Building AI-Powered Apps with Next.js and the OpenAI API
A practical playbook for shipping LLM features that feel fast, safe, and genuinely useful - not a chatbot bolted on the side.
Every product team is being asked the same question right now: "where's our AI?" The honest answer is that most AI features fail not because the model is wrong, but because the product around it is wrong. Here's the stack and the patterns we ship with.
The stack
- Next.js App Router for streaming UI from server components.
- Vercel AI SDK for unified provider access and React streaming hooks.
- Edge runtime for low-latency token streaming close to the user.
- Postgres + pgvector for embeddings and retrieval.
Three rules we don't break
1. Stream everything. A 4-second wait for a complete response feels broken. The same response streamed token-by-token feels intelligent.
2. Always ground. Pure LLM output is a liability. Retrieve from your own data first, then let the model reason over it.
3. Design for the failure case. Rate limits, timeouts, hallucinations - they will happen. Your UI must degrade gracefully, not crash.
AI isn't a feature you add. It's a layer that changes how the whole product behaves. Treat it that way and you'll ship things people actually use.