Over 200,000 people follow her fearless, "unhinged" posts on production A.I. systems, and yet Carly Taylor often can't sleep the night before she speaks on stage. In today's episode, hear why she chases the situations that scare her, including at the A.I. frontier.
More on Carly:
• She is (IMO) the funniest person to follow on LinkedIn.
• Founder of Rebel Data Science.
• Shipped nine Call of Duty titles in five years at Activision, where she led game security.
• Other previous roles include being director of engineering at Microsoft and Field CTO for the gaming vertical at Databricks.
In today's fun and wide-ranging episode, Carly covers:
• Technical A.I. tips.
• General career advice anyone can make use of in these fast-moving times.
• Why she deliberately chases the situations that scare her.
• Why no organization can afford *not* to innovate right now.
• How to use A.I. to sharpen your thinking.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Filtering by Category: Interview
In Case You Missed It in September 2026
September was PACKED with incredible guests having invaluable conversations on my show. ICYMI, today's episode highlights the best bits:
1. The wildly popular data scientist and entrepreneur Aishwarya Srinivasan details which failures a person ought to live through themselves before anyone trusts them to deploy an agent to production.
2. Dr. Luis Serrano, founder of Serrano Academy and author of the bestselling book Grokking Machine Learning, describes "word gravity": that is, how transformer architectures "bend space".
3. Dr. Caitlin Malone, host of the very popular Linear Digressions podcast, fills us in on how A.I. automations brought the show back to life after a five-year hiatus.
4. Dell Technologies' distinguished engineers Ishan S. and Tyler Cox explain why agentic A.I. burns through tokens at a rate that is catching companies out... and what we can do about it.
5. Dr. Dilani Kahawala — a Harvard physics PhD who spent a decade in product leadership at Etsy, Facebook and Atlassian — tells me she has had to throw almost all of that product experience away as she began developing Anna, her always-on A.I. assistant for families. She then walks us through the three problems that turn out to be hardest when your product has no user interface and never stops running.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Workslop: The Hidden Cost of AI-Generated Work, with Prof. Jeff Hancock and Dr. Kate Niederhoffer
That A.I.-written email you fired off to save 10 minutes? It may have cost your colleague an hour... and cost you their trust. Today Prof. Jeff Hancock and Dr. Kate Niederhoffer, coiners of the term "workslop", join me to fix its scourge!
More on Jeff:
• Professor of communication at Stanford University and founding director of the Stanford Social Media Lab.
• Was previously a professor at Cornell University.
• Holds a PhD in psychology from Dalhousie University in Canada.
More on Kate:
• Chief Scientist at BetterUp, a workforce coaching platform that combines human professional coaching, behavioral science, and A.I. to support personal growth, leadership, and mental fitness.
• Holds a PhD in psychology from the The University of Texas at Austin.
Together, Kate and Jeff are prolific co-authors of widely-cited articles on workplace productivity in the A.I. era. They publish in both academic journals and commercially-minded publications like the Harvard Business Review. It was their September 2025 HBR article "A.I.-Generated Workslop is Destroying Productivity" that introduced the world to the now widely-used "workslop" term.
In this episode, Kate and Jeff reveal:
• Why over half of workers admit to producing workslop.
• How it can cost a large company tens of millions of dollars a year.
• Their new concept of "relation slipping".
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Agents Need 10x More Data Than Humans, with Salesforce’s CDO Michael Andrew
Four years ago, Salesforce's own customer data were scattered across 650 different data streams and 266 million fragmented profiles, so getting a complete customer picture felt impossible.. My guest today, Salesforce’s Chief Data Officer Michael Andrew, fixed that… and now he's rebuilding it all again for a new kind of customer: AI agents. #ad #SalesforcePartner
More on Michael Andrew:
• Has been at Salesforce for nearly 8 years, eventually growing into the CDO role.
• Has spent nearly three decades listening to customers through data and, at Salesforce, he runs one of the largest Data 360 deployments in the world.
• Previously held a range of analytics and data science leadership roles between San Francisco and London.
In this special episode recorded live at Dreamforce two weeks ago, Michael explains:
• Why agents need ten times more data than humans do.
• Why moving data between warehouses is usually money wasted.
• What data scientists, engineers and analysts should be learning right now as agents (rather than people!) become the main consumers of their work.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Tokenomics: Why Your Agentic AI Bill Is Exploding (and How to Fix It), with Tyler Cox and Ish Shah
Over a single weekend, Ishan S. burned through 2 billion tokens (building a video game for his wife)! He and Tyler Cox join me in today's episode to explain why agentic A.I. bills are exploding... and how a box under your desk can cut them by up to 93%.
Tyler and Ish are returning guests on my podcast... but they are on the show *together* for the first time today. They are both Distinguished Engineers in the Office of the CTO for the client group at Dell Technologies, where they work out how to run powerful A.I. models on the machines closest to you.
