100% agree.
rag + careful prompting + eval loops. that's it. ships faster, costs less, and updates instantly when the world changes.
fine-tuning at startup scale is almost always a vanity project disguised as a technical decision. teams want "our own model" on the pitch deck more than they want a working product.
save the fine-tuning budget. spend it on better data pipelines and retrieval quality. boring wins.