Chain of Thought

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

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

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

Vikram Chatterji, CEO of Galileo, and Atindriyo Sanyal, CTO, dive into the transformative landscape of AI by 2025. They explore the shift from chatbots to intelligent task automation, often seen as a gold rush for middleware innovation. The duo discusses the challenges surrounding AI reliability and debugging complex systems while introducing their vision for a robust reliability platform. Insights on balancing creativity with the demand for performance highlight the rapid evolution in enterprise AI and the role of user-friendly technologies.

As AI redefines how products are built and customers are understood, what are the core strategies engineering leaders use to drive innovation and create lasting value?Join Conor Bronsdon as he welcomes Wade Chambers, Chief Engineering Officer at Amplitude, to explore these critical questions. Wade shares how Amplitude is leveraging AI to deepen customer understanding and enhance product experiences, transforming raw data into actionable insights across their platform. He also discusses their approach to navigating constant change while building an adaptable, high-performing engineering culture that thrives in the current AI landscape.The conversation explores Amplitude's strategy for building a sustainable AI advantage through proprietary data, deep domain expertise, and robust feedback loops, moving beyond superficial AI applications. Wade offers insights on fostering an AI-ready engineering culture through empowerment and clear alignment, alongside exploring the exciting potential of agentic AI to create proactive, intelligent copilots for product teams. He then details Amplitude’s successful approach to integrating specialized AI talent, drawing key lessons from their acquisition of Command AI.Chapters00:00 Introduction and Guest Welcome01:55 Understanding and Acting on Data with AI06:42 Amplitude's Unique Position in the Market08:36 Differentiation and Competitive Advantage09:58 Incorporating Customer Feedback12:48 Evaluating AI Outcomes17:21 Agentic AI and Future Prospects21:38 Acquiring and Integrating AI Talent28:44 Building a Culture of Innovation37:21 Advice for Leaders and Individual Contributors43:26 The Future of AI in the Workplace45:38 Closing ThoughtsFollow the hostsFollow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)LinkedIn: Wade ChambersWebsite: amplitude.comCheck out Galileo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Try Galileo⁠⁠⁠⁠⁠⁠⁠⁠Agent Leaderboard

Is the prevailing approach to Artificial General Intelligence (AGI) missing a crucial step – deep, focused specialization? For the first time since co-founding Poolside, CEO Jason Warner & CTO Eiso Kant reunite on a podcast articulating their distinct vision for AI's future with our host, Conor Bronsdon. Poolside has intentionally diverged from general-purpose models, developing highly specialized AI meticulously designed for the specific, complex task of coding, viewing it as a direct and robust pathway towards achieving AGI, and revolutionizing how software is created.Jason and Eiso dive deep into the core tenets of their strategy: an unwavering conviction in reinforcement learning through code execution feedback and the burgeoning power of synthetic data, which they believe will help expand the surface area of software by an astounding 1000x. They candidly discuss the "devil's trade" of data privacy, Poolside's commitment to enterprise-grade AI for high-consequence systems, and why true innovation requires moving beyond flashy demos to solve real-world, critical challenges. Looking towards the horizon, they also share their insights on the evolving role of software engineers, where human agency, taste, and judgment become paramount in a landscape augmented by AI "coworkers." They also explore the profound societal implications of their work and the AI industry more generally, touching upon the "event horizon" of intelligent systems and the immense responsibility that comes with being at the forefront of this technological wave. Chapters00:00 Introduction and Guest Welcome01:19 Founding of Poolside02:56 Vision for AGI and Reinforcement Learning05:36 Defining AGI and Its Implications10:03 Training Models for Software Development17:08 Scaling and Synthetic Data20:12 Focus on High-Consequence Systems26:17 Privacy and Security in AI Solutions28:09 Earning Trust with Developers31:08 Reinforcement Learning and Compute34:29 The Vision for AI's Future39:50 Will Developers Still Exist?47:07 Poolside Cloud's Ambitions49:37 ConclusionFollow the hostsFollow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)Website: poolside.aiLinkedIn: Jason WarnerLinkedIn: Eiso KantCheck out Galileo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Try Galileo⁠⁠⁠⁠⁠⁠Agent Leaderboard

