Agentic RAG — 13 Technical Articles

Apr 22, 2026 · Artificial Intelligence

From Flawed RAG to Production‑Ready: Deep Dive into Scaling Retrieval‑Augmented Generation

This expert roundtable dissects why RAG often fails in production—low recall, hallucinations, cost overruns—and walks through concrete diagnostics, hybrid search designs, knowledge‑engineering tricks, GraphRAG and Agentic RAG advances, plus practical deployment, security, and cost‑optimization guidelines.

AI DeploymentAgentic RAGHybrid Search

0 likes · 20 min read

From Flawed RAG to Production‑Ready: Deep Dive into Scaling Retrieval‑Augmented Generation

CodeTrend

Apr 21, 2026 · Artificial Intelligence

AI Agents for Beginners: A Zero‑Prerequisite Course Overview

This article breaks down Microsoft’s open‑source AI‑Agent learning repository, explaining core concepts, five design patterns, production deployment considerations, and emerging protocols, while offering practical engineering guidance for building reliable multi‑agent systems from scratch.

AI agentsAgentic RAGMetacognition

0 likes · 10 min read

AI Agents for Beginners: A Zero‑Prerequisite Course Overview

SuanNi

Mar 24, 2026 · Artificial Intelligence

How Compression, Orchestration, and LangGraph Are Redefining LLM Context Engineering

This article analyzes the six pillars of context engineering for large language models, focusing on compression techniques, extractive vs. abstractive methods, the LLMLingua toolkit, dynamic orchestration with routing and agentic RAG, and how LangGraph enables sophisticated agent‑driven workflows.

Agentic RAGContext CompressionLLM

0 likes · 14 min read

How Compression, Orchestration, and LangGraph Are Redefining LLM Context Engineering

DataFunTalk

Feb 28, 2026 · Artificial Intelligence

Exploring Cutting‑Edge AI Search & Recommendation: Agentic RAG, LLM‑Enhanced Recs, and Baidu’s Generative Ranking

This article reviews three advanced AI-driven solutions—Alibaba Cloud's Agentic RAG for high‑concurrency multimodal search, Huawei Noah's LLM‑augmented recommendation architecture, and Baidu's generative ranking model GRAB—detailing their challenges, designs, performance gains, and practical deployment insights.

AI searchAgentic RAGAlibaba Cloud

0 likes · 8 min read

Exploring Cutting‑Edge AI Search & Recommendation: Agentic RAG, LLM‑Enhanced Recs, and Baidu’s Generative Ranking

DataFunTalk

Feb 11, 2026 · Artificial Intelligence

Why Most RAG Deployments Fail and How to Build a Production‑Ready RAG System

This round‑table dissects the gap between RAG’s hype and real‑world production, exposing common pitfalls such as low recall, hallucinations and cost overruns, and then delivers a systematic diagnostic framework, hybrid search strategies, fine‑tuning rules, and practical best‑practice roadmaps for building reliable enterprise RAG solutions.

Agentic RAGFine-tuningHybrid Search

0 likes · 20 min read

Why Most RAG Deployments Fail and How to Build a Production‑Ready RAG System

DataFunSummit

Dec 19, 2025 · Artificial Intelligence

How Agentic RAG, LLM‑Powered Recommendations, and Generative Ranking Transform AI Search and Ads

This article surveys cutting‑edge AI techniques—including Alibaba Cloud's Agentic RAG for multimodal search, Huawei Noah's LLM‑enhanced recommendation evolution, and Baidu's generative ranking (GRAB) for ads—detailing their architectures, optimization tricks, performance gains, and real‑world deployment results.

AI searchAgentic RAGGPU acceleration

0 likes · 9 min read

How Agentic RAG, LLM‑Powered Recommendations, and Generative Ranking Transform AI Search and Ads

phodal

Nov 27, 2025 · Artificial Intelligence

How AutoDev’s Agentic RAG Turns Docs into a Programmable Knowledge Base

This article explains how AutoDev builds an Agentic Retrieval‑Augmented Generation system with a Document Query Language (DocQL) that lets LLM agents navigate hierarchical code and documentation structures using JSONPath‑like queries, detailing implementation, multi‑level keyword expansion, and experimental findings.

