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Async Rust Meets Async Python: How Daft runs... by Colin Ho, Srinivas Lade

 📝NLP  Content type: Video
youtube.com·

10 MCP servers to connect LLMs with databases

 🤖n8n, automation, AI agents, Gemini, Claude, openrouter, grok, chatgpt
infoworld.com·

RohiRIK/OpenLtm: Long-Term Memory plugin for Claude Code — semantic search, context injection, session learning

 🔍RAG  Content type: Code
github.com··Hacker News, r/SideProject, r/mcp, r/vibecoding

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

 👥CrewAI  Content type: Discussion
news.ycombinator.com··Hacker News

A Bigger Toolbox for MCP

 💬Prompt Engineering
cra.mr·

Researchers trained an open source AI search agent, Harness-1, that outperforms GPT-5.4 on recalling relevant information

 🤖Transformers
venturebeat.com··Hacker News

memory OS for AI agents (ranks, compresses and evolves agents memory)

 🔍RAG
thrindex.com··Hacker News

Build a 'Brain' for Your AI: How to Create a Knowledge Base Chatbot Using Vector Databases

 📝NLP  Content type: Blog
medium.com
·

Kuramoto Attention: Synchronizing Self-Attention on the Torus

 🤖Transformers  Content type: Academic
arxiv.org·

Postgres 19 Beta 1 is here

 🗄️Vector Databases
postgresweekly.com·

The AI Agents Stack (2026 Edition)

 💬Prompt Engineering  Content type: Blog
oreilly.com·

HelixDB/helix-db: HelixDB is an OLTP graph-vector database built in Rust.

 📝NLP  Content type: Code
github.com··Hacker News

The Read Model Zoo: Projections Beyond Tables - EventSourcingDB

 🗄️Vector Databases  Content type: Blog  Content type: Reference
docs.eventsourcingdb.io··Hacker News

| Amine Raji, PhD

 📝NLP
aminrj.com·

The week AI infrastructure crossed from a technology story to a financial one

 🤖Automation  Content type: News
mlwhiz.com·

Predictive Processing: Conscious when Training

 📝NLP
lesswrong.com·

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

 🌐Web Development  Content type: Discussion
news.ycombinator.com··Hacker News

LangChain vs LlamaIndex 2026: Response Time on 10 RAG Tasks

 🦜LangChain  Content type: Blog  Content type: Discussion
tildalice.io·

I kept losing good answers in my AI chat history, so I built search for it

 🔍RAG  Content type: Blog
indiehackers.com·

Aperon Technical Report: Hierarchical No-Pointer Tangent-Local Search for High-Dimensional Approximate Nearest Neighbors

 🗄️Vector Databases  Content type: Academic
arxiv.org·
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