High Signal: Data Science | Career | AI

Delphina

Welcome to High Signal, the podcast for data science, AI, and machine learning professionals. High Signal brings you the best from the best in data science, machine learning, and AI. Hosted by Hugo Bowne-Anderson and produced by Delphina, each episode features deep conversations with leading experts, such as Michael Jordan (UC Berkeley), Andrew Gelman (Columbia) and Chiara Farranato (HBS). Join us for practical insights from the best to help you advance your career and make an impact in these rapidly evolving fields. More on our website: https://high-signal.delphina.ai/

  1. APR 16

    Episode 38: Why AI Won’t Fix Your Data Culture, It Will Only Amplify It (And What To Do About It)

    Noah Bruegmann, President of Data CRT, joins High Signal to discuss how to move your data function from a cost center to a strategic "value center". He explains how AI amplifies your existing data culture, the importance of "no-assistance" reporting, and how rebranding documentation as "Context" can finally secure executive buy-in. Drawing on 15 years of experience spanning trading floors and Silicon Valley startups, Noah argues that for too long, data teams have been submerged under an "iceberg" of invisible data preparation. He details how the arrival of LLMs and agentic tools is fundamentally shifting this landscape, automating technical drudgery and allowing data professionals to transition into what he calls "Jack Ryan" mode: acting as high-level intelligence analysts rather than mere number crunchers. We dig into the architectural and psychological shifts required to navigate this new era and why the most valuable skill in an AI-augmented world is no longer mastering SQL syntax, but "problem framing": the ability to reduce business ambiguity into high-leverage insights. Noah cautions that while AI offers a dopamine hit of instant answers, it demands a new discipline of rigorous verification to avoid automated hallucinations. The conversation provides a clear directive for executives: move past the "ticket-taker" model and start treating the data team as the essential "left-side brain" for organizational decision-making. LINKS Noah on LinkedIn High Signal podcast Watch the podcast episode on YouTube Delphina's Newsletter

    46 min

  2. APR 2

    Episode 37: Engineered Intelligence and The Data Science Problem in AI

    Jordan Morrow, SVP of Data & AI Transformation at AgileOne and the "Godfather of Data Literacy," joins High Signal to discuss the shift from being "data-driven" to becoming "AI-enabled." Jordan warns that many organizations are walking into the same traps that derailed the data science era a decade ago: prioritizing expensive tooling and hype over the cultural change and literacy required to actually move the needle. The pattern is already visible: enterprise AI projects are failing at around 90%, while individuals doing shadow AI are quietly thriving. The catch is that shadow AI brings its own risks, with people feeding sensitive data into public models without governance. He argues that because AI is probabilistic rather than deterministic, the bottleneck for success has shifted from technical coding ability to a user’s ability to apply "Engineered Intelligence," a blend of machine capability and human emotional intelligence. LINKS Jordan's new book "Data and AI Skills: Gain the Confidence You Need to Succeed" (also here on Amazon) Jordan on LinkedIn High Signal podcast Watch the podcast episode on YouTube Delphina's Newsletter

    46 min

  3. MAR 19

    Episode 36: AI and the Judgment Problem in Data Science

    Dawn Woodard (Distinguished Engineer, LinkedIn), Andrés Bucchi (LATAM Airlines), and Jeremy Hermann (CEO & Co-Founder, Delphina) join High Signal for a deep dive into the shifting architecture of data science & analytics in the era of AI. As the industry moves from static dashboards to vibe coding and conversational querying, this panel of industry veterans explores why traditional data fundamentals—strict cataloging, verifiable outputs, and a single source of truth—are suddenly the most critical bottlenecks in the AI era. We dig into the sobering reality of the "source of truth" problem, where the speed of AI-generated code far outpaces our ability to define what "correct" actually looks like in a complex enterprise. The conversation reveals how AI is breaking legacy experimentation platforms, the transition of the data analyst into a "verifier" of AI-generated workflows, and why "headless" security architectures are essential for the next generation of autonomous agents. From the limitations of LLMs in causal reasoning to the challenges of integrating AI into "brownfield" enterprise codebases, this discussion provides a grounded framework for leaders navigating the gap between AI hype and operational reality. LINKS Dawn on LinkedIn Andrés on LinkedIn Jeremy on LinkedIn Build Your Bracket with Data in the Delphina Sandbox High Signal podcast Watch the podcast episode on YouTube Delphina's Newsletter

    1h 4m

  4. MAR 5

    Episode 35: Beyond Online Experimentation: Generative Software That Optimizes Itself

    Martin Tingley, Head of Windows Experimentation at Microsoft and former Head of the Experimentation Platform Analysis Team at Netflix, talks about why humans are the bottleneck in experimentation, and how a five-level maturity framework points the way toward self-optimizing software. Our conversation traces the path from basic hypothesis testing to a frontier where Generative AI creates, evaluates, and refines product variants in a closed loop. We explore the architectural shift required to move from testing single variants to optimizing entire parameter spaces, and how startups are already using AI to generate production-ready landing pages for Fortune 500 companies in hours rather than weeks. Tingley also shares a strategic lens on "experimentation programs," explaining how plotting the distribution of treatment effects across different product areas can serve as a powerful tool for capital allocation and high-level strategy. LINKS Martin on LinkedIn Want Your Company to Get Better at Experimentation? by Iavor Bojinov, David Holtz, Ramesh Johari, Sven Schmit and Martin Tingley (Harvard Business Review) Avoid the Pitfalls of A/B Testing by Iavor Bojinov, Guillaume Saint-Jacques and Martin Tingley (Harvard Business Review) Martin & Co.'s Seven Part Blog Series on Experimentation at Netflix Roberto Medri (Meta) on High Signal: The Incentive Problem in Shipping AI Products — and How to Change It Tim O’Reilly on High Signal: The End of Programming As We Know It Watch the podcast episode on YouTube Delphina's Newsletter

