Codersarts Blog.

Here's a question worth sitting with: when did you last fine-tune, retrain, or change the prompt on your production model — and how do you know it didn't make things worse? Not "did it feel better in the five examples you tried." How do you know. If your answer is "the demo looked good" or "the team felt like it was more helpful," you're not alone — and you're also flying blind. The Pattern We See Constantly A team ships v1. It works well enough. A few months in, they fine-tu

A fine-tuned model can become much better at understanding domain-specific language, following certain workflows, or generating responses in a particular style. Traditional fine-tuning approaches tried to push knowledge into the model. RAG flips the approach completely. Instead of permanently storing information inside model weights, RAG allows the AI to retrieve relevant information dynamically at runtime.