AIAgentic RAGDocQL

0 likes · 12 min read

How AutoDev’s Agentic RAG Turns Docs into a Programmable Knowledge Base

DataFunTalk

Nov 25, 2025 · Artificial Intelligence

Unlocking Agentic RAG and Generative Ranking: AI Search & Recommendation Breakthroughs

This article summarizes cutting‑edge techniques from Alibaba Cloud AI Search’s Agentic RAG architecture, Huawei Noah’s LLM‑enhanced recommendation evolution, and Baidu’s GRAB generative ranking model, detailing multi‑agent retrieval, multimodal data handling, scaling laws, causal attention, and performance gains demonstrated through benchmarks and real‑world deployments.

AI searchAgentic RAGGenerative Ranking

0 likes · 8 min read

Unlocking Agentic RAG and Generative Ranking: AI Search & Recommendation Breakthroughs

Alibaba Cloud Developer

Jul 25, 2025 · Artificial Intelligence

Build an Agentic RAG AI App in Days with RDS Supabase & LangChain

This article demonstrates how to rapidly create a full‑stack Agentic Retrieval‑Augmented Generation (RAG) application using Alibaba Cloud RDS PostgreSQL‑based Supabase, covering data preparation, vector storage, real‑time communication, authentication, deployment steps, performance optimizations, and code examples with LangChain and large language models.

AI ApplicationAgentic RAGLangChain

0 likes · 18 min read

Build an Agentic RAG AI App in Days with RDS Supabase & LangChain

Tencent Cloud Developer

Jul 15, 2025 · Artificial Intelligence

How RAG Evolved: From Naive to Agentic – A Complete Guide

This article systematically outlines the evolution of Retrieval‑Augmented Generation (RAG) from its naive three‑step pipeline to advanced, modular, and agentic architectures, highlighting each generation's motivations, core features, advantages, drawbacks, and practical implementation details for large language model applications.

Agentic RAGArtificial IntelligenceLLM

0 likes · 20 min read

How RAG Evolved: From Naive to Agentic – A Complete Guide

AI Algorithm Path

Jul 3, 2025 · Artificial Intelligence

Exploring Advanced, Graph, and Agentic RAG: The Evolution of Retrieval‑Augmented Generation

This article examines how Retrieval‑Augmented Generation (RAG) has progressed from simple keyword‑based retrieval to advanced semantic methods, modular architectures, graph‑enhanced reasoning, and autonomous agentic systems, highlighting each approach's workflow, benefits, limitations, and the shift toward dynamic AI decision‑making.

AIAgentic RAGGraph RAG

0 likes · 7 min read

Exploring Advanced, Graph, and Agentic RAG: The Evolution of Retrieval‑Augmented Generation

Architect's Alchemy Furnace

Jun 4, 2025 · Artificial Intelligence

What Is an AI Engineer? Roles, Skills, and the Future of LLM‑Powered Systems

This article examines the evolving role of the AI engineer, contrasting it with AI researchers, ML engineers, and software engineers, outlines essential skills such as prompt engineering, MLOps, and data integration, and predicts how AI engineering will become a pivotal, high‑demand discipline in the coming years.

AI SystemsAI engineeringAgentic RAG

0 likes · 17 min read

What Is an AI Engineer? Roles, Skills, and the Future of LLM‑Powered Systems

AI Large Model Application Practice

May 6, 2025 · Artificial Intelligence

How to Build an Agentic RAG System from Scratch Using MCP Architecture

This article walks through the design and full implementation of an Agentic Retrieval‑Augmented Generation (RAG) system built on the MCP standard, covering the conceptual fusion of MCP and RAG, server‑side tool creation with LlamaIndex, client‑side agent construction with LangGraph, configuration files, caching strategies, code examples, and an end‑to‑end demonstration.

Agentic RAGLLMLangGraph

0 likes · 15 min read

How to Build an Agentic RAG System from Scratch Using MCP Architecture