RAG

retrieval augmented generation, retrieval pipeline, chunking, indexing

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Modernizing attendance ticketing in SAS Viya using SAS Agentic AI Accelerator

 🧠Context Engineering  Content type: Blog
blogs.sas.com·

Why Most RAG Systems Slow Down After the First 3 Months

 📡Information Retrieval  Content type: Blog
blog.stackademic.com
·

Unlocking dependable responses with Gemini Enterprise Agent Platform’s Agentic RAG

 🧠Context Engineering  Content type: Blog
research.google·

I Built a RAG System in 2025. The “RAG Is Dead” Posts Keep Telling Me to Delete It.

 🧠Context Engineering
ai.gopubby.com
·

cylburn

 🗄️Vector Databases
margarinalia.my·

Location: Arlington Heights, IL, USA (Chicago Area) Remote: Yes Willing to reloc...

 🤖LLM Agents  Content type: Discussion

Hashtag Jakarta EE #336

 🧠Context Engineering
agilejava.eu·

If Algorithms Are Your Arsenal, Parameters Are Your Best Weapon

 📡Information Retrieval  Content type: Blog
medium.com
·

A Fun & Absurd Introduction to Vector Databases • Alexander Chatzizacharias

 🔍Semantic Search  Content type: Video
youtu.be··r/programming

AI context windows: Why context quality beats context size

 🧠Context Engineering  Content type: Blog
redis.io·

Hybrid Search for RAG: Fix Retrieval Accuracy in AI

 📡Information Retrieval  Content type: Blog
pingcap.com·

New comment by Revanthkodati in "Ask HN: Who wants to be hired? (June 2026)"

 💬LLMs

Energy-Efficient On-Device RAG on a Mobile NPU: System Design and Benchmark on Snapdragon X Elite

 🧠Context Engineering  Content type: Academic
arxiv.org·

Chunking: Stop Splitting Sentences Mid-Thought

 🗜️Context Compression  Content type: Blog
rephrase-it.com·

Toolora MCP Server – 12 free tools: PDF, OCR, QR codes, audio transcription, URL scraping, Excel, Word. No key needed.

 🔍Semantic Search
glama.ai··r/mcp

Build an AI-Powered Equipment Repair Assistant Using Amazon Bedrock AgentCore

 🧠Context Engineering  Content type: Blog
aws.amazon.com·

Agentic AI frameworks compared: LangChain, LangGraph, AutoGen

 🤖LLM Agents  Content type: Blog
udacity.com·

My Notes on the Progression from Context to Prompt to Harness engineering in making GPT LLMs Useful: (TUESDAY) MAMLMs

 🧠Context Engineering  Content type: News  Content type: Blog

Show HN: Incremental RAG ingestion, only changed chunks get re-embedded

 🗄️Vector Databases  Content type: Code
github.com··Hacker News
Less-relevant results

a desktop GUI to browse, search, & visualize your vector databases

 🔢Embeddings
vectorlens.dev··Hacker News

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