Barrchives

Barrchives

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Barrchives episodes

  • Why Your Customer Support Tools Won't Cut It in the AI Era with Jesse Zhang, CEO of Decagon

    This episode consists of the following chapters:


    00:00 - Introduction to Jesse Zhang and Decagon


    02:33 - Why customer support emerged as a clear use case for AI


    05:00 - The importance of discovery and understanding customer value


    08:20 - The Decagon product architecture: core AI agent, routing, and human assistance


    11:01 - How enterprise logic is integrated into the AI agent


    15:45 - Shared frameworks across different customers and industries


    17:12 - How AI agents are changing organizational planning


    19:59 - Automatically identifying knowledge gaps to improve resolution rates


    22:57 - Handling routing across different modalities (text and voice)


    26:09 - The continued importance of humans in customer support


    30:17 - The evolving role of human agents: supervising, QA, and logic building


    36:57 - Value-based pricing tied to the work AI performs


    39:17 - How sophisticated buyers evaluate AI customer support solutions


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    Spotify: https://open.spotify.com/show/37O8Pb0LgqpqTXo2GZiPXf


    Apple: https://podcasts.apple.com/us/podcast/barrchives/id1774292613


    Twitter: https://x.com/barrnanas


    LinkedIn: https://www.linkedin.com/in/barryaron/

    46 min
  • How To Build AI That Creates Music, with Suno CEO, Mikey Shulman

    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.

    49 min
  • How Hex Builds AI For Data Scientists, with Barry McCardel

    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.

    54 min
  • Solving Technical Problems To Help AI Teams Move Up The Stack, with Erik Bernhardsson, CEO of Modal

    When it comes to building cutting-edge technology companies, Erik Bernhardsson's journey with Modal exemplifies the mix of passion, technical ingenuity, and adaptability required to succeed. From tackling infrastructure challenges in the data and AI space to navigating the nuanced dynamics of scaling a business, Modal’s story provides a masterclass in modern tech entrepreneurship.

    48 min
  • From Hidden Work to AI-powered Productivity, with Jennifer Smith, CEO of Scribe

    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.

    44 min
  • Building AI That Understands Our World Like We Do, with Amit Jain, Co-Founder and CEO of Luma AI

    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.

    46 min
  • Building Deep Tech Beyond the SaaS Playbook with Naveen Rao, VP of AI at Databricks

    Naveen Rao discovered artificial intelligence through science fiction in middle school, devouring the works of Asimov while his peers in Kentucky were doing whatever kids in Kentucky normally did. Growing up in a family of doctors, he chose a less conventional path, following his early interests in programming and circuit building.

    After establishing himself as an engineer, he stepped away to pursue a neuroscience PhD at Brown, finishing in record time. This combination of engineering expertise and biological understanding shaped his approach to AI hardware development at his companies Nervana (acquired by Intel) and MosaicML (acquired by Databricks).

    In this conversation, the VP of AI at Databricks breaks down what's actually needed for meaningful progress in machine reasoning (hint: it's not just bigger models), and why deep tech development needs a different playbook than what we're used to.

    53 min
  • Building Tomorrow’s Data Ecosystems for AI and Analytics with dbt

    Tristan Handy’s move to develop dbt Labs meant stepping away from steady consulting revenue to build a product. With support from an open-source community and interest from enterprise clients, dbt quickly found a growing user base. By 2019, it had become a go-to tool for data professionals looking to streamline workflows and prepare data for AI. Today, dbt Labs serves over 50,000 teams globally, with dbt Cloud helping organizations tackle modern analytics and AI needs through data transformation, observability, and orchestration.

    In this episode of Barrchives, Tristan discusses how dbt is adapting to support the evolving demands of today’s data ecosystems. He shares insights on how data teams can move beyond manual, repetitive tasks to create environments where data becomes a valuable, collaborative asset. From AI’s potential as an analytical “thought partner” to the emerging standards reshaping data access, Tristan explores the shifts making data infrastructure more adaptable and effective.

    52 min

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