DEV Community

#rag

Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

Posts

đź‘‹ Sign in for the ability to sort posts by relevant, latest, or top.
How many tokens does a web page cost your LLM? We measured 20 real pages

How many tokens does a web page cost your LLM? We measured 20 real pages

Comments 2
5 min read
Building a Production RAG Pipeline on AWS Lambda and pgvector

Building a Production RAG Pipeline on AWS Lambda and pgvector

Comments 1
17 min read
When does an agent beat RAG? We benchmarked three pipelines on a TigerGraph knowledge graph

When does an agent beat RAG? We benchmarked three pipelines on a TigerGraph knowledge graph

Comments
4 min read
Online Course Tutor Retrieval Architecture — Tuning Relevance Without Index Waste

Online Course Tutor Retrieval Architecture — Tuning Relevance Without Index Waste

Comments
4 min read
How to Make RAG Show Its Evidence: Claim Verification at 15M-Document Scale

Stanford's enterprise legal RAG failure stats

How to Make RAG Show Its Evidence: Claim Verification at 15M-Document Scale

25
Comments 62
25 min read
RAG vs. Fine-tuning vs. Prompt engineering: 5 cues to choose the right approach for enterprise data

RAG vs. Fine-tuning vs. Prompt engineering: 5 cues to choose the right approach for enterprise data

Comments
7 min read
How to Build Financial Dashboard Pagination with Traceable Retrieval Contracts

How to Build Financial Dashboard Pagination with Traceable Retrieval Contracts

Comments
6 min read
Grew the Collection from 5 Entries to 741 Real Chunks

Grew the Collection from 5 Entries to 741 Real Chunks

Comments
2 min read
Building a RAG App That Knows When to Say "I Don't Know"

Building a RAG App That Knows When to Say "I Don't Know"

Comments
2 min read
Identical or Similar? AI-Powered Product Matching with Amazon Bedrock and S3 Vectors

Identical or Similar? AI-Powered Product Matching with Amazon Bedrock and S3 Vectors

2
Comments
36 min read
Architecting Stateful AI Agents in Laravel: Bridging n8n, MCP, and RAG for Production Workflows

Architecting Stateful AI Agents in Laravel: Bridging n8n, MCP, and RAG for Production Workflows

7
Comments
14 min read
Why Does RAG Hallucinate When the Right Documents Exist?

Why Does RAG Hallucinate When the Right Documents Exist?

6
Comments 2
4 min read
Close the Loop: Chatbot Analytics That Turn Misses Into Fixes

Close the Loop: Chatbot Analytics That Turn Misses Into Fixes

Comments
3 min read
Semantic Caching and Live Internet Search: Tools That Let AI Cache Answers to Save Money, and Pull Data From the Web When It Needs To

Semantic Caching and Live Internet Search: Tools That Let AI Cache Answers to Save Money, and Pull Data From the Web When It Needs To

Comments 4
9 min read
UNREAL Unifies Retrieval & Long‑Context—Cut Latency 50% in One Pass!

UNREAL Unifies Retrieval & Long‑Context—Cut Latency 50% in One Pass!

Comments
7 min read
đź‘‹ Sign in for the ability to sort posts by relevant, latest, or top.