In this information-rich episode, Tyler and Ish:
• Dig into "tokenomics" (why agents and their sub-agents devour so many more tokens than chatbots ever did).
• How to pick the right LLM for the job.
• How moving agentic workloads off pay-per-token cloud APIs and onto your own hardware can pay for itself in as little as two months.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Garbage In, Gospel Out: Why Agents Need Better Data, with Salesforce’s Gaurav Pathak
When humans get bad data, we argue about it in meetings. When AI agents get bad data, they can turn it into an answer with total confidence.
My wise guest today, Gaurav Pathak, calls it “garbage in, gospel out.” The takeaway? Better data and context lead to better AI — and, of course, Gaurav has some thoughts on how to get there. #ad #SalesforcePartner
Gaurav Pathak:
• Senior Vice President Product Management AI and Metadata at Salesforce.
• Previously spent 13 years at Informatica building its metadata and AI products, including the CLAIRE AI engine, before Salesforce acquired the company last year.
• Holds a degree in computer science and engineering, as well as an MBA
In this episode, filmed live at Dreamforce in San Francisco last week, Gaurav explains:
• Why context is 95% of the battle for enterprise agents.
• Who the "sin eaters" are that pay for an agent's mistakes.
• The three skills that matter most for AI engineers today.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
How AI Brought a Podcast Back From the Dead, with Linear Digressions’ Katie Malone
Dr. Caitlin Malone's extremely popular "Linear Digressions" podcast went silent for five years. Then A.I. made it possible to bring it back... and to manage it like a team. Hear all about effective agent teams in today's excellent episode.
More on Katie:
• Hosts and produces "Linear Digressions", one of the world's most popular data-science podcasts. (It's excellent — check it out!)
• Senior Researcher at Moonlite AI.
• Previously Sr Director of the A.I. Innovation Lab at the Health Care Service Corporation, Sr Director of Data Science at Tempus Labs, and Director of Data Science at Civis Analytics.
• Has taught machine learning via Udacity and at the University of Chicago.
• Holds a PhD in experimental particle physics from Stanford University focused on working with CERN data.
In this episode, Katie explains:
• Why managing people and managing A.I. agents are the same skill in different clothing.
• Why A.I. could hollow out the expertise we need to catch its mistakes.
• A fascinating range of data paradoxes from Simpson’s to Benford’s.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
The Chip Built for Agentic AI Inference, with SambaNova’s Anton McGonnell
GPUs are the workhorse of A.I. inference… but they aren’t actually optimized for inference! SambaNova has raised over $2B to build a new chip that is, pushing the frontier of real-time A.I. speed and bandwidth. Hear about it from Anton in today's episode.
More on Anton McGonnell:
• VP of Product at SambaNova, a Bay Area A.I.-hardware business recently valued at $11 billion.
• Was previously Director of Product Management for Machine Learning at UiPath and responsible for A.I. research at Glasswing Ventures.
• Holds an MBA from Harvard Business School and a degree in computer science from Queen's University Belfast.
In today's episode, Anton explains:
• Why agentic A.I. has changed the shape of inference workloads.
• How SambaNova's chip sidesteps the memory bottleneck that slows GPUs when generating output tokens.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Word Gravity: How Transformers Bend Space, with Dr. Luis Serrano
Today, the renowned A.I. scientist Dr. Luis Serrano (>200k YouTube subs; ex-Apple; ex-Cohere) returns to launch the second edition of his bestselling ML book and for a mind-bending convo on how LLMs "curve space-time".
More on Luis:
• Founder of the Serrano Academy (YouTube channel with over 200,000 subscribers hooked on his visual, intuitive explanations of machine learning).
• Previously worked at Apple, Cohere and the quantum-computing startup Zapata.
• The second edition of his bestselling Manning Publications Co. book "Grokking Machine Learning" is out this month!
In today's episode, Luis details:
• His mind-bending new paper on how transformer architectures mirror Einstein's curved space-time.
• Why RAG isn't an agent.
• How GRPO (the reinforcement-learning technique behind DeepSeek's reasoning breakthrough last year) works.
• ...and much more!
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
In Case You Missed It in August 2026
If you're in the Northern Hemisphere, summer is drawing to a close... but, ICYMI, today's episode highlights the best bits of the hot hot hot conversations that we had on my podcast in August:
1. In one of the technically richest conversations ever on the show, MongoDB's Field CTO of A.I., Pete Johnson, details the two common traits every company seeing ROI on A.I. investment have.
2. Gurobi Optimization's manager of decision-intelligence strategy Jerry Yurchisin returns to the show to explain where the division of labour between agents and mathematical solvers ought to fall.
