agent Integration in HandCat App: Architecture, Tool Management, and Implementation

The HandCat team designed an end‑to‑LLM pipeline that separates agent templates, tool protocols, and view layers, enabling LLM‑driven agents with memory, planning, and three tool types—general, selector, and interruptor—to safely manage sessions, handle errors, and balance granularity for performance within a commercial mobile app.

AI agentAgent LabLLM
0 likes · 18 min read
Exploring AI Agent Integration in HandCat App: Architecture, Tool Management, and Implementation
DeWu Technology
DeWu Technology
May 6, 2024 · R&D Management

DeWu Quality Management System Overview

DeWu’s three‑year Quality Management System integrates a risk‑controlled iteration review mechanism, distinct testing and collaboration processes, metric‑driven “Quality Month” methods, and a suite of automation and monitoring tools to standardize, automate, and continuously improve product stability, efficiency, and innovation.

R&D Managementprocess managementquality assurance
0 likes · 13 min read
DeWu Quality Management System Overview
Alibaba Cloud Developer
Alibaba Cloud Developer
Mar 6, 2024 · Artificial Intelligence

Unlocking LangChain: Build Powerful LLM Apps Like LEGO with Real-World Examples

This article explains how LangChain simplifies building and integrating large language model applications by providing modular components such as models, prompts, indexes, tools, memory, chains, and agents, illustrated with practical use cases like travel assistants, face‑recognition troubleshooting, and multi‑agent workflows.

AI AgentsLLMLangChain
0 likes · 44 min read
Unlocking LangChain: Build Powerful LLM Apps Like LEGO with Real-World Examples
Baobao Algorithm Notes
Baobao Algorithm Notes
Feb 4, 2024 · Industry Insights

Balancing Fun, Utility, and Slow Thinking: The Future of AI Agents

In this talk, the speaker examines the dual goals of AI agents—being entertaining and useful—while introducing the concepts of fast and slow thinking, multimodal perception, long‑term memory, retrieval‑augmented generation, and tool integration as essential steps toward building truly valuable digital companions.

AI AgentsFuture AILong-term Memory
0 likes · 18 min read
Balancing Fun, Utility, and Slow Thinking: The Future of AI Agents
NetEase Cloud Music Tech Team
NetEase Cloud Music Tech Team
Dec 12, 2023 · Artificial Intelligence

How LangChain Powers AI Agents: Principles, Debugging, and Real‑World Optimizations

This article explains the concept of AI Agents in the large‑language‑model era, details LangChain's implementation mechanics, shares practical challenges and optimizations encountered by NetEase Cloud Music, and provides step‑by‑step code examples and performance insights for building robust AI Agents.

AI agentDebuggingLLM
0 likes · 20 min read
How LangChain Powers AI Agents: Principles, Debugging, and Real‑World Optimizations
DataFunTalk
DataFunTalk
Nov 2, 2023 · Artificial Intelligence

Enhancing Language and Vision Models with External Knowledge and Tools: OREO‑LM, REVEAL, and AVIS

This article reviews recent research on augmenting language and multimodal models with external knowledge sources and tool‑calling mechanisms, covering three systems—OREO‑LM for knowledge‑graph reasoning, REVEAL for multi‑source visual‑language pretraining, and AVIS for dynamic tool selection—and their experimental results and implications.

MultimodalReasoningknowledge graph
0 likes · 28 min read
Enhancing Language and Vision Models with External Knowledge and Tools: OREO‑LM, REVEAL, and AVIS
DevOps
DevOps
Jun 25, 2023 · Operations

Planning DevOps Infrastructure for Traditional Enterprises: A Comprehensive Capability Blueprint

The article analyzes how traditional enterprises can design a DevOps infrastructure by mapping required capabilities across foundation, development, testing, operations, and project management, illustrating each with representative tools and highlighting the need for a flexible, evolving architecture and a balanced one‑stop DevOps platform.

ITSMci/cdcloud platform
0 likes · 13 min read
Planning DevOps Infrastructure for Traditional Enterprises: A Comprehensive Capability Blueprint
Efficient Ops
Efficient Ops
Mar 22, 2021 · Operations

Boosting Operational Efficiency: Process, Tools, and Engineering Insights

This article explores practical ways to improve operational efficiency by examining process optimization, tool adoption, quality considerations, and engineering practices, highlighting real-world examples like OA, CICD, Spring Cloud, Java, and Kubernetes while emphasizing shared value and cultural factors.

EfficiencyOperationsengineering management
0 likes · 7 min read
Boosting Operational Efficiency: Process, Tools, and Engineering Insights
Efficient Ops
Efficient Ops
Jun 27, 2018 · Operations

How ZhiYun Job Platform Revolutionizes Automated Operations

The article introduces the ZhiYun Job Platform, detailing its evolution from basic tool construction to advanced orchestration and API integration, highlighting how it standardizes, automates, and secures repetitive operational tasks for enterprises across cloud environments.

Cloud ComputingOperationsOrchestration
0 likes · 10 min read
How ZhiYun Job Platform Revolutionizes Automated Operations
Qunar Tech Salon
Qunar Tech Salon
Feb 14, 2017 · R&D Management

Case Study: Qunar Project Management Platform for Reducing Development Costs and Boosting R&D Efficiency

This case study describes how Qunar's R&D support team built an integrated project management platform that unified workflow, data, and toolchains across development, testing, and release stages, dramatically lowering communication overhead, eliminating information inconsistencies, and improving overall engineering productivity.

Project ManagementR&D efficiencyprocess automation
0 likes · 14 min read
Case Study: Qunar Project Management Platform for Reducing Development Costs and Boosting R&D Efficiency
Efficient Ops
Efficient Ops
Nov 16, 2015 · Operations

Mastering IT Change Management: Tools, Processes, and Risk Strategies

This article outlines effective IT operations change management by emphasizing the need for robust tools, standardized forms, precise steps, reusable templates, a change calendar, and clear risk classification, culminating in six simple principles to streamline execution and minimize disruptions.

Risk Assessmentprocess automationtool integration
0 likes · 12 min read
Mastering IT Change Management: Tools, Processes, and Risk Strategies