Jay Shah

“What was your entry point into AI and what sparked your initial interest?”

This is almost always the opening question, used to establish the guest's origin story.

“What was the rationale for your transition from academia to a startup, or from big tech to founding a company?”

He asks this to understand the career calculus behind major professional moves.

“Looking back at your career or education, is there anything you would do differently?”

A reflective question asked near the end to elicit personal insights and hindsight.

“What are the key differences or trade-offs between working in academia versus industry research?”

A recurring theme that explores the pros and cons of different career paths in AI.

“Can you describe the specific problems you're focused on in your current role or venture?”

This question transitions the conversation from personal history to the guest's technical work.

“Can you walk me through the findings of your specific research on [guest's paper/topic]?”

This demonstrates prior research and invites the guest to get into the technical details of their work.

“Looking ahead 5-10 years, what major trends or shifts do you anticipate in your area of AI?”

A standard future-focused question to elicit high-level predictions from the expert guest.

“Do you see the future of AI leaning towards single, large foundation models or multiple specialized ones?”

He poses this to get the guest's take on a central architectural debate in the AI community.

“What's your take on a current debate in the field, like scaling laws, using LLMs as evaluators, or open-source risks?”

This question surfaces the guest's opinion on a timely and often controversial topic.

“Beyond compute and data, what are the fundamental limitations or research challenges for current AI models?”

This probes for deeper, more foundational problems that are yet to be solved in the field.

“What advice would you give someone just starting out and wanting to enter the AI field today?”

This is a signature closing question to provide actionable takeaways for the audience.

“What common pitfalls should entrepreneurs in the AI space try to avoid?”

He asks this of guests with startup experience to extract lessons for aspiring founders.