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.
Stop Blaming Your LLM: Fix RAG Retrieval Quality With Better Chunking in .NET

Stop Blaming Your LLM: Fix RAG Retrieval Quality With Better Chunking in .NET

1
Comments
7 min read
The Prep Tax: Why Miscommunicated Requirements Create Rework for AI Engineers (and How to Fix It)

The Prep Tax: Why Miscommunicated Requirements Create Rework for AI Engineers (and How to Fix It)

Comments
5 min read
We open-sourced Omega Walls: a stateful runtime defense for RAG and AI agents

We open-sourced Omega Walls: a stateful runtime defense for RAG and AI agents

4
Comments 2
2 min read
# Understanding RAPTOR: A Powerful Architecture for Hierarchical Retrieval in RAG Systems

# Understanding RAPTOR: A Powerful Architecture for Hierarchical Retrieval in RAG Systems

1
Comments
6 min read
Why Your RAG System Needs a Graph Database (Not Just Vectors)

Why Your RAG System Needs a Graph Database (Not Just Vectors)

1
Comments 1
6 min read
Complete RAG Tutorial Python: Build Your First Agent

Complete RAG Tutorial Python: Build Your First Agent

Comments
6 min read
Detecting Embedding Drift: The Silent Killer of RAG Accuracy

Detecting Embedding Drift: The Silent Killer of RAG Accuracy

Comments
7 min read
RAG Decisions Without Retrieval Proof: The Compliance Gap No One Audits

RAG Decisions Without Retrieval Proof: The Compliance Gap No One Audits

5
Comments
5 min read
When building AI chat is actually hard (how and why we built our agents)

When building AI chat is actually hard (how and why we built our agents)

Comments 1
6 min read
From RAG to Knowledge Graphs Why the Agent Era Is Redefining AI Architecture

From RAG to Knowledge Graphs Why the Agent Era Is Redefining AI Architecture

4
Comments 5
15 min read
Agentic AI

Agentic AI

Comments
2 min read
How to Build AI Agents That Actually Remember: Memory Architecture for Production LLM Apps

How to Build AI Agents That Actually Remember: Memory Architecture for Production LLM Apps

1
Comments
16 min read
Stop over-engineering your n8n RAG pipeline before you've shipped anything

Stop over-engineering your n8n RAG pipeline before you've shipped anything

1
Comments
4 min read
FERPA Compliance in RAG Pipelines: Five Rules Your Enterprise System Probably Breaks

FERPA Compliance in RAG Pipelines: Five Rules Your Enterprise System Probably Breaks

Comments
6 min read
Document Tool: Grounding AI in Enterprise Knowledge

Document Tool: Grounding AI in Enterprise Knowledge

1
Comments 1
3 min read
đź‘‹ Sign in for the ability to sort posts by relevant, latest, or top.