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AI Agent

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DataFunSummit
DataFunSummit
Jun 8, 2025 · Artificial Intelligence

Mastering LLM Applications: Practical Agent Design and Implementation Strategies

This comprehensive guide explores the core implementation paths for large language model (LLM) applications, focusing on agent design, workflow orchestration, tool integration, memory management, multi‑agent architectures, and future trends, providing actionable methodologies and real‑world examples for practitioners.

AI AgentAgent DesignLLM
0 likes · 25 min read
Mastering LLM Applications: Practical Agent Design and Implementation Strategies
Youzan Coder
Youzan Coder
Jun 6, 2025 · Artificial Intelligence

How AI Agents Turn Manual Data Retrieval into Fully Automated Insights

This article examines the challenges of manual data extraction in data‑driven enterprises, explains why large language models alone fall short, and details how the Cursor‑Agent framework automates end‑to‑end querying, knowledge‑base integration, and result validation to become a self‑sufficient "data master" for both technical and non‑technical users.

AI AgentCursor-AgentData Automation
0 likes · 26 min read
How AI Agents Turn Manual Data Retrieval into Fully Automated Insights
Tencent Technical Engineering
Tencent Technical Engineering
Jun 5, 2025 · Artificial Intelligence

How AI Agents Turn 0‑Day Vulnerability Hunting into an Automated Production Line

This article explores how a multi‑agent AI system dramatically improves 0‑day vulnerability detection by automating code audit, reducing false positives, and outperforming traditional static analysis tools in large‑scale real‑world benchmarks.

0day vulnerabilityAI Agentautomated security testing
0 likes · 9 min read
How AI Agents Turn 0‑Day Vulnerability Hunting into an Automated Production Line
DataFunTalk
DataFunTalk
Jun 4, 2025 · Artificial Intelligence

Google Gemini Full‑Stack LangGraph Quickstart: Building a Research‑Grade AI Agent

The article introduces Google’s open‑source Gemini‑Fullstack‑LangGraph‑Quickstart project, explains its modern front‑end/back‑end architecture, details a five‑step intelligent research workflow, and outlines development, deployment, and extensibility considerations for creating a self‑contained, research‑oriented AI agent.

AI AgentDockerGemini
0 likes · 7 min read
Google Gemini Full‑Stack LangGraph Quickstart: Building a Research‑Grade AI Agent
Tencent Technical Engineering
Tencent Technical Engineering
May 23, 2025 · Artificial Intelligence

The Evolution, Challenges, and Future Directions of AI Agents

An in‑depth overview traces the development of AI agents from early LLM milestones to modern “class‑Agent” models, examines core components such as memory, tool use, planning and reflection, analyzes current limitations, and outlines emerging solutions like workflows, multi‑agent systems, and model‑as‑product paradigms.

AI AgentAgentic WorkflowFunction Call
0 likes · 40 min read
The Evolution, Challenges, and Future Directions of AI Agents
Tencent Technical Engineering
Tencent Technical Engineering
May 19, 2025 · Artificial Intelligence

RAG, Agents, and Multimodal Large Models: Evolution, Challenges, and Future Trends

This article examines the evolution of large model technologies—including Retrieval‑Augmented Generation, AI agents, and multimodal models—detailing their technical foundations, practical challenges, industry applications, and future development trends, offering a comprehensive perspective for AI practitioners and researchers.

AI AgentRAGknowledge retrieval
0 likes · 14 min read
RAG, Agents, and Multimodal Large Models: Evolution, Challenges, and Future Trends
Tencent Cloud Developer
Tencent Cloud Developer
May 8, 2025 · Artificial Intelligence

Advances and Future of AI Agents: Capabilities, Trends, and Applications

AI agents are rapidly evolving toward a 2025 breakthrough in perception, autonomous planning, tool use and memory, driven by multimodal models, neural‑symbolic reasoning and embodied intelligence, with $27 billion investment forecasts, exemplified by general‑purpose agents like Manus and emerging applications in code generation, research, healthcare, and risk analysis.

AGENT frameworkAI AgentAutonomous Planning
0 likes · 12 min read
Advances and Future of AI Agents: Capabilities, Trends, and Applications
Java Captain
Java Captain
Apr 17, 2025 · Artificial Intelligence

Demonstrating the Full Lifecycle of Model Context Protocol (MCP) with Tool Calls

This article explains how the Model Context Protocol (MCP) enables large language models to retrieve up‑to‑date external information through standardized tool calls, illustrating the complete end‑to‑end workflow with Python code for the MCP server, client, and host, and discussing its advantages for building AI agents.

AI AgentLLMMCP
0 likes · 21 min read
Demonstrating the Full Lifecycle of Model Context Protocol (MCP) with Tool Calls
Tencent Technical Engineering
Tencent Technical Engineering
Apr 11, 2025 · Information Security

Security Analysis of MCP and A2A Protocols for AI Agents

The article examines critical security flaws in Anthropic’s Model Context Protocol (MCP) and Google’s Agent‑to‑Agent (A2A) protocol—such as hidden tool‑poisoning, rug‑pull, and command‑injection attacks that can hijack AI agents and leak data—while proposing hardening measures like authentication, sandboxing, digital signatures, fine‑grained permissions, and robust OAuth‑based consent to safeguard AI‑agent communications.

