Answer eight questions about your problem and see whether prompting, structured outputs, RAG, fine-tuning or a combination is the best place to start.
What it helps you do
Teams often reach for fine-tuning when a better prompt or retrieval would solve the problem, or build retrieval when the real issue is output format. This framework matches your answers to the technique most likely to help first.
How to use it
Answer based on the problem as it is today. The result is a recommended starting point; confirm it with a small test on your own data.
Decision framework
0 of 8 answeredHow the recommendation works
Each answer adds weight to the techniques it favours. The highest total is the suggested starting point. When two techniques are close, combining them is often appropriate, for example RAG for facts with structured outputs for format.
Why prompting comes first
If a well-written, measured prompt has not been tried, start there. It is the cheapest option and the baseline every other technique must beat.
If you want to test more than one approach on your own data, our Generative AI team can help design the comparison.
Generative AI Development- Fine-tuning guideOpenAI · Documentationplatform.openai.com
- Fine-Tuning or Retrieval? Comparing Knowledge Injection in LLMsOvadia et al., Microsoft · 2023 · Research paperarxiv.org
- Structured outputsOpenAI · Documentationplatform.openai.com