AI PM Interview Mistakes to Avoid in 2026

Hosted by Mahesh Yadav

7,327 students

In this video

What you'll learn

Beyond Product Sense: What happens in an AI PM Interview?

Learn about hiring signals in AI-specific interviews - system design and case studies.

Turn Your AI Knowledge Into a Working Product Portfolio

Stop talking about AI products in theory. Learn how to build, showcase, & present real AI agents.

Build Your First AI Product Using OpenClaw

You'll understand how AI product workflows translate into real builds using modern agentic frameworks.

Develop a Targeted Job Strategy That Works

Learn which roles to target, how to position your portfolio & what hiring managers look for in AI PM candidates.

Why this topic matters

Hiring managers reject "strategic thinkers" who can't build. AI PM roles require proof: working agents, live prototypes, portfolio evidence. This session teaches you to build interview-ready AI products using OpenClaw, demonstrate technical fluency without coding, and target roles that match your skills. Stop getting rejected. Start showing you can ship.

You'll learn from

Mahesh Yadav

Ex-GenAI Product Lead at MAANG Firms l AI PM Coach l 10k+ Alumni

Mahesh Yadav brings 20+ years of experience building AI products at Google, Meta, AWS, Microsoft. He holds 12 patents in AI training, power management and computer vision. He has launched major agentic-AI initiatives (for example launching an agent for AWS Bedrock, featured in CEO keynote) and trained thousands of professionals to succeed in AI roles. With this programme you get rare access to CEO-level of mentorship.

Currently, he is building back-office AI agents for the enterprise, starting with in-house legal teams through LegalGraph.AI. His work bridges education and real-world AI deployment, helping organizations adopt agentic systems that automate complex knowledge work.

Previously at