Fine-tuning vs. Advanced Prompting

Welcome! As you become more skilled in prompt engineering, you'll encounter situations where simply crafting a better prompt might not be enough.

This lesson explores two powerful ways to customize Large Language Models (LLMs): advanced prompting and fine-tuning. We'll compare them to help you decide which strategy is best for different scenarios.

Advanced prompting involves carefully designing your input to guide a pre-trained LLM to produce specific, high-quality outputs without changing its underlying model weights.

• It's like giving very detailed instructions to a highly knowledgeable person.
• Techniques include Chain-of-Thought, RAG (Retrieval Augmented Generation), and persona prompting.

The model uses its existing knowledge, steered by your prompt.