In-depth, opinionated guides on shipping production AI systems — Retrieval-Augmented Generation (RAG), LangChain and LangGraph agent workflows, vector search, Next.js performance, TypeScript architecture, and the DevOps that holds it all together. Every post is written for engineers who have to make the trade-offs, not just describe them.
· Written by Niraj Kumar
Practical breakdowns of AI systems, scalable backends, modern web stacks, and production-ready engineering.
46 articles found
A complete guide to architecting and building a production-grade Retrieval Augmented Generation (RAG) system using LangChain for orchestration and Next.js for the frontend, covering ingestion, retrieval, streaming, and deployment best practices.
Read ArticleA practical, code-first guide to building a production-ready GraphQL API on Node.js using Apollo Server and KitQL, covering schema design, resolvers, and hybrid REST/GraphQL architectures for mixed-client apps.
Read ArticleLearn how to harden Node.js APIs with Redis-based rate limiting, caching strategies, and observability using Prometheus and structured logging — with practical, production-ready code examples.
Read ArticleA pragmatic, engineering-first comparison of modular monoliths and microservices in 2026 — covering when each architecture wins, real-world examples, code patterns, and common pitfalls to avoid.
Read ArticleA practical, in-depth comparison of PostgreSQL and MongoDB covering schema design, scaling strategies, consistency models, and developer experience to help you pick the right database in 2026.
Read ArticleLearn how to build real-time live chat, push notifications, and live dashboards using Socket.IO with a React and Node.js stack, including scaling, auth, and production best practices.
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