By the end of this lesson, you will understand the decision framework for choosing between prompt engineering, Retrieval Augmented Generation (RAG), and fine-tuning AI models, recognizing the appropriate use cases, costs, and timelines for each approach.
Most companies waste significant resources on fine-tuning AI models when simpler, more cost-effective methods like prompt engineering or RAG would suffice.
A common mistake is to immediately jump to fine-tuning when an off-the-shelf LLM doesn't perform perfectly.