3. Priyanka "The Cloud Girl" Vergadia (bestselling author, ex-Google, ex-Microsoft) walks us through how she structures Claude skills so that her output stops being slop.
4. dbt Labs founder and CEO Tristan Handy explains why the semantic layer matters more, not less, now that analytics agents are the ones asking the questions.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Agentic AI Skills That Matter Now, with Aishwarya Srinivasan
My exceptional guest today is world-renowned data scientist, author, tech entrepreneur and content creator (>1.2m followers!) Aishwarya Srinivasan... and she does not disappoint! This is one of my favorite episodes ever, enjoy :)
More on Ash:
• Co-founder of The Gen Academy and a stealth A.I. startup.
• Prolific A.I. startup advisor and investor.
• Sought-after global keynote speaker.
• Author of the book "What's Your Worth? Discovering Your Personal Brand".
• Has held roles at Nebius, Fireworks AI, Microsoft, and been a data scientist at Google, IBM and Goldman Sachs.
• Holds a Master's in Data Science from Columbia University.
In this episode, Ash covers:
• Where defensibility comes from when code is nearly free.
• How to evaluate non-deterministic agentic systems end to end.
• Why reinforcement learning is having such a resurgence.
• How to future-proof your career.
• ...and much, much more!
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
How dbt Won Analytics Engineering, with dbt Lab’s CEO Tristan Handy
dbt is THE open-source tool that brought software-engineering rigor to data transformation; it's now used by over 100,000 teams. Today's rockstar guest, Tristan Handy, is CEO of dbt Labs, the company behind the movement.
More on Tristan:
• President and co-founder of "Fivetran + dbt Labs" (recent merger).
• Coined the term "analytics engineering".
• Over two decades of experience as a data practitioner working in both large enterprises and startups.
• His expertise and data industry best practices have influenced thousands of subscribers and listeners weekly via his newsletter (The Analytics Engineering Roundup) and The Analytics Engineering Podcast.
In this episode, Tristan explains:
• What dbt is.
• Why dbt Labs' the recent merger with Fivetran is a win for dbt users.
• Why skill files are so powerful.
• Why he turned down acquisition offers for years
• How the semantic layer keeps A.I. agents from confidently getting your metrics wrong
• ...and much more.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Vector Search, Agentic Memory and Effective RAG, with MongoDB’s Pete Johnson
Today's guest, MongoDB's "field CTO for A.I." Pete Johnson, is exceptional... don't miss this episode! We get deep into vector search, agentic memory, RAG and much more, with Pete vividly explaining technical content like no other.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Mathematical Optimization in the Agentic AI Era, with Gurobi’s Jerry Yurchisin
LLMs will confidently tell you they've optimized your entire business while ignoring the one constraint that could cost you millions. Today's episode with Jerry Yurchisin is all about a technique that makes breaking a constraint mathematically impossible.
More on Jerry:
• Manager of Decision Intelligence Strategy at Gurobi Optimization, a "mathematical optimization" solver that's used by the vast majority of Fortune 100 companies.
• Has over a decade of experience in operations research, data science, and visualization... and specializes in enhancing decision-making.
• Prior to Gurobi, Jerry worked in consulting (OnLocation, Inc. & Booz Allen Hamilton) where he focused on mathematical optimization, machine learning, statistics and simulation.
• Taught statistics and operations research at The University of North Carolina at Chapel Hill and graduate math at Ohio University (he also holds Master's degrees from both of these institutions).
In this episode, Jerry:
• Lays out where mathematical optimization fits in the agentic AI era (hint: LLMs formulate problems and solvers like Gurobi guarantee the answers).
• Shares striking mathematical-optimization applications spanning energy grids, retirement planning... and the model that powered @null's women's team to a gold medal at the Paris Olympics.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
Weapons of Math Destruction, Ten Years On, with Dr. Cathy O’Neil
What makes an algorithm terrifying? My guest today, mega-bestselling author of "Weapons of Math Destruction" Dr. Cathy O'Neil, says it's not the complexity of the math; it's the secrecy, the unaccountability and the fact that you can't opt out.
More on Dr. O'Neil:
• A decade after her "Weapons of Math Destruction" (2016) sounded the alarm on algorithmic harm, she's busier than ever.
• Through her algorithmic-auditing firm ORCAA and her nonprofit OCEAN, she now provides the statistical evidence behind lawsuits against some of the world's biggest tech companies.
• Co-hosts the "A.I. Skeptics" podcast.
• Also wrote "The Shame Machine: Who Profits in the New Age of Humiliation", which was published in 2022 (like WMD, also by Penguin Random House).
• Before writing trade publications, her first book was actually an O'Reilly book, "Doing Data Science".
• Earlier in her career, she held academic positions at Massachusetts Institute of Technology and Barnard College before becoming a Wall-Street analyst at The D. E. Shaw Group.
