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A Conversation with Nita Laad
Catching up on another episode with Nita Laad – Bay Area tech leader, engineer-turned-entrepreneur, and founder of Nexia AI – as she shares her journey from growing up in Goa, India to building enterprise-scale products in Silicon Valley and now shaping the future of human-plus-AI collaboration. With over 20 years across engineering, product, and go-to-market roles at companies like Cisco, HP, and FireEye, Nita unpacks what it really takes to move from corporate scale to startup speed, and why AI should amplify humans—not replace them.
In this episode, you’ll learn:
• How Nita’s engineering foundation and two degrees in computer engineering shaped her approach to product, strategy, and entrepreneurship.
• Why customers don’t buy features—they buy outcomes—and how that insight drove her pivots from engineering to product and GTM leadership.
• The real challenges of selling AI in the enterprise, from adoption fears to governance, regulation, and ROI.
• A pragmatic take on AI’s future, AGI hype, and why the pace of adoption matters more than the pace of innovation.
• Key lessons for founders transitioning from corporate environments to startups—and why speed, adaptability, and curiosity win.
• Advice for young women and aspiring entrepreneurs on taking risks, crossing streams, and building careers around learning, not titles.
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By Michael PeresCatching up on another episode with Nita Laad – Bay Area tech leader, engineer-turned-entrepreneur, and founder of Nexia AI – as she shares her journey from growing up in Goa, India to building enterprise-scale products in Silicon Valley and now shaping the future of human-plus-AI collaboration. With over 20 years across engineering, product, and go-to-market roles at companies like Cisco, HP, and FireEye, Nita unpacks what it really takes to move from corporate scale to startup speed, and why AI should amplify humans—not replace them.
In this episode, you’ll learn:
• How Nita’s engineering foundation and two degrees in computer engineering shaped her approach to product, strategy, and entrepreneurship.
• Why customers don’t buy features—they buy outcomes—and how that insight drove her pivots from engineering to product and GTM leadership.
• The real challenges of selling AI in the enterprise, from adoption fears to governance, regulation, and ROI.
• A pragmatic take on AI’s future, AGI hype, and why the pace of adoption matters more than the pace of innovation.
• Key lessons for founders transitioning from corporate environments to startups—and why speed, adaptability, and curiosity win.
• Advice for young women and aspiring entrepreneurs on taking risks, crossing streams, and building careers around learning, not titles.