Your biggest obstacle is proving fine-tuning is more effective than prompting, workflow design, RAG, etc during the initial pass. Most of my customers are still getting big improvements by picking the low-hanging fruit with those approaches. A much smaller fraction is at a place where they're ready to start fine-tuning. Obviously, this will change as AI programs mature.
Exactly! Finetuning needs at least 10 examples to even work. That’s why Promptrepo begins with prompting and schema-based generation when teams have little or no data. As they gather more examples, it gradually shifts to fine-tuning. It’s the classic cold start problem and we’ve simplified it for product teams who want to launch quickly but improve accuracy over time.
