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 AI

And 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.

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

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 transformations

If you’re building for the enterprise, selling to CISOs, or investing in cybersecurity, this is a blueprint you can’t afford to miss.

In this must-listen episode of The Enterprise GTM Podcast, Pavi Ramamurthy, Global CIO and CSO of Blackhawk Network, shares a candid and deeply insightful look into the world of enterprise security, tech innovation, and risk management. From managing massive fraud prevention systems behind the gift cards you see at Target, to navigating startup pitches and the realities of AI adoption—this is a masterclass in modern IT and security leadership.

💡 What You’ll Learn:

• How Pavi balances business priorities vs. security risks

• Why startup founders need to drop the pitch and start a real conversation

• The surprising cost of switching vendors—even if the tech is “10x better”

• Why shadow AI isn’t so different from shadow IT—and how to manage both

• The power of CISO communities and peer recommendations

• Why “best-of-suite” often wins over “best-of-breed” in today’s enterprise deals

• What makes a new security vendor stand out—or get silently passed over

• The magic wand wish that Pavi has from startups

💬 Memorable Quote:

“I ask one question before investing in any solution: What’s the cost of not doing this?”

“Know your CISO!”

👀 Who Should Listen:

• Founders and startups pitching to the enterprise market

• Security and IT professionals navigating risk and innovation

• Anyone curious about how real enterprise decisions get made

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 Learning

2️⃣ Founding Augmend: AI for DevOps Knowledge Sharing

3️⃣ The biggest challenges for Dev Tool startups

4️⃣ Bits.ai: The AI Assistant for DevOps & Security

5️⃣ Lessons in building with Gen AI & GTM Insights

Who 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 automation

Resources & Links:

🔗 Follow Diamond Bishop on LinkedIn

🔗 Datadog Bits.ai (Private Beta)

📢 Enjoyed this episode? Don’t forget to subscribe, rate, and share! 🚀

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 marketplace

Together, 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 Singh

Spiffy AI

Anu Trivedi

Flipkart

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.

Chapters

00:00 Introduction to AI Experts

02:05 Current State of GenAI in Enterprises

05:58 Use Cases and Adoption Challenges

11:59 Parallels in AI Evolution

16:02 Shreya's Research on GenAI and Databases

22:41 The Future of Data Engineering and Automation

24:11 Simplifying Data Management with Gen.AI

27:20 The Role of Coding Assistants in Data Tasks

30:47 Rethinking Benchmarks for AI Tools

35:33 User Experience in AI Applications

39:20 Designing for Human-AI Collaboration

44:18 Education and Training for Effective AI Use

Links mentioned in today’s episode:

Shreya Shankar

Shreya’s work DocETL

Manasi Vartak on Linkedin

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 LinkedIn

Evisort

Tim Zonca on LinkedIn

Tim Zonca on X

Vidya Raman on LinkedIn

Vidya Raman on X

Welcome back to another episode of The Enterprise GTM Podcast. Today we are joined by the Vice President of Enterprise Data and Analytics at Swire Coca-Cola, Bharathi Rajan.

In this episode, Bharathi delves into crucial aspects of GTM that founders should pay attention to:

🔹 Know Your Customers and Their KPIs: Understanding what drives your customers is key to offering solutions that truly meet their needs.

🔹 Transferable KPIs Across Industries: Bharathi shares how fundamental business problems remain consistent across sectors like healthcare, finance, and manufacturing. Founders should leverage this when pitching horizontal products to different industry verticals.

We also dive deep into her recent product buying experience:

🔸 Continuous Engagement: Stay in your customers' inboxes and minds. Be present when you become highly relevant to them.

🔸 Power of Reference Selling: Never underestimate the influence of your current customers. Their endorsements can be game-changers.

🔸 Competitive Landscape: A good market always has competition. Learn how Bharathi's team evaluates competitors—not just on price.

🔸 Pricing, TCO, and ROI: Understand how enterprises weigh the decision between replacing existing products and adopting new ones.

One standout takeaway: Bharathi refers to the vendor they chose as a "partner." This reinforces a recurring theme we've heard throughout our podcast series, especially in conversations with Leslie Venetz. Customers today are seeking partners, not just products or platforms.

👉 If you're keen to gain invaluable insights from the other side of the table, this episode is a must-listen!

Quotes:

“Data is so foundational for us to do anything in the AI – space.” — Bharathi Rajan [0:04:46]

“For me, our customers are everyone across the organization.” — Bharathi Rajan [0:08:00]

“Data is data at the end of the day.” — Bharathi Rajan [0:08:40]

“Deeply understanding your customer’s business will make a big difference even in your first dialog with a prospect.”— Bharathi Rajan [0:14:00]

Links Mentioned in Today’s Episode:

Bharathi Rajan on LinkedIn

Swire Coca-ColaTim Zonca on LinkedIn

Tim Zonca on X

Vidya Raman on LinkedIn

Vidya Raman on X

Founder-led sales are common in early-stage startups. But, they could be much more effective with a deeper understanding of sales fundamentals. Joining us today is Leslie Venetz, founder of The Sales-Led GTM Agency to discuss how founders can level up their skills and transform their sales. Drawing on her extensive history in B2B sales, which includes over 250,000 cold calls, Leslie covers everything founders need to know, from earning the right to your prospect’s attention to efficiently managing your time during the sales process. She shares her top tips on crafting concise, value-driven emails, how to use AI in sales without over-relying on it, and how to strategically time your demos. Leslie also shares her unique perspective on objections, including how to figure out which objections are worth addressing, and why you should always lead with curiosity.

Key Points From This Episode: 

* Some background on Leslie Venetz and her extensive background in sales.

* Improving founder-led sales, especially in early-stage startups.

* The key to developing active listening skills and why it is essential in sales.

* Cold emails: best practices and common mistakes.

* Key components of highly relevant messaging and how to audit your emails.

* What your initial email outreach should look like.

* Why you need to earn the right to write longer emails.

* Leslie’s advice on how to use AI in sales – and how not to use it.

* The importance of personalized outreach in the age of AI.

* How to strategically time your product demos in a prospective customer call.

* Recognizing different types of objections and how to address them.

* Utilizing events as part of a multi-channel marketing approach.

* Leslie answers our rapid-fire questions on AI, cold-calling, and more!

Quotes:

“Founder-led sales, which is usually the norm for early-stage startups, can be so much more effective if only founders could better understand some of the foundational aspects of sales.” — @veenormous [0:04:17]

“It is your responsibility to earn the right to your prospect's time” — @LeslieVenetz [0:11:41]

“We want to do everything that we can to reduce the cognitive load – and make it easy for them to scan and digest that email.” — @LeslieVenetz [0:15:16]

“Especially for early-stage founders. You all are busy. – You do not have the time to spend an hour sending an email to a prospect that doesn't actually want you to email them.” — @LeslieVenetz [0:34:05]

Links Mentioned in Today’s Episode:

Leslie Venetz

Leslie Venetz on LinkedInJill Konrath

Snap Selling

Tim Zonca on LinkedIn

Tim Zonca on X

Vidya Raman on LinkedIn

Vidya Raman on X