The age of ubiquitous AI agents is here, bringing immense potential - and unprecedented risk.

Hosts Conor Bronsdon and Vikram Chatterji open the episode by discussing the urgent need for building trust and reliability into next-generation AI agents. Vikram unveils Galileo's free AI reliability platform for agents, featuring Luna 2 SLMs for real-time guardrails and its Insights Engine for automatic failure mode analysis. This platform enables cost-effective, low-latency production evaluations, significantly transforming debugging. Achieving trustworthy AI agents demands rigorous testing, continuous feedback, and robust guardrailing—complex challenges requiring powerful solutions from partners like Elastic.

Conor welcomes Philipp Krenn, Director of Developer Relations at Elastic, to discuss their collaboration in ensuring AI agent reliability, including how Elastic leverages Galileo's platform for evaluation. Philipp details Elastic's evolution from a search powerhouse to a key AI enabler, transforming data access with Retrieval-Augmented Generation (RAG) and new interaction modes. He discusses Elastic's investment in SLMs for efficient re-ranking and embeddings, emphasizing robust evaluation and observability for production. This collaborative effort aims to equip developers to build reliable, high-performing AI systems for every enterprise.

Chapters:

00:00 Introduction 

01:09 Galileo's AI Reliability Platform

01:43 Challenges in AI Agent Reliability

06:17 Insights Engine and Its Importance

11:00 Luna 2: Small Language Models

14:42 Custom Metrics and Agent Leaderboard

19:16 Galileo's Integrations and Partnerships

21:04 Philipp Krenn from Elastic

24:47 Optimizing LLM Responses 

25:41 Galileo and Elastic: A Powerful Partnership

28:20 Challenges in AI Production and Trust

30:02 Guardrails and Reliability in AI Systems

32:17 The Future of AI in Customer Interaction

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Connect with Philipp on LinkedIn

Learn more about Elastic

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⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Agent Leaderboard

The Internet of Agents is rapidly taking shape, necessitating innovative foundational standards, protocols, and evaluation methods for its success.

Recorded at Cisco's office in San Jose, we welcome Giovanna Carofiglio, Distinguished Engineer and Senior Director at Outshift by Cisco. As a leader of the AGNTCY Collective (an open-source initiative by Cisco, Galileo, LangChain, and many other participating companies), Giovanna outlines the vision for agents to collaborate seamlessly across the enterprise and the internet. She details the collective's pillars, from agent discovery and deployment using new agentic protocols like Slim, to ensuring a secure, low-latency communication transport layer. This groundbreaking work aims to make distributed agentic communication a reality.

The conversation then explores the critical role of observability and evaluation in building trustworthy agent applications, including defining an interoperable standard schema for communications. Giovanna highlights the complex challenges of scaling agents to thousands or millions, emphasizing the need for robust security (agent identity with OSF schema) and predictable agent behavior through extensive testing and characterization. She distinguishes between protocols like MCP (agent-to-tool) and A2A (agent-to-agent), advocating for open standards and underlying transport layers akin to TCP.

Chapters:

00:00 Introduction

01:00 Overview of Agent Interoperability

02:20 What is AGNTCY

03:45 Agent Discovery and Composition

04:38 Agent Protocols and Communication

05:45 Observability and Evaluation

07:00 Metrics and Standards for Agents

09:45 Challenges in Agent Evaluation

14:15 Low Latency and Active Evaluation

23:34 Synthetic Data and Ground Truth

25:07 Interoperable Agent Schema

26:37 MCP & A2A

30:17 Future of Agent Communication

32:03 Security and Agent Identity

34:37 Collaboration and Community Involvement

38:28 Conclusion

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AGNTCY Collective: agntcy.org

Connect with Giovanna on LinkedIn

Learn more about Outshift: outshift.cisco.com

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When AI makes creating content and code nearly free, how do you stand out? Differentiation now hinges on two things: unique taste and effective distribution.

This week, Bharat Vasan, founder & CEO at Intangible and a "recovering VC," explains why the AI landscape compelled him to return to founding. He sees AI sparking a new creative revolution, similar to the early internet, that makes it easier than ever to bring ideas to life. The conversation delivers essential advice for founders, revealing why relentless shipping is the ultimate clarifier for a business and why resilience, not just intelligence, is the key to survival.

Drawing from his experience on both sides of the venture table, Bharat breaks down the brutally competitive VC landscape and shares Intangible's mission: to simplify 3D creative tools with AI, finally bridging the gap between human vision and machine power. Listeners will gain insights on company building, brand strategy, and why customer obsession is the ultimate moat in the AI age.

Chapters:

00:00 Introduction

00:45 From Founder to VC and Back

03:17 Human Creativity in the Age of AI

07:50 The Role of Taste and Distribution

11:49 Building a Brand in the AI Era

16:17 The Venture Capital Landscape for AI Startups

20:11 Advice for Founders in the AI Boom

23:55 Incumbents vs. Startups

27:10 The New Generation of Innovators

29:19 Pirate Mentality in Startups

30:00 Building a Brand

36:28 Shipping and Resilience

41:49 Customer Obsession

46:58 The Vision for Intangible

51:52 Conclusion

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Connect with Bharat on LinkedIn.

Follow Bharat on X.

Learn more about Intangible at intangible.ai.

