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Building & Product

How do founders ship their first AI feature (APIs, wrappers, RAG in plain terms)?

Your first AI feature is usually one API call: send the model your instructions plus the user's input, get text or structured JSON back, and wrap it in your existing UI. RAG simply means fetching your own data (docs, tickets, listings) and pasting the relevant bits into the prompt so the model answers from your facts instead of its memory. Ship a thin version in days with the OpenAI or Claude API and a toolkit like Vercel's AI SDK, then iterate on prompts before touching anything fancier.

Go deeper

19 resources.

More in AI in Your Product

Should my startup add AI features, and which ones actually matter to users? 20 → How much does it cost to run AI features, and how do I keep costs sane? 19 → Which AI model should I build on (GPT, Claude, Gemini, open-source), and how do I avoid locking myself in? 17 → How do I test whether my AI feature actually works before launch (evals, in plain terms)? 18 → How do I stop my AI feature from making things up in front of customers? 17 → Prompt engineering, RAG, or fine-tuning: which one does my product actually need? 18 → How do I design AI features people trust (chat vs buttons, streaming, showing the work)? 18 → What is my moat if I'm building on someone else's model? 19 → Should I put an AI agent in my product, or is a simple workflow enough? 18 → Is it safe to send customer data to AI APIs, and what about privacy laws like India's DPDP Act? 18 → How should I price AI features: per seat, per use, or per outcome? 17 → My AI feature is live. How do I monitor it and make it better with real usage? 18 →

Also in Starting Up

The same ground, over in Build the product, our Starting Up track.

What actually counts as an MVP, and what's the smallest one I can get away with? 20 → Which no-code tool should I use to build my first product? 20 →
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