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Welcome to DataFramed, a weekly podcast exploring how artificial intelligence and data are changing the world around us. On this show, we invite data & AI leaders at the forefront of the data revolution to share their insights and experiences into how they lead the charge in this era of AI. Whether you're a beginner looking to gain insights into a career in data & AI, a practitioner needing to stay up-to-date on the latest tools and trends, or a leader looking to transform how your organization uses data & AI, there's something here for everyone.
Join host Richie Cotton as he delves into the stories and ideas that are shaping the future of data. Subscribe to the show and tune in to the latest episode on the feed below.
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#385 Creating an Engine of Value from AI | Jim Rowan, Head of AI at Deloitte USA
Most large organizations have bought into AI, yet far fewer have turned it into measurable value. Surveys of thousands of business leaders show the same pattern: spending on technology is up, while investment in data foundations, process re
#384 Is the Cloud Over? | Sergio Gago, CTO at Cloudera
AI agents are only as useful as the data they can reach, and most company data is scattered across clouds, data centers, and legacy systems. Giving agents access is easy to get wrong, especially when the data includes salaries, customer rec
#383 How to Coordinate Intelligence Across Teams & Agents | Vijoy Pandey, SVP of Outshift at Cisco
AI agents are getting easier to build and connect. Open standards now let them discover each other, pass messages and use shared tools. But connecting agents is not the same as getting them to work toward the same goal, and research on mult
#382 What DataCamp's Learner Data Says About Learning | Pieter Moors, Lead Data Scientist at DataCamp
Career goals in data have shifted quickly. Data scientist was long the default target, but AI engineer has appeared from almost nowhere, and companies are moving training toward AI literacy, agents, and prompt engineering. Certifications ar
#381 Escaping the AI Hiring Doom Loop with Daniel Chait, CEO & Ophir Samson, Head of Voice AI at Greenhouse
Most hiring decisions still come down to gut feel, and gut feel is full of blind spots — a favorite school, a firm handshake, the type of coffee someone carries into the room. As AI reshapes recruiting, the industry is being forced to ask w
#380 The Best Moments from RADAR 11x: AI, Jobs, Agents and Skills
A job title can stay the same while the work underneath it changes completely. That idea ran through RADAR 11x, our online conference, and this recap keeps the best moments from four of the day's eight sessions. You will hear how to sort yo
#379 The Secrets of Deploying AI in Production | Sumti Jairath, Chief Architect at SambaNova
AI agents are moving from demos into production, but many teams run into the same wall: responses that take too long and cost too much. As models grow bigger and reason through more steps before answering, every chained agent adds delay, an
#378 The Data Engine for AI with Ledion Bitincka, CTO at Cribl & Nikhil Mungel, Head of AI R&D at Cribl
As agents take over more of the actual coding, the nature of technical work is shifting from producing software to judging it. Engineers increasingly spend their time specifying what should be built and then checking whether an agent's outp
#377 The Algorithm for Hypergrowth with Jon McNeill, CEO at DVx Ventures & Former President at Tesla
Hypergrowth companies rarely scale on strategy alone — they scale on how fast decisions get made and how much risk employees feel safe taking. A recurring idea in high-growth environments is treating decisions differently depending on wheth
#376 Rethinking the Data Stack in the age of AI with Tristan Handy, President of Fivetran + dbt Labs
Across the data and AI industry, infrastructure that once served dashboards and human analysts is being rebuilt to serve autonomous agents instead. That shift changes what "AI-ready data" actually means, pushing teams to rethink documentati
#375 Is Math The Key to Better Coding AI? With Tudor Achim, CEO at Harmonic
AI capability in mathematics jumped before most people noticed, tackling Olympiad-level problems and unsolved research questions that had resisted attack for years. But the pattern of where AI succeeds and where it stalls is uneven and wort
#374 How to Thrive in a World of Continuous Transformation | Phil Le Brun and Jana Werner, Executives in Residence at AWS
Technology is now moving faster than the organizations trying to adopt it. A model can be tested in an afternoon, but the approval to test it can take half a year, and that gap is where most transformation budgets quietly disappear. The str
#373 What Do Your Colleagues Do All Day? (The Value of Institutional Knowledge & AI for Process Reengineering) | Jennifer Smith, CEO at Scribe
Four years into the AI boom, headlines still promise agents that will run entire departments, yet most companies can't point to the transformation they were sold. The gap isn't intelligence — today's models are remarkably capable — it's con
#372 Bulletproof Large Scale Data Science with Srini Raghavan, Chief Product Officer at Freshworks
Software buying decisions used to be made once, by someone far removed from the people actually using the tool. That model is breaking down. Teams now expect software to work out of the box, without weeks of setup, integration, and configur
