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LangGraph in Python: Building Stateful AI Agents
LangChain agents run in a straight line — call a tool, get a result, respond. This guide replaces that line with a graph: typed state, conditional edges, human-in-the-loop checkpoints, streaming, and a Postgres-backed production deploy, all in Python.
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How to Build an AI SaaS Product with Next.js, Stripe, and OpenAI
Building an AI feature is the easy part — this is the full build most tutorials skip: Clerk auth, Stripe subscription billing, OpenAI usage tracking, rate limiting, and an architecture that survives real traffic, all in Next.js.
Read article →Building an AI Agent Backend with Python, FastAPI, and LangChain
Every serious AI job listing in 2026 wants Python — this is the full build: a FastAPI and LangChain agent backend with real tools and streaming SSE, bridged cleanly to the Next.js frontend from Article #4.
Read article →Streaming AI Responses in Next.js with the Vercel AI SDK
Users stare at a blank screen for four seconds before your AI answers — streaming fixes that, and the Vercel AI SDK makes it almost free: useChat, streamText, streaming tool calls, structured objects, error handling, and production deployment on Vercel.
Read article →OpenAI Function Calling in 2026: A Complete Guide for Node.js Developers
Function calling is what turns an LLM from a text generator into something that actually does things. This is the complete Node.js + TypeScript guide — tool schemas, parallel calls, streaming, strict mode, tool_choice, and the production-grade error handling most tutorials skip.
Read article →Building a RAG Application with Next.js, OpenAI, and Pinecone — Step by Step
A complete, production-aware walkthrough of building a RAG application with Next.js App Router, OpenAI, and Pinecone — chunking, embeddings, vector search, streaming with the Vercel AI SDK, deployment, and the retrieval optimizations every tutorial skips.
Read article →How to Build an AI Agent with LangChain and OpenAI
A complete, production-minded walkthrough of building an AI agent with LangChain and OpenAI in TypeScript — tools, memory, the agent loop, error handling, deployment, and the things every tutorial leaves out.
Read article →Prompt Engineering for Developers: Practical Patterns
Prompt engineering is not magic incantations. For developers it is interface design — clear contracts, worked examples, and treating prompts like code you can test.
Read article →React Server Components in Next.js: Simple Guide
React Server Components split your tree across the network. Once you see where the server/client boundary sits, the whole model — and when to reach for "use client" — clicks into place.
Read article →TypeScript Patterns for Safer JavaScript Apps
The best TypeScript is not the cleverest. It is the code where wrong states will not compile — using the type system as a design tool, not a chore you satisfy after the fact.
Read article →Trustworthy AI Features: Product Engineering Guide
A model that is right 90% of the time can still feel broken if the other 10% shows up at the wrong moment. Trust is a product problem, not a model problem.
Read article →Web Performance Guide: Core Web Vitals for Engineers
Performance is a feature you can measure, and most of the wins are unglamorous. Ship less, ship it later, and stop blocking the main thread.
Read article →Design Systems That Scale: Tokens, Components, Teams
A design system is not a component library. It is an agreement — and agreements break the moment they stop being convenient to keep.
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