Spend less time writing docs and more time deciding what to build.
Get the Principal Product Manager briefIn 2026, AI handles much of the first draft work a Principal PM used to do by hand: synthesizing customer interviews, turning rough notes into structured PRDs, and pulling themes from support tickets and reviews. It also speeds up competitive teardowns and data exploration, so you can test a hypothesis against usage data in minutes instead of waiting on an analyst. The judgment about what matters and why still sits with you, but the busywork around it shrinks.
Paste these into Claude or ChatGPT and replace the bracketed parts with your own details.
Draft a product requirements document for [feature name]. The problem is [problem statement], the target user is [user segment], and success looks like [success metric]. Include goals, non-goals, user stories, key requirements, and open questions.Here are notes from [number] customer interviews about [topic]: [paste notes]. Identify the top 5 recurring problems, how many users mentioned each, and any quotes that capture the problem clearly.Here is my product strategy for [product/area]: [paste strategy]. Argue against it as a skeptical executive. List the weakest assumptions, the biggest risks, and what evidence would change my mind.I can build either [option A] or [option B] this quarter but not both. Context: [goals, constraints, data]. Write a one page recommendation memo with the tradeoffs, my recommendation, and the reasoning.Cluster this raw customer feedback into themes and rank them by frequency and severity: [paste feedback]. For each theme, note the likely root cause and one possible solution.One AI tool, one prompt, and one trick for Principal Product Managers, every weekday morning. Free.