    55 min

  5. FEB 10

    Episode 34: Duolingo and the Future of Personalized Education with AI

    Bozena Pajak, VP of Learning at Duolingo, joins High Signal to discuss the evolution of AI at Duolingo: from personalized difficulty models to the current generative frontier where AI characters provide low-stakes and high impact conversational practice. We discuss the role of AI in overcoming one of the biggest hurdles in language acquisition, speaking anxiety. We also talk about how Bozena's team leverages agentic workflows to scale content and why the next wave of personalization involves shifting from difficulty levels to "thematic lenses" tailored to specific user interests. LINKS Bozena on LinkedIn The original AI: how your brain tracks language patterns, a Duolingo blog post How Duolingo uses AI to create lessons faster, a Duolingo blog post Duolingo is hiring a Learning Scientist (Efficacy Research), a Director of Learning Design (Language Learning), and a Director of Learning Design (Immersive Language Learning) High Signal podcast Watch the podcast episode on YouTube Delphina's Newsletter

    46 min

  6. JAN 27

    Episode 33: Why Your AI Product Will Be Obsolete in Six Months (And What To Do About It)

    Benn Stancil, writer and co-founder of Mode, joins High Signal to ask some uncomfortable questions about the current AI moment. Is now actually a terrible time to start a company? If the tools you build on today are obsolete in six months, at what point does the head start stop mattering? Is all that context engineering you're doing a waste of time, destined to go the way of Boolean search syntax in the 90s? Benn argues that AI is turning us all into Steve Jobs, not the visionary who delegated, but the one who berated people over pixel placement. As AI takes over the doing, our job becomes obsessing over the polish. He makes the case that technical debt may be self-healing: if future models can untangle the mess today's models made, then messy code isn't debt…it's a spec for a clean rewrite. We also dig into why Claude Cowork can't work. AI has these uncanny ticks you can't beat out, so anything it writes "as you" will smell like AI. The solution isn't better AI writing—it's to stop pretending we write to each other at all. Benn envisions a future where communication is radically intermediated: I dump facts into a shared repository, your AI reads them, and nobody bothers with the social decoration in between. LINKS Benn’s blog on Substack Benn.website, with links to all everything else Benn related Will there ever be a worse time to start a startup? Today's frontier is tomorrow's tech debt. Why Cowork can’t work: The future isn’t collaborative. Producer theory: Platforms are overrated. Tim O’Reilly on High Signal: The End of Programming As We Know It Watch the podcast episode on YouTube Delphina's Newsletter

    1 hr

  7. JAN 13

    Episode 32: The Post-Coding Era: What Happens When AI Writes the System?

    Nicholas Moy, former Head of Research at Windsurf & now at Google DeepMind, joins High Signal to discuss the shift from "co-driving" to a truly "agentic" era of development. We discuss Windsurf's journey from early prototypes that struggled with compounding errors to the successful launch of their agentic coding product. Nick explains that building a startup in the current climate requires a strategy of "disrupting yourself" to avoid the innovator’s dilemma; companies must be ready to pivot as soon as a new frontier model makes previously impossible features viable. He argues that traditional technical moats are increasingly fragile, and true defensibility now comes from real-world usage data, brand reputation, and a deep intuition for what users need at the frontier of these capabilities. LINKS Nicholas Moy on LinkedIn Introducing Google Antigravity, a New Era in AI-Assisted Software Development “A Flash of Deflation - Gemini 3 Flash represents a step function increase in model deflation : a gauntlet thrown” by Thomas Tunguz Tomasz Tunguz on Why a Trillion Dollars of Market Cap Is Up for Grabs (and How AI Teams Will Win It) High Signal podcast Watch the podcast episode on YouTube Delphina's Newsletter

    42 min

  8. 12/30/2025

    Episode 31: Why Data Governance In Your Org is Broken (And How to Fix It)

    Cara Dailey, VP and Head of Data Strategy at Early Warning (the parent company of Zelle), joins High Signal to discuss the evolution of high-stakes data leadership and governance. From her early work in online advertising at DoubleClick to shaping data strategy at Nike and holding Chief Data Officer roles at Bank of the West and T. Rowe Price, Cara has seen every iteration of the data leader’s role. Now, she’s navigating her 'product era'—shaping the data strategy for Early Warning's Decisions Intelligence business, where she leverages rich financial data and data science to drive fraud monitoring and modeling. In this episode, Cara shares her pragmatic 'progress over perfection' approach to governance, why she’s abandoning monolithic platforms in favor of incremental data products, and her 80/20 rule for balancing operational rigor with innovation. We also discuss why 'loving' data isn't enough—you have to actually 'take care' of it—and why AI is finally shining a spotlight on the often-neglected fundamentals of data stewardship and conversational BI. LINKS Cara Dailey on LinkedIn Why AI Adoption Fails: A Behavioral Framework for AI Implementation, A High Signal Conversation with Lis Costa (Chief of Innovation, Behavioural Insights Team) Watch the podcast episode on YouTube High Signal podcast Delphina's Newsletter

    47 min
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5
out of 5
19 Ratings

About

Welcome to High Signal, the podcast for data science, AI, and machine learning professionals. High Signal brings you the best from the best in data science, machine learning, and AI. Hosted by Hugo Bowne-Anderson and produced by Delphina, each episode features deep conversations with leading experts, such as Michael Jordan (UC Berkeley), Andrew Gelman (Columbia) and Chiara Farranato (HBS). Join us for practical insights from the best to help you advance your career and make an impact in these rapidly evolving fields. More on our website: https://high-signal.delphina.ai/

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