Fine-Tuning

Fine-tuning is the process of taking a pre-trained AI model and continuing to train it on your own specific data, so it learns your domain, tone, format, or task. A pre-trained model is a generalist; fine-tuning makes it a specialist. Use cases: customer service bots that speak in your brand voice, code assistants trained on your codebase's conventions, medical AI tuned on clinical notes. RAG is often a better first option (cheaper, no training needed), but for tasks requiring a specific style or format that RAG can't enforce, fine-tuning is the answer. OpenAI, Anthropic, and Google all offer fine-tuning APIs in 2026.