About the Guest
Conor Grennan
Chief AI Architect, NYU Stern School of Business; Founder, AI Mindset
Conor Grennan is the Chief AI Architect at NYU Stern School of Business and the founder of AI Mindset, a company that trains Fortune 500 executives and business leaders on how to effectively integrate AI into their workflows. He is recognized for his focus on the behavioral and mindset changes required to fully leverage AI, rather than just the technical tools. Grennan consults widely across industries, helping organizations move from surface-level AI use to strategic AI partnership.
In this episode of the Silicon Valley Girl Podcast, Marina Mogilko interviews Conor Grennan, Chief AI Architect, NYU Stern School of Business; Founder, AI Mindset. Marina Mogilko interviews Conor Grennan about why most professionals are falling behind on AI due to behavior, not lack of tools. They explore how to shift from using AI as a search engine to treating it as a strategic thinking partner, including practical techniques like building AI memory and using power prompts. Grennan also addresses how hiring is changing, with up to 30% of entry-level roles at risk, and why entrepreneurship is uniquely positioned to thrive in the AI era.
Key Takeaways
- AI adoption is lower than most people assume — the gap is behavioral, not technological; people default to using AI like Google instead of as a collaborative thought partner.
- Building AI memory takes minutes: you can transfer context and personal background between platforms so every AI tool you use understands who you are and what you need.
- Two power prompts that unlock AI's real value are 'push back on this' and 'what am I missing?' — both force the AI to surface blind spots rather than just validate your thinking.
- Approximately 30% of entry-level jobs are at risk as AI automates entry-level tasks; job seekers who visibly demonstrate AI fluency in interviews will stand out significantly.
- Now is described as one of the best moments in history to be an entrepreneur, because AI dramatically lowers the cost and barrier to building products and testing ideas quickly.