A technical guide demonstrates how to build a human-in-the-loop feedback RAG system that captures team corrections and retrieves them into LLM prompts. The pipeline covers modeling corrections as stru…
A developer built a retrieval-augmented generation (RAG) knowledge base using Amazon Bedrock, Aurora PostgreSQL with pgvector, and Terraform, all synced automatically from a Git repository via GitHub …
A developer built Ravn, an open-source Python error monitoring tool, after finding Sentry's pricing too expensive for a side project. Ravn captures exceptions with two lines of code, groups similar er…
A developer argues that 90% of AI startups launched last year were thin wrappers over LLM APIs and failed when providers released native features. To build defensible AI apps, the developer recommends…
Researchers introduced HyphaeDB, an agent-native memory infrastructure that repurposes HNSW graph topology from vector databases into a communication fabric for multi-agent AI systems, enabling knowle…
ForthWrite, an AI email assistant that learns a user's writing voice from every edit they send, launched on Hacker News. The tool uses retrieval-augmented generation (RAG) with Gmail Sent folder impor…
A team built ThreatLedger, an AI-powered Network Detection and Response dashboard, in 72 hours using AWS Aurora and Vercel. The tool turns raw security logs into actionable threat intelligence, aiming…
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 at BizFlowAI details a production-tested pattern for building reliable AI agents, emphasizing the importance of a clear job spec, robust tool design, and a split between stable system prom…
A developer built a universal review graph that aggregates ratings for any item across users using pgvector on Amazon Aurora PostgreSQL Serverless v2. The system matches differently spelled item descr…
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 Seoul-based backend developer built k-cosmos, an interactive 3D music space that maps K-pop tracks using 768-dimensional vector embeddings, running entirely on the OCI Free Tier. The system uses a s…
A developer in Tunisia built Virantics, a self-learning vector database application on AWS Aurora Serverless PostgreSQL with pgvector, during a weekend hackathon. The app analyzes YouTube performance …
A developer built FarmOps Desk, a B2B SaaS for farm management, using Aurora, pgvector, and Bedrock. The system treats AI governance as a database primitive with atomic credit reservation and per-farm…
A developer built a complete RAG system from scratch using pgvector, Gemini embeddings, and MCP, covering setup, indexing, ingestion, search, and multi-step agents. The series concluded with deploymen…
A developer built and deployed a Retrieval-Augmented Generation (RAG) system to the cloud using Render and Supabase. The system uses pgvector for vector search and is accessible via an MCP server host…
A developer built a reusable tool server using the Model Context Protocol (MCP) to expose pgvector search functions as a standalone server that any LLM client can connect to. The implementation uses F…
A developer built a RAG system from scratch using pgvector and Gemini embeddings, explaining design decisions such as choosing pgvector over dedicated vector databases, using 768-dimensional embedding…
A developer built a RAG (Retrieval-Augmented Generation) system from scratch using pgvector and Google Gemini, implementing a full pipeline for embedding, vector storage, and semantic search. The proj…
A developer demonstrates how to integrate AI capabilities directly into PostgreSQL using the pgvector extension, enabling semantic search, natural language queries, and vector storage without a separa…