The New RAG Method that Sees the Page Instead of Reading It
👉 Access our Starter Apps & AI Architects course in our community https://www.theaiautomators.com/?utm_... 🔗PixelRAG Demo: https://pixelrag.ai/ GitHub Rep: https://github.com/StarTrail-org/Pixe... Research Paper: https://github.com/StarTrail-org/Pixe... 🔗Other Resources ColPali (arXiv): https://arxiv.org/abs/2407.01449 VisRAG (arXiv): https://arxiv.org/abs/2410.10594 DeepSeek-OCR (arXiv): https://arxiv.org/abs/2510.18234 When an AI agent comes back empty handed, it's usually not because the answer wasn't there. It's because it didn't survive being flattened into text. Almost every agent grounds itself in some body of content, and the first step is nearly always the same: convert a messy page or PDF into markdown, where tables, charts and diagrams don't always survive the trip. New research from Berkeley, Princeton, EPFL and Databricks puts a number on it: over a third of failures on a 1,000-question Wikipedia benchmark traced back to parser loss. So they asked a more radical question. What if you don't convert the page to text at all? That's PixelRAG. Render each page as an image, tile it, embed the tiles with a vision model, and hand the screenshots straight to a VLM at query time. In this video I walk through the architecture, demo the app indexing over 7 million Wikipedia pages, and show the PixelShot skill in Claude Code reading a diagram WebFetch couldn't touch, along with the practical caveats before you'd adopt any of it. ⏱️ Timestamps: 00:00 Demo 05:11 PixelShot Agent Skill 06:56 Architecture 09:33 Findings and Conclusions #AI #AIAgents #RAG #PixelRAG #VisionRAG #VLM #ColPali #VisRAG #DeepSeekOCR #Docling #ClaudeCode #WebFetch #AgenticRAG #ContextEngineering #AIArchitects #AIBuilder
Andrej Karpathy's Wiki Idea Was Just Shipped by Pinecone
I Ran DeepSeek's New DSpark and Doubled My Qwen3 Model’s Speed (Here’s How)
Is RAG Still Needed? Choosing the Best Approach for LLMs
Baidu Just Fixed DeepSeek-OCR for Reading Long Documents
Using Large Language Models | Build Your Own LLM Workshop #1
RAG Just Got Inverted. Here's The Stack That Replaces It.
Google's OKF: Why a Folder Beats the Vector Database
This New Google Format Gives Your AI Agent a Second Brain
The Multi-Agent Architecture That Actually Ships — Luke Alvoeiro, Factory
Karpathy's LLM Wiki - Full Beginner Setup Guide
The Next Era of Second Brains Is Here
Claude Code pro features in action to build Agentic RAG with MCP
The Database That Should Be Dead but Runs the Internet
RAG's Evolution: From Simple Retrieval to Agentic AI
RAG vs. CAG: Solving Knowledge Gaps in AI Models
Google Replaced The Karpathy's LLM Wiki
Don't learn AI Agents without Learning these Fundamentals
