Jacob Bank, CEO of Relay and former product lead at Gmail, joins Aishwarya Ashok to explore how AI agents are truly reshaping the way we work. He explains why structured AI workflows solve most real-world needs today and highlights the concept of “spiky intelligence,” where AI excels at some tasks but still needs human direction. Jacob emphasizes that the most important skill in this new era isn’t coding, but the ability to clearly define goals and structure problems for AI. He shares practical ways to use AI not just to replace tasks, but to automate complex, cross-platform outcomes—unlocking new levels of productivity and enabling small teams to achieve big results. 00:00 - Intro 1:17 - Welcome 2:34 - Jacob's Journey: From Google to AI Agents 3:25 - Beyond Tools: Focusing on Workflows & Outcomes11:34 - AI Workflows vs AI Agents: What's the Difference?19:43 - The Human Role: Critical Thinking & Future Skills27:30 - Understanding "Spiky Intelligence" in AI31:30 - How to Start Building Your Own AI Agents43:21 - Demo of Relay53:11 - Summary and Outcome of the agent

Ami Vora, CPO at Faire and former VP of Product & Design at WhatsApp, shares a unique perspective on how fear can be a driving force in decision-making and career growth. Raised in a family where fear played a significant role in shaping decisions, she turned fear into a tool for clarity.Rather than ignoring fear, she acknowledges it, writing down her fears and actively mitigating them when making big decisions, such as accepting a new job. By making the fear explicit, she unravels its power, turning it into actionable insights that help guide her.

Vora's experience reflects the ever-changing landscape of tech, where continuous learning is the only way to remain relevant. She draws on a lesson from a high school teacher, emphasizing the importance of staying on the frontier of knowledge to adapt to the unpredictable nature of the industry. Vora integrates this mindset by constantly challenging herself with low-stakes learning experiences outside of work, like ice skating, to reinforce the mindset of growth and adaptation. She reminds us that, especially in product and AI, there’s a need to embrace curiosity and let go of the pressure to always be right. In a world where everything is evolving rapidly, embracing failure and being comfortable with not knowing is essential for continual progress.Chapters0:00 Technology Won't Save You—Learning Will

2:09 Meet Ami Vora: From WhatsApp to Wild Versatility

4:04 How Jokes Helped Me Lead Through Hard Times

6:18 Turning Liberal Thinking Into a Career Superpower

9:00 What Actually Drives Us? Energy Over Everything

13:00 The Hardest Job I Stayed In—and What It Taught Me

17:00 Fear, Feedback, and Showing Up Anyway

20:00 Context Switching for Humans (Not Just AI)

22:08 The Tools I Trust: Reframing, Fear-Setting, and Closing Loops

36:02 AI, Agency, and Always Being Behind

43:27 Being Right vs Being Curious—The Career Mindset Shift

47:13 Execution > Strategy: Why Doing Beats Planning

51:25 My Career Is a Small Plates Dinner—and That’s a Superpower

Responsible AI is no longer just a theory—it's a necessity. In this episode of The Founder's Foyer, we sit down with Aishwarya Srinivasan to explore how organisations are tackling ethical AI in real-world environments.

This discussion covers deep and practical insights into data privacy, copyright, enterprise integrations, and the future of agent-based systems. If you're building with AI or implementing LLMs in your org, this episode is a must-watch.

Learn how AI adoption, compliance, and governance must go hand-in-hand to shape innovation responsibly.

Timestamps:00:00 – Introduction: Why Responsible AI Matters 02:42 – Data-Centric AI vs. Theory: Applying Ethics in Practice 07:35 – Copyright & Model Training Dilemmas 11:40 – Post-Training, Filters & What Data Should Be Used 16:10 – Role-Based Access & AI in Enterprise Workflows 22:25 – Productivity Tools & Data Privacy Risks 29:20 – Agent vs Automation: What’s the Difference? 35:10 – Human-in-the-Loop: Where It Matters Most 41:00 – Real AI Use Cases: Sales, GTM, and Non-Tech Teams 48:00 – The Need for Cross-Functional AI Literacy 52:45 – The Challenge of Data Silos and Integration 58:10 – Final Thoughts: Building Trustworthy AI Systems