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Show HN: YourMemory, agentic memory is a pruning problem, not a hoarding problem

 🔍Information Retrieval  Content type: Discussion

When More Documents Hurt RAG: Mitigating Vector Search Dilution with Domain-Scoped, Model-Agnostic Retrieval

 📌Embedding Retrieval  Content type: Academic
arxiv.org·

Zero-Downtime Modernization: Norwegian Labor and Welfare Administration’s Path to Open Source Observability with OpenSearch

 🔎Inverted Index
opensearch.org·

The State Layer Behind Every Good AI Agent

 📌Embedding Retrieval  Content type: Blog

Quantum computing, agentic AI, and the next infrastructure layer in financial services

 📌Embedding Retrieval  Content type: Blog
elastic.co·

I built a free extension that adds shared folders + search across ChatGPT, Claude and Gemini

 📌Embedding Retrieval

Enterprises Are Quietly Moving Their AI Back On-Premises. Here Is Why.

 📌Embedding Retrieval  Content type: Blog
medium.com·

Foragd vs Inoreader vs Feedly: a feed reader comparison

 🔎Inverted Index
foragd.app·

meilisearch/meilisearch v1.46.1

 🔍Information Retrieval  Content type: Code
github.com
·

How DocValuesSkippers in Lucene 10 make range queries faster without doubling your storage

 🔎Inverted Index  Content type: Blog
elastic.co·

I launched SnapFound, a private screenshot search app for iPhone, and would love feedback

 🔎Inverted Index

OneRetrieval: Unifying Multi-Branch E-commerce Retrieval with an Editable Generative Model

 🔎Inverted Index  Content type: Academic
arxiv.org·

Show HN: Lore – LLM proxy for coding agent context and memory management

 🐧Operating Systems
withlore.ai··Hacker News

Connect Your Redis index to AI agents with RedisVL MCP

 📌Embedding Retrieval  Content type: Blog
redis.io·

Made my own writing app. Simple, yet for someone from non-IT background, it's a big personal win.

 🔎Inverted Index

Building AI shopping agent using Amazon Bedrock AgentCore Runtime and Amazon OpenSearch Service

 📌Embedding Retrieval  Content type: Blog
aws.amazon.com·

LangChain vs LlamaIndex 2026: Response Time on 10 RAG Tasks

 📌Embedding Retrieval  Content type: Blog  Content type: Discussion
tildalice.io·

How Ecolab rebuilt retail intelligence on Databricks and Anthropic Claude

 📌Embedding Retrieval  Content type: Blog
databricks.com·
Less-relevant results

Emmanuel Gatwech

 📌Embedding Retrieval

HNSW vs LSH: How Elasticsearch hits 0.99 recall@10 at 15,000 QPS — and what it costs

 🗂️Vector Indexes  Content type: Blog
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