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Tencent Technical Engineering
Tencent Technical Engineering
Jun 16, 2025 · Artificial Intelligence

Mastering RAG and AI Agents: Practical Tips, Code Samples, and Evaluation Strategies

This comprehensive guide walks you through the fundamentals of Retrieval‑Augmented Generation (RAG) and AI agents, explains their inner workings, shares optimization tricks, provides ready‑to‑run code snippets, and demonstrates how to evaluate performance with metrics such as recall, faithfulness, and answer relevance.

AI agentsLLMPrompt Engineering
0 likes · 36 min read
Mastering RAG and AI Agents: Practical Tips, Code Samples, and Evaluation Strategies
Instant Consumer Technology Team
Instant Consumer Technology Team
May 15, 2025 · Artificial Intelligence

Unlocking Agentic AI: How Agent Workflows Transform Intelligent Automation

This article demystifies AI agents and agentic workflows, explaining their core components—LLMs, tools, and memory—while detailing planning, tool‑use, and reflection patterns, comparing agentic, non‑agentic, and traditional workflows, and exploring real‑world applications, advantages, and limitations.

AI agentsLLMMemory
0 likes · 21 min read
Unlocking Agentic AI: How Agent Workflows Transform Intelligent Automation
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
DevOps
DevOps
Dec 12, 2024 · Artificial Intelligence

The Future of Large Language Models: From Consumer Q&A to Agentic Workflows

Andrew Ng highlights that large language models are shifting from optimizing simple question‑answering for consumers to supporting complex agentic workflows, including tool usage, computer interaction, and multi‑agent collaboration, signaling a major evolution in AI capabilities.

AI TrendsAI agentsAgentic AI
0 likes · 8 min read
The Future of Large Language Models: From Consumer Q&A to Agentic Workflows
Tencent Cloud Developer
Tencent Cloud Developer
May 28, 2024 · Artificial Intelligence

AI Agents: Concepts, Key Components, and Development Frameworks

AI agents extend large language models with planning, short‑term and long‑term memory, and tool‑use capabilities, enabling autonomous task decomposition, external API interaction, and persistent knowledge retrieval; frameworks such as MetaGPT, LangChain, and CrewAI simplify building agents like a researcher that gather information, browse web content, and generate reports, heralding broader AI‑enhanced productivity.

AI agentsFrameworksMemory
0 likes · 20 min read
AI Agents: Concepts, Key Components, and Development Frameworks
Baidu Geek Talk
Baidu Geek Talk
May 8, 2023 · Artificial Intelligence

Augmented Language Models: Reasoning and External Tool Utilization

The survey shows that once language models exceed roughly ten billion parameters they spontaneously acquire two complementary abilities—step‑by‑step reasoning, often elicited by chain‑of‑thought prompts or scratch‑pad training, and the capacity to invoke external tools such as search engines, calculators, or robots—enabling them to retrieve up‑to‑date information, perform complex computations, and act in the world, thereby advancing toward general artificial intelligence.

AIPrompt Engineeringlarge language models
0 likes · 20 min read
Augmented Language Models: Reasoning and External Tool Utilization