Unlocking AI agents for knowledge work automation and scaling intelligent, multi-agent systems within enterprises fundamentally requires measurability, reliability, and trust.João Moura, founder & CEO of CrewAI, joins Galileo’s Conor Bronsdon and Vikram Chatterji to unpack and define the emerging AI agent stack. They explore how enterprises are moving beyond initial curiosity to tackle critical questions around provisioning, authentication, and measurement for hundreds or thousands of agents in production. The discussion highlights a crucial "gold rush" among middleware providers, all racing to standardize the orchestration and frameworks needed for seamless agent deployment and interoperability. This new era demands a re-evaluation of everything from cloud choices to communication protocols as agents reshape the market.João and Vikram then dive into the complexities of building for non-deterministic multi-agent systems, emphasizing the challenges of increased failure modes and the need for rigorous testing beyond traditional software. They detail how CrewAI is democratizing agent access with a focus on orchestration, while Galileo provides the essential reliability platform, offering advanced evaluation, observability, and automated feedback loops. From specific use cases in financial services to the re-emergence of core data science principles, discover how companies are building trustworthy, high-quality AI products and prepare for the coming agent marketplace. Chapters:00:00 Introduction and Guest Welcome02:04 Defining the AI Agent Stack03:49 Challenges in Building AI Agents05:52 The Future of AI Agent Marketplaces06:59 Infrastructure and Protocols09:05 Interoperability and Flexibility20:18 Governance and Security Concerns24:12 Industry Adoption and Use Cases25:57 Unlocking Faster Development with Success Metrics28:40 Challenges in Managing Complex Systems30:10 Introducing the Insights Engine30:33 The Importance of Observability and Control32:33 Democratizing Access with No-Code Tools35:39 Ensuring Quality and Reliability in Production41:08 Future of Agentic Systems and Industry TransformationFollow the hostsFollow AtinFollow ConorFollow VikramFollow YashFollow Today's Guest(s)Joao Moura: LinkedIn | X/TwitterCrewAI: crewai.com | X/Twitter Check out GalileoTry GalileoAgent Leaderboard
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49:53
AMD's Vision for an Open Ecosystem | Anush Elangovan & Sharon Zhou
How is an open ecosystem powering the next generation of AI for developers and leaders?Broadcasting live from the heart of the action at AMD's Advancing AI 2025, Chain of Thought host Conor Bronsdon welcomes AMD’s Anush Elangovan, VP of AI Software, and Sharon Zhou, VP of AI. They unpack AMD's groundbreaking transformation from a hardware giant to a leader in full-stack AI, committed to an open ecosystem. Discover how new MI350 GPUs deliver mind-blowing performance with advanced data types and why ROCm 7 and AMD Developer Cloud offer Day Zero support for frontier models.Then Conor welcomes Sharon Zhou, VP of AI at AMD, to discuss making AMD's powerful software stack truly accessible and how to drive developer curiosity. Sharon explains strategies for creating a "happy path" for community contributions, fostering engagement through teaching, and listening to developers at every stage. She shares her predictions for the future, including the rise of self-improving AI, the critical role of heterogeneous compute, and the potential of "vibes based feedback" to guide models. This vision for democratizing access to high-performance AI, driven by a deep understanding of the developer journey, promises to unlock the next generation of applications.Chapters:00:00 Live from AMD's Advancing AI 2025 Event00:30 Introduction to Anush Elangovan01:38 The MI350 GPU Series Unveiled04:57 CDNA4 Architecture Explained07:00 The Future of AI Infrastructure08:32 AMD's Developer Cloud and ROCm 711:50 Cultural Shift at AMD14:48 Open Source and Community Contributions18:35 Software Longevity and Ecosystem Strategy22:19 AI Agents and Performance Gains27:36 AI's Role in Solving Power Challenges28:11 Thanking Anush28:42 Introduction to Sharon Zhou29:45 Sharon's Focus at AMD30:39 Engaging Developers with AMD's AI Tools31:24 Listening to the AI Community33:56 Open Source and AI Development45:04 Future of AI and Self-Improving Models48:04 Final Thoughts and FarewellFollow the hostsFollow AtinFollow ConorFollow VikramFollow YashFollow Today's Guest(s)Anush Elangovan: LinkedInSharon Zhou: LinkedInAMD Official Site: amd.comAMD Developer Resources: AMD Developer CentralCheck out GalileoTry GalileoAgent Leaderboard
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49:16
Your Key to AI Success is Hiding in Plain Sight | Cohesity's Greg Statton
What if the most valuable data in your enterprise—the key to your AI future—is sitting dormant in your backups, treated like an insurance policy you hope to never use?Join Conor Bronsdon with Greg Statton, VP of AI Solutions at Cohesity, for an inside look at how they are turning this passive data into an active asset to power generative AI applications. Greg details Cohesity’s evolution from an infinitely scalable file system built for backups into a data intelligence powerhouse, managing hundreds of exabytes of enterprise data globally. He recounts how early successes in using this data for security and anomaly detection paved the way for more advanced AI applications. This foundational work was crucial in preparing Cohesity to meet the new demands of generative AI.Greg offers a candid look at the real-world challenges enterprises face, arguing that establishing data hygiene and a cross-functional governance model is the most critical step before building reliable AI applications. He shares the compelling story of how Cohesity's focus on generative AI was sparked by an internal RAG experiment he built to solve a "semantic divide" in team communication, which quickly grew into a company-wide initiative. He also provides essential advice for data professionals, emphasizing the need to focus on solving core business problems.Chapters:00:00 Introduction00:36 The Role of Gaming in AI Development05:43 Personal Gaming Experiences08:26 The Intersection of AI and Gaming12:53 Importance of Data in Game Development19:03 User Testing and QA in Gaming25:49 Postmortems and Telemetry27:21 Beta Testing and Data Preparedness29:18 Traditional AI vs Generative AI31:31 Challenges of Implementing AI in Games35:57 Leveraging AI for Data Analytics39:41 Automated QA and Reinforcement Learning42:01 AI for Localization and Sentiment Analysis44:21 Future of AI in GamingFollow the hostsFollow AtinFollow ConorFollow VikramFollow YashFollow Today's Guest(s)Company Website: cohesity.comLinkedIn: Gregory StattonCheck out GalileoTry GalileoAgent Leaderboard
