Chain of Thought

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.

Charity Majors, co-founder and CTO of Honeycomb, shares her sharp insights on the challenges AI brings to engineering teams. She argues that while generative AI is a hot topic, it won't build effective teams or replace the essential roles of junior engineers. The conversation dives into hiring practices, emphasizing the importance of potential over experience. Charity also highlights the complexities of system ownership and the risks of cognitive decay from over-relying on AI, stressing the need for deep understanding among engineers.

In this engaging talk, Maryam Ashoori, Head of Product for watsonx AI at IBM, shares her expertise from over 15 years in enterprise AI. She discusses how watsonx simplifies the AI stack and automates processes, enabling businesses to scale AI operations cost-effectively. Maryam highlights the balance of using open-source and commercial models while addressing the challenges of implementing AI agents, emphasizing the importance of data management and governance in regulated industries.

What if everyone in your organization had equal information at all times? Would meetings even exist? This week, we dive into the concept of information symmetry with Manoj Agarwal, co-founder and president of DevRev. Manoj, along with hosts Conor Bronsdon and Yash Sheth, explores how DevRev is connecting data, personalizing schemas, and automating complex tasks, offering a glimpse into the next generation of AI-driven workflows. This is revolutionizing enterprise data and decision-making by breaking down the silos that create information asymmetry.Learn how AI is reshaping business outcomes and collaboration, moving us closer to a world where everyone has the information they need.Chapters:00:00 Welcome to Chain of Thought00:57 Information Symmetry in Enterprises02:03 Challenges of Decision Making03:41 Recency Bias and Product Management04:58 Data Silos and Information Waste05:23 Structured vs. Unstructured Data06:04 Collaboration and Data Retrieval Issues08:17 DevRev's Approach to AI and Data Integration09:23 Building a Business-Centric Knowledge Graph10:00 Conversational AI and Automation12:57 Agentic Interactions and Skills Programming20:05 Multi-Agent Systems and Future Vision21:25 Challenges in Multi-Agent Communication25:10 Data Cleanliness and Governance28:14 Trust and Reliability in AI Systems36:58 Conclusion and Future OutlookFollow the hostsFollow⁠⁠⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)devrev.aiDevRev UniversityLinkedIn Manoj AgarwalCheck out Galileo⁠⁠⁠⁠⁠⁠⁠Try Galileo⁠⁠

Is the agentic AI bubble about to burst? Kelly Vaughn, Director of Engineering at Spot AI, questions whether the agent craze is overpromising potential and leading startups down a path of unsustainable expectations.Never one to shy away from a hot take, Kelly joins host Conor Bronsdon for a pragmatic look at AI, discussing the differences between building AI-enabled and traditional software, why replacing humans with AI teams will backfire (looking at you customer service), and the proliferation of AI tools.Kelly also shares insights on constructing AI teams, navigating data governance, and building user trust while avoiding common startup pitfalls. Chapters:00:00 Introduction and Guest Welcome01:13 Is Agentic AI a Bubble?02:40 Startup Challenges and Market Noise11:02 Building AI Products vs. Traditional Software17:31 Ethical Implications and Governance19:48 Constructing AI-Enabled Teams22:07 AI Tooling and Productivity26:00 Questioning Productivity Claims32:28 Conclusion and Final ThoughtsFollow the hostsFollow⁠⁠⁠⁠⁠⁠⁠ Atin⁠⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠⁠⁠ Conor⁠⁠⁠⁠⁠⁠Follow⁠⁠⁠⁠⁠ Vikram⁠⁠⁠⁠⁠Follow⁠⁠⁠ ⁠⁠⁠⁠Yash⁠⁠⁠⁠⁠⁠⁠Follow Today's Guest(s)Kelly’s Newsletter The Modern LeaderLinkedIn Kelly VaughnCheck out Galileo⁠⁠⁠⁠⁠⁠Try Galileo⁠⁠