9 years of building production apps with Java, Spring Boot, React & JavaScript. Now exploring AI agents, LLMs, RAG, and LangChain. Learning in public.
A comprehensive guide to leveraging Java 21 Virtual Threads for building high-throughput HTTP proxies, with benchmarks showing 3x performance improvements over traditional platform threads.
How I went from theory to a working AI chatbot in production — using Next.js, FastAPI, Groq, LangChain, HuggingFace Embeddings API, and Neon Postgres with pgvector.
I watched AI Jason's RAG from Scratch course so you don't have to wade through 2.5 hours. Here's the core of what RAG is, how it works, and why it matters — explained the way I wish someone had explained it to me.
A Retrieval-Augmented Generation chatbot that answers Java interview questions from personal markdown notes. Built with Next.js 16, FastAPI, LangChain, Groq (Llama 3.1), HuggingFace Endpoint Embeddings, and Neon Postgres with pgvector. Frontend and Python backend co-deployed as a Vercel monorepo.
Production-ready REST API powered by Spring AI. Exposes RAG capabilities built on Java/Spring Boot with OpenAI integration, streaming responses, and pgvector for document retrieval.