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.
87 articles found
A practical 2026 guide to securing RAG and LLM applications against prompt injection and jailbreak attacks using Llama Guard, Ollama, Next.js Edge Middleware, and PostgreSQL-based threat logging aligned with the OWASP Top 10 for LLMs.
Read ArticleLearn how to replace brittle, rule-based RPA scripts with resilient, goal-driven multi-agent systems built with CrewAI, Playwright, and Node.js. Includes real code for autonomous web navigation, JSON validation, and PostgreSQL integration.
Read ArticleInstrument Next.js with OpenTelemetry, trace server-side LangChain calls, and attribute AI inference costs per tenant in PostgreSQL for usage billing.
Read ArticleWire Claude Code into GitHub Actions to review pull requests across security, performance and testability — line-by-line, before a human opens the diff.
Read ArticleStop cross-tenant leaks in B2B AI SaaS — PostgreSQL Row-Level Security for embeddings, tenant IDs from Next.js JWTs, and isolated retrieval.
Read ArticleBuild production human-in-the-loop approval gates in LangGraph with AsyncPostgresSaver, interrupt_before, and Command-based resume flows.
Read Article87 articles grouped into the subjects they go deepest on. Each hub collects the full series for that topic.
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