#371 The Real Reason Your Product Team Needs a Feedback Loop with Todd Olson, CEO at Pendo
Software teams are shipping faster than ever, but speed hasn't solved the oldest problem in the industry: most software still isn't very good. AI coding tools have lowered the barrier to building something, yet they haven't lowered the barr
#370 Failure is Data (and Other Career Advice) | Todd Dewett, Leadership Author & Speaker
As AI takes over more technical and routine work, the skills that set data and AI professionals apart are shifting. Raw technical ability and a high IQ still matter, but they are becoming table stakes as tools get more capable and teams get
#369 How to Become a Top Business Intelligence Analyst | Helen Wall, Founder at Helen Data Design & Microsoft Influencer
Business intelligence has never been only about building charts and writing queries. Most of the work that makes a report trustworthy happens below the surface — in the data models, documentation, and stakeholder conversations that users ne
#368 AI Agents Are Now Your Database's Main User | Reynold Xin, Co-Founder at Databricks
For forty years, the rule held that transactional and analytical databases had to be separate systems, connected by fragile pipelines that move data from one to the other. That assumption is now being questioned. As AI agents start generati
#367 Don't Build on Jell-O: How to Make Agentic AI Reliable with Dan Klein, CTO at Scaled Cognition
Across the AI industry, capability has exploded while trustworthiness has lagged badly behind. The same technology that writes fluent prose can invent a refund policy that was never real, and most of those errors are subtle enough that no o
#366 Can AI Agents Outperform a Data Scientist? | James Zou, Professor at Stanford University
AI agents are no longer limited to automating routine tasks like customer support or report generation. Research labs and pharmaceutical companies are beginning to deploy teams of specialist AI agents capable of designing experiments, analy
#365 Your 90 Day Blueprint for AI Success with Charlene Li, Author of Winning with AI
Most organizations know AI matters, but few have turned that conviction into a written plan. Ambition and hope are everywhere; a clear roadmap tied to business strategy is rare. For teams on the ground, this gap shows up as scattered initia
#364 How to Enable Agentic Commerce with Nell Thomas, VP of Data at Shopify
AI agents are starting to handle parts of the shopping journey that used to require human judgment — discovery, comparison, checkout. But behind every agent recommendation is a massive, invisible layer of data infrastructure. Product catalo
#363 Build Your Personal Brand at Work | Dorie Clark, Executive Education Faculty at Columbia Business School
Technical skills are being commoditized faster than ever. As AI takes on more of the work that used to define a junior knowledge worker, the things that once made someone valuable are becoming table stakes. What compounds in this environmen
#362 How to Have a Machine Learning Career in 2026 | Marina Wyss, Senior Applied Scientist at Twitch
The role of the machine learning engineer is being rewritten in real time. AI coding assistants are absorbing parts of the day-to-day, planning and evaluation are eating up more of the week, and the lines between machine learning engineer,
#361 If You Want AI to Work, Fix This Boring Thing First with Veronika Durgin, VP of Data at Saks
Every conversation about AI in data eventually arrives at the same question: which roles survive, and which ones get automated away? Generative AI can already draft SQL, build dashboards, and run exploratory analysis — but it still can't si
#360 What's Your Biggest AI Ethical Nightmare? | Reid Blackman, CEO at Virtue Consultants
Most AI ethics conversations sound the same: be fair, be transparent, be accountable. The values are right, but in practice they don't get teams out of bed in the morning. Executives nod along, employees take the compliance training, and me
#359 My Best Friend is AI with Valerie Tiberius, Professor of Philosophy at University of Minnesota
Valerie Tiberius is the Paul W. Frenzel Chair in Liberal Arts and Professor of Philosophy at the University of Minnesota. She is an expert in ethics, moral psychology, and well-being, and the author of five books including What Do You Want
#358 How AI Agents Will Work While You Sleep | Ruslan Salakhutdinov, Professor at Carnegie Mellon
Almost every AI agent demo lands in roughly the same place: it works most of the time, looks remarkable, and then fails in a way no one anticipated. Self-driving cars hit this wall a decade ago, and agents are running into it now. For data
#357 Data-Driven Workforce Analytics with Ben Zweig, CEO at Revelio Labs
The data field has changed shape faster than almost any other. The role that used to be a statistician became a data scientist, became an ML engineer, and is now morphing into AI engineer. Consulting firms are hiring fewer entry-level analy
#356 The Forecast for Time Series Forecasts with Rami Krispin, Senior Manager of Data Science at Apple
Time series data is everywhere — from inventory systems and energy grids to financial planning and product demand. As data volumes grow, the old ways of building individual forecasting models simply don't scale. How do you forecast hundreds
