When should an AI startup fine-tune a model vs prompt-engineer?

May 13, 2026 · AI

Prompt-engineer first for speed and cost. Fine-tune when you need consistent format, domain behavior, lower latency/cost at scale, or private in-house performance.

Default to prompt engineering (and RAG) until you can’t reliably hit your quality, latency, or cost targets. Fine-tune when you have repeatable tasks, a stable spec, and enough high-quality labeled examples to measurably improve outcomes or reduce per-request spend. If the problem is “missing knowledge,” use RAG; if the problem is “wrong behavior/format,” fine-tune.

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