AI's Two Extremes – Foundations & The Frontier | Databricks’ Denny Lee
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
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43:30
Why Enterprises Need a Different Approach to AI Agents | Lyzr’s Siva Surendira
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
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38:48
Will AI Erase All Language Barriers? | Smartling's Olga Beregovaya
Are we on the verge of removing all language barriers with AI?Olga Beregovaya, VP of AI at Smartling, joins host Conor Bronsdon to tackle this question, discussing the evolution from rule-based NLP to today's powerful LLMs. Together, they confront the persistent challenges that stand in the way, like the English-centric nature of AI, domain-specific inaccuracies, and the unpredictability of model hallucinations. Olga unpacks the difficulties faced when striving for accurate, nuanced translation across all languages, especially under-resourced ones.Beyond these hurdles, the conversation explores the cutting-edge opportunities and technical innovations driving progress, including RAG, the rise of purpose-built models, agentic AI workflows, and the potential of multilingual multimodality. Olga shares insights into boosting translator productivity, achieving more predictable quality, and the path toward human parity in translation, examining how technology and human expertise will shape the future of global communication.Chapters00:00 Introduction and Guest Welcome01:14 Evolution of NLP: From Rule-Based to Machine Learning02:40 Challenges in AI Translation04:21 Biases in Language Models05:28 Inference Time and Latency05:44 English-Centric AI Models08:53 Opportunities in AI Translation09:14 Industries Benefiting from Language AI10:36 Human-in-the-Loop Translation12:06 Architectural Innovations in Language AI16:20 Success with RAG Architectures17:58 Multilingual Vectorization19:54 Agentic AI in Translation24:35 Data Sets and Data Privacy28:30 Using Smaller, Purpose-Built Models32:10 Future of AI in Translation36:37 Conclusion and FarewellFollow the hostsFollow AtinFollow ConorFollow VikramFollow YashFollow Today's Guest(s)LinkedIn Olga BeregovayaLinkedIn SmartlingCheck out GalileoTry Galileo
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40:30
AI, Low-Code, and Shaping the Next Generation of Apps | OutSystems' Rodrigo Coutinho
What if you could turn a requirement document into a full enterprise application in just minutes?Rodrigo Coutinho, co-founder and AI Product Manager at OutSystems, joins hosts Conor Bronsdon and Atin Sanyal to explore this new reality of AI-driven development. Rodrigo shares insights from OutSystems' nearly 25-year journey, detailing their early adoption of AI and the development of their AI platform, Mentor. Discover how the pairing of AI and low-code empowers developers, accelerates the creation of enterprise applications, and shortens the cycle from idea to deployment.But this newfound speed brings its own set of challenges. The discussion addresses the hurdles of managing AI-generated code, contrasting experiences with traditional versus low-code approaches. Learn why a dev's focus pivots from syntax to strategy, pinpointing human creativity and ideation as the crucial limiter in today's development lifecycle. Chapters00:00 Welcoming Rodrigo Coutinho of OutSystems01:30 OutSystems' Early AI Journey (Pre-LLM)03:30 The LLM Revolution & OutSystems Mentor Emerges07:30 The Critical Need for Validating AI-Generated Apps12:00 The Shifting Role of the Modern Developer13:30 Quality Control & Accountability in the AI Era16:00 Low-Code's Edge in AI Validation18:30 OutSystems Mentor: A Deeper Look23:30 Choosing the Right AI Models (In-House vs Public)27:30 Future Opportunities: Speed, Experimentation & Multimodal AI37:00 The Use Case Hurdle & Final ThoughtsFollow the hostsFollow AtinFollow ConorFollow VikramFollow YashFollow Today's Guest(s)Website www.outsystems.comOutSystems MentorLinkedIn Rodrigo Sousa CoutinhoCheck out GalileoTry Galileo
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40:16
AI Won't Solve Your Toughest Engineering Problems | Honeycomb’s Charity Majors
Generative AI dominates the conversation, but does it actually make it easier to build, lead, and sustain high-performing engineering teams?Host Conor Bronsdon sits down with Charity Majors, co-founder and CTO of Honeycomb (.io), and the mind behind charity.wtf. Known for her sharp insights and unfiltered opinions, Charity kicks off the discussion by expanding on her popular article: 'Generative AI is not going to build your engineering team for you.' Together, they explore how AI has altered the dynamics for engineering teams and leaders. The discussion navigates the complex dynamics of hiring in an AI-enabled era, challenging the "senior-only" trend and championing the vital role of junior engineers in creating learning organizations. Charity also explains why writing code is often the "easy part" compared to the full lifecycle of owning and operating systems, a challenge amplified by AI-generated code. Finally, Conor and Charity discuss the risk of "cognitive decay" from over-reliance on AI tools and why fostering deep system understanding remains paramount for engineers and leaders.Chapters00:00 Introduction and Guest Welcome01:51 Generative AI and Engineering Teams02:26 The Writing Process and Inspiration03:49 AI's Impact on Hiring and Team Building05:30 Embracing AI and Automation07:43 The Role of Junior Engineers09:33 Building Effective Engineering Teams17:01 Future of AI in Code Generation20:07 High Performing Engineering Teams21:48 Evolving Expectations for Engineering Managers22:41 Cognitive Decay25:00 Feedback Loops in Software Systems26:56 Hiring for Potential vs. Experience29:17 The Future of Observability39:50 Closing Thoughts and Advice for EngineersFollow the hostsFollow AtinFollow ConorFollow VikramFollow YashFollow Today's Guest(s)Follow Charity: charity.wtfLearn more about Honeycomb: www.honeycomb.ioRead: Generative AI is not going to build your engineering team for youCheck out GalileoTry Galileo
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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