The Founder to Fortune Podcast

Michael Raybman, former CTO of Hustle Fund and a founder whisperer, discusses the transformative power of AI-native tools and no-code platforms for aspiring tech entrepreneurs. He emphasizes how non-technical founders can accelerate their progress, showcasing a live demo of a working app built in minutes. The conversation highlights the changing landscape of hiring developers and the renewed value of product managers in the era of AI. Raybman offers valuable insights into navigating engineering team dynamics and scaling from prototypes to fully-fledged products.

What happens when two long-time product and engineering leaders—who once yelled at each other across the office—reunite on a podcast to decode the future of data and AI?In this episode, Vidya Raman hosts Anjan Kundavaram (CPO at Fivetran) and Chandler Hoisington (formerly CPO at EnterpriseDB and AWS exec) for a candid, behind-the-scenes conversation that spans:* Why the Lakehouse architecture is more than a buzzword—and how Iceberg is quietly winning the open standards race* Whether RAG, embeddings, and vector databases are already becoming yesterday’s news* What’s really holding enterprise AI adoption back (hint: it’s not just the models)* Why unstructured data is the new oil—and what most companies are missing* How the roles of PMs and engineers are being reshaped (but not replaced) by AIAnd a whole lot more—from the false promises of CI/CD for data to whether you’ll really need a vector DB six months from now. If you’re building, shipping, or leading in the age of intelligent infrastructure, this episode is one you won’t want to miss. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.foundertofortune.org

What happens when one of the world’s largest asset managers decides to think like a tech company? In this episode, Diwakar Goel, Global Head of Data at BlackRock, pulls back the curtain on how his team is orchestrating one of the most ambitious data transformations in the financial world.From powering global investments with a touchless analytics “green package,” to reimagining operations through a homegrown AI-infused task platform, Diwakar shares how data governance, privacy, and automation are embedded not as afterthoughts—but as design principles. You’ll hear how they balance speed and regulation, why operational excellence isn’t just grunt work anymore, and why he believes most AI projects need to start with something far less sexy: foundational data modeling.Oh, and did we mention he manages a 3,300-person org where 80% of operations are already fully automated?This is not your average CIO playbook.🔑 Topics Covered:* Why BlackRock treats data like code—and how it’s paying off* The surprising way AI is helping reduce employee churn in data ops* Why Diwakar prefers “boring” AI over “magical” AI* How a single-digit governance team handles massive compliance needs* What startups often get wrong when trying to sell to enterprises like BlackRock This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.foundertofortune.org

In this episode, we go inside the minds of two powerhouse CISOs—Rinki Sethi (Upwind, ex-Twitter, Rubrik, Bill.com) and Lucas Moody (Alteryx, ex-Palo Alto Networks)—as they unpack what it really takes to secure an enterprise in today’s world of AI, multi-cloud sprawl, and constant threat exposure.They talk candidly about:* The evolving role of the CISO—from reactive firewalls to boardroom influence* Why some vendors gain trust while others get ignored* The hidden complexity behind “simple” security practices like IAM* What early-stage founders consistently get wrong—and how to fix it* The parallel lessons from cloud, mobile, and now GenAI transformationsIf you’re building for the enterprise, selling to CISOs, or investing in cybersecurity, this is a blueprint you can’t afford to miss. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.foundertofortune.org

Pavi Ramamurthy, the Global CIO and CSO of Blackhawk Network, shares over 20 years of security expertise. He discusses balancing security risks with business goals, urging startup founders to foster genuine conversations with CISOs. Insights on the true costs of vendor switching reveal that perception is crucial, while the rise of shadow AI mimics earlier IT trends. Ramamurthy emphasizes the power of CISO communities, challenges of vendor selection, and why 'best-of-suite' often prevails in decision-making. His mantra? "Know your CISO!"

