Choose Between Prompting, RAG, and Fine-Tuning

Thu, 03 Sep 2026 00:00:00 +0700

When an AI application produces weak results, teams often jump directly to fine-tuning. That can be the right choice, but many problems are cheaper and easier to solve with better prompting or retrieval-augmented generation (RAG).

The three approaches change different parts of the system. Prompting changes the instructions and context given at inference time. RAG supplies relevant external information at inference time. Fine-tuning changes the model’s learned parameters through additional training.

Fine-Tuning on Nalar

Choose Between Prompting, RAG, and Fine-Tuning