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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 Welcome

02:04 Defining the AI Agent Stack

03:49 Challenges in Building AI Agents

05:52 The Future of AI Agent Marketplaces

06:59 Infrastructure and Protocols

09:05 Interoperability and Flexibility

20:18 Governance and Security Concerns

24:12 Industry Adoption and Use Cases

25:57 Unlocking Faster Development with Success Metrics

28:40 Challenges in Managing Complex Systems

30:10 Introducing the Insights Engine

30:33 The Importance of Observability and Control

32:33 Democratizing Access with No-Code Tools

35:39 Ensuring Quality and Reliability in Production

41:08 Future of Agentic Systems and Industry Transformation

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Joao Moura: LinkedIn | X/Twitter

CrewAI: crewai.com | X/Twitter

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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 Event

00:30 Introduction to Anush Elangovan

01:38 The MI350 GPU Series Unveiled

04:57 CDNA4 Architecture Explained

07:00 The Future of AI Infrastructure

08:32 AMD's Developer Cloud and ROCm 7

11:50 Cultural Shift at AMD

14:48 Open Source and Community Contributions

18:35 Software Longevity and Ecosystem Strategy

22:19 AI Agents and Performance Gains

27:36 AI's Role in Solving Power Challenges

28:11 Thanking Anush

28:42 Introduction to Sharon Zhou

29:45 Sharon's Focus at AMD

30:39 Engaging Developers with AMD's AI Tools

31:24 Listening to the AI Community

33:56 Open Source and AI Development

45:04 Future of AI and Self-Improving Models

48:04 Final Thoughts and Farewell

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Anush Elangovan: LinkedIn

Sharon Zhou: LinkedIn

AMD Official Site: amd.com

AMD Developer Resources: AMD Developer Central

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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 Introduction

00:36 The Role of Gaming in AI Development

05:43 Personal Gaming Experiences

08:26 The Intersection of AI and Gaming

12:53 Importance of Data in Game Development

19:03 User Testing and QA in Gaming

25:49 Postmortems and Telemetry

27:21 Beta Testing and Data Preparedness

29:18 Traditional AI vs Generative AI

31:31 Challenges of Implementing AI in Games

35:57 Leveraging AI for Data Analytics

39:41 Automated QA and Reinforcement Learning

42:01 AI for Localization and Sentiment Analysis

44:21 Future of AI in Gaming

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Company Website: cohesity.com

LinkedIn: Gregory Statton

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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.

Chapters

00:00 Introduction

00:28 The Role of Gaming in AI Development

05:35 Personal Gaming Experiences

08:18 The Intersection of AI and Gaming

12:45 Importance of Data in Game Development

18:55 User Testing and QA in Gaming

25:41 Postmortems and Telemetry

27:13 Beta Testing and Data Preparedness

29:10 Traditional AI vs Generative AI

31:23 Challenges of Implementing AI in Games

35:49 Leveraging AI for Data Analytics

39:33 Automated QA and Reinforcement Learning

41:53 AI for Localization and Sentiment Analysis

44:13 Future of AI in Gaming

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Connect with Carly on LinkedIn

Subscribe to Carly's Substack: Good At Business

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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.

Chapters

00:00 Welcome and Introductions

01:05 Generative AI and Task Completion

02:13 Middleware and Orchestration Systems

03:17 Enterprise Adoption and Challenges

05:55 Multimodal AI and Future Plans

08:37 AI Reliability and Evaluation

11:08 Complex AI Systems and Developer Challenges

13:45 Galileo's Vision and Product Roadmap

18:59 Modern AI Evaluation Agents

20:10 Galileo's Powerful SDK and Tools

21:24 The Importance of Observability and Robust Testing

22:27 The Rise of Vibe Coding

24:48 Balancing Creativity and Reliability in AI

31:26 Enterprise Adoption of AI Systems

36:59 Challenges and Opportunities in Regulated Industries

42:10 Future of AI Reliability and Industry Impact

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Website: galileo.ai

Read: Galileo Optimizes Enterprise–Scale Agentic AI Stack with NVIDIA

Check out Galileo

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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.

Chapters

00:00 Introduction and Guest Welcome

01:55 Understanding and Acting on Data with AI

06:42 Amplitude's Unique Position in the Market

08:36 Differentiation and Competitive Advantage

09:58 Incorporating Customer Feedback

12:48 Evaluating AI Outcomes

17:21 Agentic AI and Future Prospects

21:38 Acquiring and Integrating AI Talent

28:44 Building a Culture of Innovation

37:21 Advice for Leaders and Individual Contributors

43:26 The Future of AI in the Workplace

45:38 Closing Thoughts

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LinkedIn: Wade Chambers

Website: amplitude.com

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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.

Chapters

00:00 Introduction and Guest Welcome

01:19 Founding of Poolside

02:56 Vision for AGI and Reinforcement Learning

05:36 Defining AGI and Its Implications

10:03 Training Models for Software Development

17:08 Scaling and Synthetic Data

20:12 Focus on High-Consequence Systems

26:17 Privacy and Security in AI Solutions

28:09 Earning Trust with Developers

31:08 Reinforcement Learning and Compute

34:29 The Vision for AI's Future

39:50 Will Developers Still Exist?

47:07 Poolside Cloud's Ambitions

49:37 Conclusion

Follow the hosts

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Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Follow⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

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Follow Today's Guest(s)

Website: poolside.ai

LinkedIn: Jason Warner

LinkedIn: Eiso Kant

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