Prompt engineering, RAG, or fine-tuning: which one does my product actually need?

Work up the ladder: better prompts cost hours, RAG costs days and adds your own live data, fine-tuning costs weeks and only changes behaviour and style, not knowledge. Most teams that fine-tune could have gotten the same result from a cleaner prompt and better retrieval, so treat fine-tuning as a last resort for narrow, repeatable patterns at volume. The emerging umbrella skill is context engineering: deciding exactly what information lands in the model's window for each request.

A quick orientation. The real value is below: resources worth your time, from people who've actually done it.