Imagine training AI to be an expert in any field, from rocket science to Renaissance art. That's the promise of building custom AI agents, and new research shows a smarter way to make them truly knowledgeable. Traditional AI models often struggle when faced with niche topics. Building datasets for these specific fields is a major roadblock—it's time-consuming, expensive, and keeping them up-to-date is a constant struggle. This new research proposes a more efficient pipeline using Retrieval-Augmented Generation (RAG) and self-fine-tuning. Think of RAG as giving the AI a personal research library. It can access and process relevant information from a specific collection of documents, like medical textbooks or legal documents. This research uses the Desk Reference to the DSM-5 (psychiatric diagnostic manual) as a test case, transforming a general language model (Mistral-7B) into a specialized psychiatric assistant. The pipeline works by first converting the DSM-5 PDF into a structured JSON format. Then, using carefully crafted prompts, the AI generates a large question-and-answer dataset based on the DSM-5 content. Finally, this dataset is used to fine-tune the base language model, creating a specialized version. The results are impressive. Compared to a standard language model (GPT-3.5-turbo), the fine-tuned "psychiatric AI" performed significantly better when judged by GPT-4 on its ability to answer complex questions from the DSM-5. This approach has some big advantages. First, it’s dynamic. If the source material (like the DSM-5) gets updated, the AI can quickly absorb the new information without needing a complete retraining. Second, it addresses the data scarcity problem. It can generate large datasets from even limited source material, making it ideal for highly specialized fields. This research offers a practical and efficient way to build custom AI agents. While the psychiatric domain is a compelling example, the pipeline could be applied to countless other fields, from finance to engineering. Imagine having an AI expert at your fingertips, ready to answer your most specific questions—this research brings us one step closer to that reality.