A2AAI AgentMCP
0 likes · 26 min read
Security Analysis of MCP and A2A Protocols for AI Agents
Nightwalker Tech
Nightwalker Tech
Apr 1, 2025 · Artificial Intelligence

Evaluation of AutoGLM: Features, Architecture, and Practical Test Results

This article reviews AutoGLM, the first "think‑while‑doing" AI agent released by Zhipu AI, detailing its core capabilities, full‑stack architecture, user experience, identified limitations, and the outcomes of three hands‑on tests using both the client application and a Chrome extension.

AI AgentArtificial IntelligenceAutoGLM
0 likes · 4 min read
Evaluation of AutoGLM: Features, Architecture, and Practical Test Results
Architecture & Thinking
Architecture & Thinking
Mar 28, 2025 · Artificial Intelligence

What Is MCP? Comparing Model Context Protocol, Function Calls, and Agents

This article introduces the Model Context Protocol (MCP), explains its core features and open‑source implementations, and then compares MCP with Function Call and AI Agent concepts, highlighting their similarities, differences, and practical use‑case examples.

AI AgentAI integrationFunction Call
0 likes · 10 min read
What Is MCP? Comparing Model Context Protocol, Function Calls, and Agents
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
DevOps
DevOps
Mar 9, 2025 · Artificial Intelligence

A Beginner's Guide to Building Large Language Model Applications: Prompt Engineering, Retrieval‑Augmented Generation, Function Calling, and AI Agents

This article provides a comprehensive introduction to developing large language model (LLM) applications, covering prompt engineering, zero‑ and few‑shot techniques, function calling, retrieval‑augmented generation (RAG) with embedding and vector databases, code assistants, and the MCP protocol for building AI agents, all aimed at non‑AI specialists.

AI AgentFunction CallingLLM
0 likes · 48 min read
A Beginner's Guide to Building Large Language Model Applications: Prompt Engineering, Retrieval‑Augmented Generation, Function Calling, and AI Agents
Architecture and Beyond
Architecture and Beyond
Mar 9, 2025 · Artificial Intelligence

Evolution of AI Interaction Paradigms: From Function Calling to MCP and AI Agents

The article examines the rapid rise of AI agents like Manus and OpenManus, explains the limitations of cloud‑only models, details the Function Calling mechanism and its pros and cons, introduces the Model Context Protocol (MCP) as a more powerful evolution, and finally describes how AI Agents combine planning, dynamic tool use, memory, and autonomous decision‑making to achieve fully closed‑loop intelligent automation.

AI AgentAI AutomationAI Interaction
0 likes · 20 min read
Evolution of AI Interaction Paradigms: From Function Calling to MCP and AI Agents
ZhongAn Tech Team
ZhongAn Tech Team
Mar 8, 2025 · Artificial Intelligence

Weekly AI Rumors Issue 15: Manus AI Agent Launch, GPT‑4.5 Evaluation, and LightThinker Technique

This issue reviews the hype around China’s Manus AI Agent and its invitation‑code controversy, critiques OpenAI’s GPT‑4.5 performance versus DeepSeek, showcases industry solutions using AI agents, and introduces the LightThinker method for dynamically compressing LLM inference chains to boost efficiency.

AI AgentAI MarketGPT-4.5
0 likes · 15 min read
Weekly AI Rumors Issue 15: Manus AI Agent Launch, GPT‑4.5 Evaluation, and LightThinker Technique
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
Tencent Cloud Developer
Tencent Cloud Developer
Mar 4, 2025 · Artificial Intelligence

A Practical Guide to Building Large Language Model Applications: Prompt Engineering, Retrieval‑Augmented Generation, Function Calling and AI Agents

The guide teaches non‑AI developers how to build practical LLM‑powered applications by mastering prompt engineering, function calling, retrieval‑augmented generation, and AI agents, and introduces the Modal Context Protocol for seamless tool integration, offering a clear learning path to leverage large language models without deep theory.

AI AgentFunction CallingLLM
0 likes · 48 min read
A Practical Guide to Building Large Language Model Applications: Prompt Engineering, Retrieval‑Augmented Generation, Function Calling and AI Agents
Nightwalker Tech
Nightwalker Tech
Mar 1, 2025 · Artificial Intelligence

Exploring Cursor’s Agent Mode: Features, Usage Tips, and Advanced Techniques

This article introduces Cursor’s AI‑driven Agent mode, details the latest updates, explains core functionalities, shows how to enable and use it, and provides seven advanced tips—including context management, code generation, version control, and custom AI rules—to boost developer productivity.

AI AgentCursorDeveloper Tools
0 likes · 19 min read
Exploring Cursor’s Agent Mode: Features, Usage Tips, and Advanced Techniques
Java Tech Enthusiast
Java Tech Enthusiast
Feb 19, 2025 · Artificial Intelligence

AI Agent Development Guide: Building Intelligent Agents with Coze Platform

The guide explains how to build AI agents—digital labor forces that follow instructions, plan tasks, and use tools—using ByteDance’s no‑code Coze platform, outlining a 3‑phase, 10‑step framework, emphasizing business‑first design, tool integration, and concise, scenario‑driven development with real‑world case studies.

AI AgentAgent Development FrameworkBusiness Applications
0 likes · 7 min read
AI Agent Development Guide: Building Intelligent Agents with Coze Platform