Free Lesson
Prompting, RAG or Fine-Tuning? How AI PMs Decide
45 min
Oct 29, 2026 3:00 PM
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What you'll learn
Pick the right approach for your AI feature
A simple decision path for when to use prompting, RAG or fine-tuning, and what each costs.
Estimate token cost and latency
Work out what each approach costs per 1,000 users before you commit, so finance isn't surprised later.
Set up evals before launch
Use LLM-as-a-judge and a small test set to know if your feature is ready to ship.
Why this topic matters
Every AI feature starts with one question: prompt a model, add your own data with RAG, or fine-tune? Pick wrong and you burn weeks of engineering time. In this free 45-minute session, Jessica Ofoh walks through the decision path she used to lead 100+ AI-enabled solutions at Multiverse. You'll leave knowing which approach fits your feature and how to defend that choice to engineering and leadership.