In this episode, Diamond Bishop shares his fascinating journey through AI, machine learning, and enterprise software, from working at Microsoft (Cortana), Amazon (Alexa), AWS, and Meta (PyTorch) to founding Augmend, an AI-driven DevOps knowledge assistant, which Datadog later acquired.He dives deep into building AI-powered enterprise products, the challenges of selling into large organizations, and why AI-driven automation is the future of DevOps and security operations. Diamond also unveils Bits.ai, Datadog’s intelligent AI assistant designed to automate on-call incident resolution, debugging, and code error fixing.For founders, product leaders, and AI enthusiasts, this episode is packed with lessons on enterprise GTM (Go-To-Market) for Developer Tools, AI-driven automation, and the future of software engineering.Key Topics Discussed:1️⃣ The Evolution of AI & Machine Learning2️⃣ Founding Augmend: AI for DevOps Knowledge Sharing3️⃣ The biggest challenges for Dev Tool startups4️⃣ Bits.ai: The AI Assistant for DevOps & Security5️⃣ Lessons in building with Gen AI & GTM InsightsWho Should Listen?✅ AI/ML Engineers & DevOps Professionals – Learn how AI-driven automation is transforming workflows✅ Tech Founders & Enterprise GTM Leaders – Get real-world insights on selling AI to enterprises✅ Investors & AI Enthusiasts – Understand the next wave of AI-powered enterprise automationResources & Links:🔗 Follow Diamond Bishop on LinkedIn🔗 Datadog Bits.ai (Private Beta)📢 Enjoyed this episode? Don’t forget to subscribe, rate, and share! 🚀 This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.foundertofortune.org

Imagine walking into a digital store where the AI knows exactly what you want before you do. No more endless scrolling. No more generic recommendations. Just hyper-personalized shopping at lightning speed.In this electrifying episode of The Enterprise GTM Podcast, Vidya Raman sits down with two AI powerhouses:🔹 Sameer Singh, CTO of Spiffy, a startup rethinking AI-powered shopping assistants🔹 Anu Trivedi, Head of R&D at Flipkart, India’s largest e-commerce marketplaceTogether, they pull back the curtain on the AI revolution that’s already reshaping how we buy, sell, and engage with products online.What’s Inside?❓ Why are today’s product recommendations so outdated—and how is AI fixing it?🤯 Are personalized AI shopping assistants finally here? And are they actually good?🚀 How is Flipkart handling AI at a mind-blowing scale of 600M+ customers?🔥 Is AI-powered e-commerce too smart—or not smart enough?If you’re curious about how AI will change the way we shop forever, this is an episode you can’t afford to miss!Links mentioned in today’s episode:Sameer SinghSpiffy AIAnu TrivediFlipkart This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.foundertofortune.org

