The folder on your desktop is mocking you. It contains transcripts from the last 50 user interviews and sales calls. Buried inside is the key to next quarter’s roadmap, the "aha" moment you need. So you do what any modern PM would: you zip them up, feed them to an AI, and type: "Find the main user pain points."
Ten seconds later, you get a beautifully formatted, completely useless list.
- "Users want the product to be easier to use."
- "Customers mentioned pricing as a factor."
- "Performance improvements were a common theme."
This isn't insight. It's a fortune cookie. You just wasted your time and a few cents of API credits to learn nothing. The problem wasn't the AI. The problem was your approach. You treated the AI like a search engine, not a junior product analyst.
An AI doesn't understand context. It doesn't know your company’s desperate push to enter the enterprise market, or that the "performance" complaints are all coming from one legacy user group you’re planning to deprecate. It just counts words and finds patterns. To get real value, you need to stop dumping and start directing.
Prime the AI Before You Prompt It
Think of it like onboarding a new team member. You wouldn't just point them to a folder and say "find insights." You'd give them context. You'd explain the company strategy, who the key customers are, and what you’re trying to achieve this quarter.
Your AI needs the same onboarding.
1. Give It the "Company Brain" Before you upload a single transcript, feed the AI the essential context in the same prompt window. This is your priming document. It should be short and clear.
Include:
- The Goal: "We are analyzing these calls to validate our Q3 product strategy
Generated by Reportify AI — Automate your team's status reports, standups, and weekly updates. Try free →