---
title: "Discussion on \"Agentic RAG vs Traditional RAG: Architecting Real-Time AI Data Pipelines\" | Hashnode"
description: "Discussion on \"Agentic RAG vs Traditional RAG: Architecting Real-Time AI Data Pipelines\". Retrieval-Augmented Generation (RAG) solved the initial problem of LLM hallucinations by grounding models in factual data. But traditional RAG architectures share a fundamental flaw: they rely on static data.\nIf you are building an AI agent for finan..."
url: "https://hashnode.com/posts/agentic-rag-vs-traditional-rag-architecting-real-time-ai-data-pipelines/6a020e5fa78103c9c2e3b417"
---

[Feed](https://hashnode.com/feed) /

Discussion

# [Agentic RAG vs Traditional RAG: Architecting Real-Time AI Data Pipelines](https://alterlab.hashnode.dev/agentic-rag-vs-traditional-rag-architecting-real-time-ai-data-pipelines?utm_source=hashnode&utm_medium=feed)

Retrieval-Augmented Generation (RAG) solved the initial problem of LLM hallucinations by grounding models in factual data. But traditional RAG architectures share a fundamental flaw: they rely on static data. If you are building an AI agent for finan...

May 11 · 9 min read · alterlab.hashnode.dev  
Read the article

-   [#ai-agents](https://hashnode.com/tag/ai-agents)
-   [#data-pipelines](https://hashnode.com/tag/data-pipelines)
-   [#llm](https://hashnode.com/tag/llm)
-   [#python](https://hashnode.com/tag/python)
-   [#rag](https://hashnode.com/tag/rag)

## Written by

[AlterLab](https://hashnode.com/@alterlab)

@alterlab · San Francisco, USA

  
[View profile](https://hashnode.com/@alterlab)

Transforming the Web Into Data.

## Responses

Markdown supported · ⌘↵ to post

No responses yet.