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45:48
Why Gamers Paved the Way for AI | Databricks' Carly Taylor
What if the pixels and polygons of your favorite video games were the secret architects of today's AI revolution?Carly Taylor, Field CTO for Gaming at Databricks and founder of ggAI, joins host Conor Bronsdon to illuminate the direct line from video game innovation to the current AI landscape. She explains how the gaming industry's relentless pursuit of better graphics and performance not only drove pivotal GPU advancements and cost reductions, but also fundamentally shaped our popular understanding of artificial intelligence by popularizing the very term "AI" through decades of in-game experiences. Carly shares her personal journey, from a childhood passion for games like Rollercoaster Tycoon ignited while playing with her mom, to becoming a data scientist for Call of Duty. The discussion then confronts a long-standing tension in game development: how the critical need to ship titles often relegates vital game data to a secondary concern, a dynamic Carly explains is now being reshaped by AI. She details the inherent challenges game studios face in capturing and leveraging telemetry, from disparate development processes to the lengthy pipeline required for updates. Carly illuminates how modern AI, particularly generative AI, presents a massive opportunity for studios to finally unlock their vast data troves for everything from self-service analytics and community insight generation to revolutionizing QA processes. This pivotal intersection of evolving game data practices and new AI capabilities is poised to redefine how games are made, understood, and ultimately experienced.Chapters00:00 Introduction00:28 The Role of Gaming in AI Development05:35 Personal Gaming Experiences08:18 The Intersection of AI and Gaming12:45 Importance of Data in Game Development18:55 User Testing and QA in Gaming25:41 Postmortems and Telemetry27:13 Beta Testing and Data Preparedness29:10 Traditional AI vs Generative AI31:23 Challenges of Implementing AI in Games35:49 Leveraging AI for Data Analytics39:33 Automated QA and Reinforcement Learning41:53 AI for Localization and Sentiment Analysis44:13 Future of AI in GamingFollow the hostsFollow AtinFollow ConorFollow VikramFollow YashFollow Today's Guest(s)Connect with Carly on LinkedInSubscribe to Carly's Substack: Good At BusinessCheck out GalileoTry GalileoAgent Leaderboard
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49:10
The 2025 AI Shift: From Chat to Task Completion & Reliable Action | Galileo Founders
AI in 2025 promises intelligent action, not just smarter chat. But are enterprises prepared for the agentic shift and the complex reliability hurdles it brings?Join Conor Bronsdon on Chain of Thought with fellow co-hosts and Galileo co-founders, Vikram Chatterji (CEO) and Atindriyo Sanyal (CTO), as they explore this pivotal transformation. They discuss how generative AI is evolving from a simple tool into a powerful engine for enterprise task automation, a significant advance driving the pursuit of substantial ROI. This shift is also fueling what Vikram observes as a "gold rush" for middleware and frameworks, alongside healthy skepticism about making widespread agentic task completion a practical reality.As these AI systems grow into highly complex, compound structures—often incorporating multimodal inputs and multi-agent designs—Vikram and Atin address the critical challenges around debugging, achieving reliability, and solving the profound measurement problem. They share Galileo's vision for an AI reliability platform designed to tame these intricate systems through robust guardrailing, advanced metric engines like Luna, and actionable developer insights. Tune in to understand how the industry is moving beyond point-in-time evaluations to continuous AI reliability, crucial for building trustworthy, high-performing AI applications at scale.Chapters00:00 Welcome and Introductions01:05 Generative AI and Task Completion02:13 Middleware and Orchestration Systems03:17 Enterprise Adoption and Challenges05:55 Multimodal AI and Future Plans08:37 AI Reliability and Evaluation11:08 Complex AI Systems and Developer Challenges13:45 Galileo's Vision and Product Roadmap18:59 Modern AI Evaluation Agents20:10 Galileo's Powerful SDK and Tools21:24 The Importance of Observability and Robust Testing22:27 The Rise of Vibe Coding24:48 Balancing Creativity and Reliability in AI31:26 Enterprise Adoption of AI Systems36:59 Challenges and Opportunities in Regulated Industries42:10 Future of AI Reliability and Industry ImpactFollow the hostsFollow AtinFollow ConorFollow VikramFollow YashFollow Today's Guest(s)Website: galileo.aiRead: Galileo Optimizes Enterprise–Scale Agentic AI Stack with NVIDIACheck out GalileoTry GalileoAgent Leaderboard
Introducing Chain of Thought, the podcast for software engineers and leaders that demystifies artificial intelligence.
Join us each week as we tell the stories of the people building the AI revolution, unravel actionable strategies and share practical techniques for building effective GenerativeAI applications.
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