In this must-listen episode of the Enterprise GTM Podcast, I dive deep with two powerhouse AI experts:🎙 Manasi Vartak (Chief AI Architect at Cloudera)🎙 Shreya Shankar (PhD Candidate, UC Berkeley)We discuss the current landscape of GenAI in enterprises. We explore the challenges of productionizing AI applications, the importance of data privacy, and the evolving use cases within large organizations. Manasi shares insights from her experience at Cloudera, highlighting the slow adoption of GenAI in production and the prevalent use of internal applications. Shreya elaborates on her research at UC Berkeley, including how her work could transform data engineering.The conversation emphasizes the need for new tools and strategies to navigate the complexities of AI deployment and the significance of benchmarking in this evolving field. This conversation explores the evolving landscape of data engineering and the role of Generative AI (Gen.AI) in automating processes, simplifying data management, and enhancing user experience.The speakers discuss the importance of coding assistants, the need for new benchmarks in AI tools, and the critical role of user experience in designing AI applications. They emphasize the necessity of education and training to help users effectively leverage AI technologies in their workflows.Takeaways* The excitement about GenAI remains strong in enterprises.* Adoption of GenAI in production is still under 10%.* Internal use cases dominate the current landscape of GenAI applications.* The RAG pattern is a leading use case for enterprises.* Data privacy and security are major concerns for enterprises.* AI is becoming more democratized, allowing non-experts to build applications.* Productionizing AI requires significant effort and infrastructure.* Shreya's research focuses on optimizing database interactions with GenAI.* Accuracy in prompting is a complex and fuzzy concept.* Benchmarking in GenAI is challenging due to the lack of ground truth. The future of data engineering will involve more automation and less manual toil.* Gen.AI can simplify data management tasks significantly.* Natural language processing will make data access easier for non-technical users.* User experience is crucial for the success of AI applications.* AI tools should be designed for seamless human-AI collaboration.* Benchmarks for AI tools need to be redefined beyond traditional accuracy measures.* Education is key to helping users effectively utilize AI technologies.* Domain experts will benefit from tailored coding assistants in their specific environments.* The transition from creation to review in AI applications is essential for user engagement.* Accessibility of Gen.AI presents new opportunities for education and innovation.Chapters00:00 Introduction to AI Experts02:05 Current State of GenAI in Enterprises05:58 Use Cases and Adoption Challenges11:59 Parallels in AI Evolution16:02 Shreya's Research on GenAI and Databases22:41 The Future of Data Engineering and Automation24:11 Simplifying Data Management with Gen.AI27:20 The Role of Coding Assistants in Data Tasks30:47 Rethinking Benchmarks for AI Tools35:33 User Experience in AI Applications39:20 Designing for Human-AI Collaboration44:18 Education and Training for Effective AI UseLinks mentioned in today’s episode:Shreya ShankarShreya’s work DocETLManasi Vartak on Linkedin This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.foundertofortune.org

In today's episode, we sit down with Jerry Ting to delve into his experience of founding and scaling a startup in the world of AI-powered contract management. Jerry is the Founder and CEO of Evisort, a cutting-edge AI-powered contract management platform transforming how organizations manage, analyze, and automate their legal documents. Jerry's vision has been instrumental in establishing Evisort as an innovator at the intersection of law and technology.In our conversation, we discuss Jerry’s transition from sales to law, the early days of Evisort, and how he overcame skepticism to secure the company’s first clients. We also unpack the steps to identifying the right time to build sales and marketing teams, determining pricing, and the importance of a customer-first approach. Explore Evisort’s mission-driven innovation approach, the strategy of “land and expand,” and the advantages startups have over larger competitors in delivering user-focused solutions. Join us for a detailed look at the challenges and successes of building a transformative legal tech company from the ground up with Jerry Ting.Key Points From This Episode: * Introducing Jerry and his background in law and journey into entrepreneurship.* Jerry explains Evisort's product-led approach to its enterprise selling motion.* Why working with large enterprises is sometimes a curse for smaller companies.* Making the first Sales hire for Evisort and what he would do differently.* Discover how he determined Evisort's initial offerings and associated pricing.* How Evisort's mission to make peoples' lives easier catalyzed its growth. * How do you go from departmental sales to enterprise sales.* Jerry shares advice for budding founders of AI-native companies.Quotes:“[Evisort] really early on took a product-led approach in our enterprise selling motion.” — Jerry Ting [0:06:45]“My advice to the founders listening out there is that sometimes it is a curse to actually get big enterprises [interested] in the beginning.” — Jerry Ting [0:07:55]“If you really focus around the customer from a 360 [degree] company perspective, how you sell, how you support, how do you build your product, over time they become a great sounding board for the company strategy.” — Jerry Ting [0:18:18]Links Mentioned in Today’s Episode:Jerry Ting on LinkedInEvisortTim Zonca on LinkedInTim Zonca on XVidya Raman on LinkedInVidya Raman on X This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.foundertofortune.org

Bharathi Rajan, Vice President of Enterprise Data and Analytics at Swire Coca-Cola, shares invaluable insights for founders looking to sell to enterprises. She emphasizes knowing your customers and their KPIs for tailored solutions. Bharathi discusses the relevance of transferable KPIs across industries and the pivotal role of continuous engagement with clients. She also highlights the power of reference selling and the complexities of the competitive landscape, including decision-making factors like pricing and ROI. Her perspective on vendors as partners is a game changer.