Barrchives

Vanta helped create the automated security and compliance category—and now, they’re redefining it with AI.In this episode, Christina Cacioppo (CEO & Co-Founder) and Iccha Sethi (VP of Engineering) join Barr Yaron to go deep on how AI is transforming the way Vanta builds products, evaluates models, and helps companies earn and demonstrate trust.They cover:- Why compliance is the perfect playground for AI- How Vanta balances reliability, explainability, and scale- What it takes to build golden datasets in high-stakes domains- The real-world AI infrastructure behind Vanta AIIf you care about real AI product development—not just hype—this is a masterclass in doing it right.🔔 Subscribe for more deep dives with leading AI builders and thinkers.This episode is broken down into the following chapters:00:00 – Intro01:06 – Christina’s early entrepreneurial roots (Beanie Babies & all)02:51 – From venture to founder: why Christina started Vanta04:00 – What Vanta actually does05:32 – Iccha on why she joined as VP of Engineering07:09 – When Vanta started leaning into AI08:33 – AI’s growing role in Vanta’s product roadmap09:52 – How AI powers questionnaire automation12:25 – Using LLMs to map policy docs to cloud configs13:27 – Building trust: human-in-the-loop and explainability16:03 – Vanta’s evaluation system for AI features18:17 – How golden datasets are constructed (and maintained)20:59 – Feedback loops: online eval from user behavior22:43 – How model feedback informs product updates23:38 – What Vanta wants from foundation models (but isn’t getting yet)24:32 – Retrieval: how Vanta processes customer documents27:13 – The hardest technical challenges in AI integration29:41 – Internal adoption: how non-technical teams are using AI too31:52 – Vanta’s centralized AI team & how other teams plug in33:27 – Internal education: building AI intuition org-wide34:31 – From prototype to production: experimentation culture36:41 – Customer sentiment around AI in compliance workflows38:22 – Enterprise buyers & the AI “kill switch”39:06 – Personalized experiences as the future of trust40:21 – How enterprises are approaching AI risk assessments41:50 – What excites Iccha and Christina about the future of AI at VantaSubscribe to the Barrchives newsletter: https://www.barrchives.comSpotify: https://open.spotify.com/show/37O8Pb0LgqpqTXo2GZiPXfApple: https://podcasts.apple.com/us/podcast/barrchives/id1774292613Twitter: https://x.com/barrnanasLinkedIn: https://www.linkedin.com/in/barryaron/

Karan Goel, Co-founder and CEO of Cartesia, dives into the future of voice AI and the groundbreaking use of state space models (SSMs) for audio applications. He details his transition from academia at CMU and Stanford to entrepreneurship, emphasizing the innovative efficiency of SSMs over traditional models. Karan also reveals how Cartesia is developing Sonic, an ultra-low latency text-to-speech model, and elaborates on the importance of rapid execution in voice AI, all while navigating the startup landscape.

Kashish Gupta, Co-founder and Co-CEO of Hightouch, discusses the revolutionary impact of AI on marketing. He delves into the rise of Composable CDPs, illustrating how they empower marketers with data democratization. Gupta reveals how reinforcement learning agents optimize campaigns through tailored reward systems and highlights the technical challenges faced in building these AI models. He emphasizes the balance between AI efficiency and the creative input needed from marketers to truly engage customers in an increasingly automated landscape.

This episode consists of the following chapters: 00:00 - Introduction to Jesse Zhang and Decagon02:33 - Why customer support emerged as a clear use case for AI05:00 - The importance of discovery and understanding customer value08:20 - The Decagon product architecture: core AI agent, routing, and human assistance11:01 - How enterprise logic is integrated into the AI agent15:45 - Shared frameworks across different customers and industries17:12 - How AI agents are changing organizational planning19:59 - Automatically identifying knowledge gaps to improve resolution rates22:57 - Handling routing across different modalities (text and voice)26:09 - The continued importance of humans in customer support30:17 - The evolving role of human agents: supervising, QA, and logic building36:57 - Value-based pricing tied to the work AI performs39:17 - How sophisticated buyers evaluate AI customer support solutionsSubscribe to the Barrchives newsletter: www.barrchives.comSpotify: https://open.spotify.com/show/37O8Pb0LgqpqTXo2GZiPXfApple: https://podcasts.apple.com/us/podcast/barrchives/id1774292613Twitter: https://x.com/barrnanasLinkedIn: https://www.linkedin.com/in/barryaron/

Regal co-founders Alex Levin and Rebecca Greene see a future where AI doesn't just assist human agents in contact centers - it replaces them entirely at the front lines. In this episode of Barrchives, we discussed how they're building voice AI technology, the unique challenges of working with audio models, and what the future of customer service looks like.

Most of what you hear about AI right now is in text, but Mikey Shulman (co-founder and CEO of Suno) would tell you that audio is a much more interesting medium to work with. How do you use AI to generate music? What makes audio data uniquely difficult to parse? And how do you build audio models that cater to unique, subjective human preferences on music? Suno is building a future where anyone can make great music. In this episode of Barrchives, I sat down with Mikey (who, like his co-founder, is a musician) to talk about how they do what they do, from why they chose a transformer-based architecture to how they test new models when outputs are so subjective.

AI and data teams in a sense, kind of, do the same thing: make decisions based on data. So how do you build AI that *helps* data teams do their best work? Hex was one of the first companies in their space to embrace language models and build code generation features into their data workspace. In this episode of Barrchives, I went deep with Hex’s co-founder and CEO, Barry McCardel, about Hex’s journey towards becoming an AI company.

Erik Bernhardsson, CEO of Modal and former leader at Spotify, joins the conversation to discuss his entrepreneurial journey and the challenges of building infrastructure for AI teams. He shares insights into enhancing developer experiences and the importance of user-centric design. Erik dives into the impact of generative AI on customer attraction and the complexities of managing resources like GPUs. The discussion also touches on the need for low-latency solutions in AI applications and how well-positioned companies can navigate market growth.

Building a company isn’t for the faint of heart. It’s messy, nonlinear, and full of surprises. Jennifer Smith, CEO of Scribe, knows this better than most. In a recent episode of Barrchives, she shared the hard-earned lessons that helped her navigate the twists and turns of finding product-market fit. From trusting her instincts when others doubted her to rethinking how humans and AI can work together, Jennifer’s journey offers powerful insights for anyone trying to build something transformative.

From his early work in physics and mathematical simulation to leading Vision Pro development at Apple, Amit Jain has consistently pushed the boundaries of how computers process and understand our world. Now as the founder and CEO of Luma AI, he's tackling an even bigger challenge: building what he calls a "universal imagination engine." In this episode of Barrchives, Amit shares his perspective on why unified AI models outperform specialized ones, how visual data transforms AI reasoning, and what it takes to build infrastructure capable of training on millions of videos. But underlying these technical insights is a broader vision about technology's role in human progress.