The AI landscape often pulls us between the allure of cutting-edge models and the quiet necessity of foundational work—yet how do these extremes actually connect to deliver value?Join Conor Bronsdon as he welcomes Denny Lee, a self-proclaimed "data nerd" and Product Management Director, Developer Relations at Dataricks, to unpack this very spectrum, from AI's core infrastructure to its most advanced applications. Denny explains why robust logging, tracing, and data lineage are indispensable for credible AI evaluation and feedback, ultimately making AI systems more affordable, accessible, and impactful.The discussion ventures into strategies for democratizing AI, exploring the "GenAI ladder" from efficient inference and retrieval-augmented generation to deciding when to fine-tune or pre-train models. Denny also tackles the industry's pressing hardware bottlenecks, the critical role of open standards, and the imperative of navigating data privacy in an increasingly AI-driven world. Listen for grounded advice on moving beyond the hype and making practical, value-driven decisions in your AI journey.Chapters00:00 Introduction and Guest Welcome01:31 Diving into AI Foundations02:25 Importance of Logging and Tracing08:40 Challenges in Data Quality and Lineage14:49 Strategies for Cost-Effective AI19:52 Partnerships and Collaborative Opportunities22:10 Hardware Bottlenecks in AI24:56 China's Power and Networking Advantage25:26 Nvidia's Super Chip and Network Fabrics26:39 The Growing Demand for Power in AI29:26 Practical Advice for Data Governance35:47 Understanding Privacy in AI36:25 Differential Privacy and Its Challenges41:57 ConclusionFollow the hostsFollow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)Website: Databricks.comPodcast: Data Brew by Databricks (available on major podcast platforms)YouTube: @DatabricksLinkedIn: Denny LeeReadSemiAnalysis Blog: https://semianalysis.com/Check out Galileo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Try Galileo⁠⁠⁠⁠Agent Leaderboard

Agentic AI exploded in 2025, but how do businesses move beyond prototypes to deploy reliable, valuable agents at scale?Join host Conor Bronsdon and Lyzr AI CEO Siva Surendira as they discuss the complexities of building and managing AI agents for enterprises. Siva shares his journey creating Lyzr, focusing on making powerful agent frameworks accessible and trustworthy for enterprise developers. They discuss the critical hurdles businesses face, including productionization challenges, ensuring responsible AI, and bridging the gap between rapid innovation and the stringent requirements of regulated industries.Listen as Siva explains Lyzr's approach to embedding safety guardrails natively and learn about the nuances of multi-agent orchestration, including managerial, DAG, and hybrid flows. Siva also offers insights into the limitations of "vibe coding" for enterprise use cases and stresses the crucial role of robust evaluation (evals) and choosing the right models—from local open-source options to frontier LLMs. Explore the bottlenecks hindering adoption, like custom application integration and data readiness, and learn why Siva believes the biggest opportunity for agent companies may not lie in replacing SaaS platforms but rather in automating the mundane work currently performed by humans.Chapters00:22 Introduction and Guest Welcome00:52 Enterprise Agent Framework02:48 Building Enterprise-Friendly AI Frameworks04:56 Enterprise Concerns with Vibe Coding09:23 Safe and Responsible AI Implementation11:05 Multi-Agent Orchestration14:13 Challenges in Multi-Agent Systems14:22 Enterprise Integration Bottlenecks17:37 The Role of Low-Code and No-Code Solutions19:55 Inter-Agent Communication Standards21:49 Future of AI Agents in Enterprises29:37 Evaluating AI Agents36:34 Conclusion and Final ThoughtsFollow the hostsFollow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)Website: lyzr.aiLinkedIn: Siva SurendiraCheck out Galileo⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Try Galileo⁠⁠Agent Leaderboard

Olga Beregovaya, VP of AI at Smartling, dives into the captivating world of AI and translation. She discusses how AI has evolved from rule-based systems to sophisticated models that tackle language barriers. Key challenges like English-centric biases and the unpredictability of AI outputs are explored. Olga highlights opportunities in specialized language models and innovative workflows that enhance translator productivity. The potential for multilingual multimodality raises exciting possibilities for the future of global communication and more nuanced translations.

Rodrigo Coutinho, Co-founder and AI Product Manager at OutSystems, dives into the world of AI-driven application development. He discusses the groundbreaking potential of transforming requirements into full enterprise apps within minutes. Rodrigo highlights challenges in managing AI-generated code and the evolution of a developer's role from focusing on syntax to strategy. The use of low-code platforms like OutSystems Mentor empowers developers while maintaining the necessity for human creativity and effective validation, paving the way for a faster and innovative development cycle.