A developer debugging a Python pipeline for building a RAG knowledge base discovered that a perceived memory leak was actually a measurement bug. The developer was using `ru_maxrss` from `resource.get…
HubSpot built a centralized vector storage and search platform called VaaS (Vector as a Service) on top of Qdrant, now handling over 20 billion vectors across 140+ clusters. The infrastructure powers …
A benchmark comparing pgvector, Qdrant, and Pinecone on 50 million 1536-dimensional embeddings found that Postgres with pgvectorscale served 471 queries per second at 99% recall, outperforming Qdrant'…
A developer reports three production issues with Ollama serving llama3.1:8b-instruct-q4_K_M for multi-turn conversations in Spanish, including the model treating a second system message as a response …
A developer built Vector Strike, a retro arcade game that visualizes how vector databases like Pinecone, Milvus, Qdrant, and pgvector perform semantic search. The game lets players configure similarit…
HubSpot has scaled its semantic search platform to manage over 20 billion vectors across 38+ teams, using an internal service called VaaS built on Qdrant. The company automated cluster management with…
An engineer warns that n8n RAG pipelines leak sensitive data to third-party LLM providers like OpenAI in plain text, despite the common belief that RAG keeps data secure in a vector database. The post…
A developer has created a multi-stage document validation pipeline for RAG knowledge bases that uses deterministic UUIDv5 hashing for exact deduplication and HyperMinHash for similarity detection, add…
A developer built a Go library for semantic LLM caching that combines deterministic hashing with vector similarity search to reduce costs from repeated but differently worded queries. The library supp…
Qdrant has vectorized 33.7 million Ukrainian court decisions from the Unified State Register of Court Decisions using Voyage AI's voyage-3.5 embedding model. The system, running on a dedicated EC2 ins…
SecondLayer, a Ukrainian legal tech company, proposes training a 860B-parameter Mixture-of-Experts model on a 2 TB corpus of Ukrainian legal data, including 96.2 million court decisions, legislation, …
A developer created a cheat sheet for deploying LangGraph agent servers, detailing how to package a LangGraph agent, run it locally with langgraph dev, deploy to LangSmith cloud, and stream it into a …
A developer with ADHD built an AI agent called 'hex' to help manage executive dysfunction by integrating with calendar, Todoist, Obsidian, web search, browser, TTS, and Telegram. The agent uses memory…
A developer built a semantic cache using sentence-transformers to reduce AI API costs by 80%. The cache stores embeddings of prompts and reuses responses for semantically similar queries, cutting a $4…
A developer tested four AI models—ChatGPT, Claude, Gemini, and Perplexity—on database recommendations for 2026, finding that Neon emerged as the default pick over incumbents. The analysis shows that A…
Llmaker, an open-source platform for self-hosting a complete LLM stack including models, vector databases, embeddings, caching, observability, and an agent layer, launched on Hacker News. The platform…
A developer demonstrates running a complete RAG agent offline using LangGraph, Ollama, and an embedded Qdrant instance, requiring zero API keys or Docker. The system uses a provider-swap design that a…
A developer compared four vector databases—Pinecone, Weaviate, Milvus, and Qdrant—in 2026, analyzing deployment complexity, latency benchmarks, filtering quality, and cost. Qdrant achieved the lowest …
Mem0, an open-source memory layer for AI agents with nearly 60,000 GitHub stars, has released v3.0 with temporal reasoning and multi-tenant isolation. The project scored 94.8 on LongMemEval and 91.6 o…
A developer created monlite, a TypeScript library that consolidates document storage, vector search, full-text search, key-value caching, job queuing, and cron scheduling into a single SQLite file. Th…