AI Product Sense: The depth that L7+ roles actually test for
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Product sense hasn't changed with AI—but it's now impossible to hide shallow thinking. Join Mahesh Yadav and Nancy Chu (ex-Meta Director, now Leadership Coach) for a masterclass on what AI product interviews actually test for at L6-L7+ levels.
2:15 - AI PM Job Market State (2025-2026 Data)
4:30 - Why Hiring is Taking 23-45 Days Now
6:45 - What AI PM Interviews Actually Test
9:20 - Case Studies: Vibe Coding Tools Requirement
12:00 - Product Taste Still Matters: Gamma, Lovable, Claude Code
18:30 - Nancy Chu Introduction & Background
20:15 - The $10K-$18K Per Week Opportunity Cost
22:40 - Assumption #1: AI Needs Different Frameworks (WRONG)
25:30 - Assumption #2: A Few Mocks Will Be Enough (WRONG)
28:45 - Why Product Sense is NOT a Math Problem
31:20 - How Fighter Pilots Build Judgment (6:1 Ratio)
34:00 - Live Example: "Help Humans Talk to Animals" Prompt
36:30 - The Mechanical Framework Approach (Surface Level)
42:15 - What's Actually Missing: Depth of Understanding
45:40 - Going One Layer Deeper: Beyond Functional Needs
49:20 - The Real Crux: Connection, Not Translation
53:45 - Pressure Testing: Is Language Really the Blocker?
58:10 - Grounding in Tech Reality: What Can AI Actually Do?
1:02:30 - Vision Setting: Reciprocal Emotional Understanding
1:06:15 - Solutioning: Plugging into Existing Workflows
1:10:45 - Ethical Considerations in AI Product Design
1:14:20 - The Three Core Principles Applied
1:17:50 - Summary: Why AI Removed the Safety Net
1:20:30 - Next Steps & Opportunity Cost Reminder
1:23:00 - Nancy's Community Offerings
1:25:15 - Q&A and Closing Thoughts
1:28:40 - Upcoming Sessions Preview (AI Security, Azure AI Foundry)
1:32:00 - Product Sense Bootcamp Details (April 4th)
1:35:20 - Final Resources & How to Connect
What You'll Learn:
Why AI product sense requires the same frameworks but deeper reasoning
-The costly assumptions that waste weeks of interview prep time
-How to move fr
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Chapters (29)
2:15
AI PM Job Market State (2025-2026 Data)
4:30
Why Hiring is Taking 23-45 Days Now
6:45
What AI PM Interviews Actually Test
9:20
Case Studies: Vibe Coding Tools Requirement
12:00
Product Taste Still Matters: Gamma, Lovable, Claude Code
18:30
Nancy Chu Introduction & Background
20:15
The $10K-$18K Per Week Opportunity Cost
22:40
Assumption #1: AI Needs Different Frameworks (WRONG)
25:30
Assumption #2: A Few Mocks Will Be Enough (WRONG)
28:45
Why Product Sense is NOT a Math Problem
31:20
How Fighter Pilots Build Judgment (6:1 Ratio)
34:00
Live Example: "Help Humans Talk to Animals" Prompt
36:30
The Mechanical Framework Approach (Surface Level)
42:15
What's Actually Missing: Depth of Understanding
45:40
Going One Layer Deeper: Beyond Functional Needs
49:20
The Real Crux: Connection, Not Translation
53:45
Pressure Testing: Is Language Really the Blocker?
58:10
Grounding in Tech Reality: What Can AI Actually Do?
1:02:30
Vision Setting: Reciprocal Emotional Understanding
1:06:15
Solutioning: Plugging into Existing Workflows
1:10:45
Ethical Considerations in AI Product Design
1:14:20
The Three Core Principles Applied
1:17:50
Summary: Why AI Removed the Safety Net
1:20:30
Next Steps & Opportunity Cost Reminder
1:23:00
Nancy's Community Offerings
1:25:15
Q&A and Closing Thoughts
1:28:40
Upcoming Sessions Preview (AI Security, Azure AI Foundry)
1:32:00
Product Sense Bootcamp Details (April 4th)
1:35:20
Final Resources & How to Connect
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