Problem-First AI Audit: Find Where AI Belongs in Your PM Process
Every leadership team wants an AI strategy. Far fewer can say which customer problems AI should solve. This 60-minute 1:1 session helps you find out where AI actually belongs in your product process, and where it does not. We map your product development lifecycle, or a project you are working on, through four phases: choose the problem, understand the customer, test solutions, and confirm the outcome. For each phase, we run your AI ideas through a problem-first filter, then pick the two or three places where AI will save you the most time or improve your decisions. Each one gets a gate: a clear check that keeps the speed from costing you product discipline. Breaking into product management? Bring a portfolio project or product idea. The session works the same way, and the result doubles as interview material on how you would apply AI with judgment. Before we meet, you complete a 10-minute intake form so we spend the full hour on your work. After the session, you receive a one-page summary with a 30-day plan.
What's included
Before we meet, you complete a short intake form (about 10 minutes) so the full hour goes to your real context. The session is a live working conversation over video, not a lecture. I bring a repeatable structure drawn from 20+ years of leading product teams for deciding where AI belongs and how to review what it produces. My examples use Claude, and the same approach works in any AI assistant. After the session, you receive a one-page written summary with your 30-day plan.
- A prioritized view of where AI helps in your process, mapped to four phases: choose the problem, understand the customer, test solutions, confirm the outcome
- A gate for each phase, so AI speeds you up without skipping the checks that keep decisions sound
- A four-question filter you can use to test any "add AI" request before work starts
- A one-page summary with a 30-day action plan
Meet your expert
Nate B.
Build AI Products hands-on with an expert
I help product leaders and teams build with AI, not just talk about it. I've spent 20+ years in B2B SaaS product, most recently as SVP of Product at Skillable, where I led a 75-person org, drove 110% NRR, and brought generative AI into our product development lifecycle. Before that I led product at Pluralsight (through its $2B acquisition), Canopy (tripled ARR two years running, scaled from 2 to 9 teams), and Instructure. Today I build AI products myself. I created ProductOS, a 14-agent AI-native product development framework now used by 500+ people, and toolaudit.ai, an AI tools comparison platform built on Next.js and Supabase. Working with me is hands-on. We'll pick a real problem from your roadmap or workflow and build it together: agent workflows, AI-assisted PRDs and discovery, prototyping with Claude Code, or a plan for putting AI into your team's PDLC. You'll leave with something working, not a slide deck.