In this episode, Cathy:
• Punctures A.I. hype.
• Explains why A.I. won't so much replace workers as degrade them.
• Lays out how all of us can demand accountability.
I wanted to have this exceptional conversation with Dr. O'Neil for a decade, enjoy!
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
The Math Still Matters: Deep Skills in the Age of AI, with Dr. Catherine Williams
Dr. Catherine Williams was solving black-hole equations with pen and paper before she ever wrote a line of code and, in today’s episode, she makes the case that going deep on AI/ML math matters more than ever...
...even now that AI can do the math for you.
More on Dr. Williams:
• PhD in math researching general relativity and black holes.
• Postdocs at Stanford University and Columbia University.
• Became one of the very first data scientists when she joined AppNexus back in 2012, around the same time "data scientist" became a job title.
• Across more than a decade of senior data leadership at AppNexus, Xander, Qualtrics and now Candid, she's watched our field get born and then reinvent itself again and again.
In today's episode, Catherine traces the data science and AI evolution — from Bayesian models to BERT to today's LLMs — and shares sharp guidance on which skills will still matter as machines take over more of the technical work.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
How AI Is Quietly Saving Lives, with Steve Mock
Negative A.I. buzz makes most of the headlines but there are lots of ways that A.I. has made big (even life-changing!) positive impacts on people. In today's episode, Steve Mock, shares many such inspiring stories.
More on Steve:
• Investor at the venture capital firm Blumberg Capital.
• Entrepreneur involved in growing five successful software businesses.
• Creator and developer (without writing any code!) of a website called AISavedMe.org that has a wide range of inspiring examples from healthcare to education to more trivial engineering stories.
In today's episode, we discuss:
• AISavedMe.org and the stories users have posted on the site.
• How he built the website without having a technical background.
• Lots of market insights from his entrepreneur-investor brain.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
How to Find Solid Career Ground in the AI Era, with 80,000 Hours Founder Ben Todd
Today's episode is not to be missed! Benjamin Todd returns with alarming A.I. possibilities (e.g., outcomes *worse* than human extinction) but also practical roadmaps for you to mitigate risks and thrive in the A.I. future.
Ben Todd:
• Author of the new Penguin Random House book "80,000 Hours: Find a Fulfilling Career that Does Good".
• Co-founder and President of 80,000 Hours, a globally renowned charity dedicated to helping people find careers they love.
• Is particularly expert at A.I. futures, A.I. careers and the future of work.
• Holds a Master's in physics and philosophy from the University of Oxford.
In this episode, we discuss:
• Ben's data-backed, extensively-researched guidance for the A.I. era.
• The best career advice from his brand-new book.
• Ways A.I. practitioners can find solid ground and do the most good.
• ...as well as ways A.I. could do the most bad!
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
In Case You Missed It in June 2026
It is mighty hot in New York rn... but not nearly as spicy as the interviews on my podcast in June! ICYMI, here are the best bits of my on-air convos last month:
1. Two-time mega-bestselling O'Reilly author Chip Huyen on what's left for humans to do when the cost of building software is headed to $0.
2. Andrey Kurenkov, co-host of my favorite podcast ("Last Week in A.I.") and Founding A.I. Lead at Astrocade, on effective vibe-coding.
3. Lightning AI's VP of Infrastructure Frank Basso on what it's actually like inside an A.I. data center.
4. Gilbert Eijkelenboom on why 85% of data scientists can't communicate their work effectively... and the framework for fixing this.
5. In a role-reversal for landmark Episode #1001, the founder and original host of the SuperDataScience Podcast, Kirill Eremenko, interviewed me. In this clip, we discussed whether AGI would require something like consciousness to be realized.
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.
People Skills for Analytical Thinkers, with Bestselling Author Gilbert Eijkelenboom
Gilbert Eijkelenboom was a pro poker player who read his opponents through data alone but in today's episode, the bestselling author explains why the people side of data science matters more than the math.
More on Gilbert:
• Wrote the bestselling book "People Skills for Analytical Thinkers".
• Run MindSpeaking, a firm that's trained over 15,000 (mostly technical) folks on "people skills".
• Folks love his invaluable content, allowing him to gather over 200k followers.
• Was previously Managing Consultant on data and digital analytics for Capgemini, as well as a professional poker player on BetVictor.
• Holds a Master's in behavioral economics from Maastricht University.
In today's episode, Gilbert covers:
• Why no matter how good your model or analysis is, it only creates value once people actually use it, which makes communication a core data skill rather than an optional extra.
• His "and, but, therefore" communications framework.
• How research suggests only around 15% of people are self-aware and his tips for closing that gap.
• How experiences in childhood install personal "algorithms" in our adult behavior like avoiding conflict or staying silent... but we can change as adults (and he also provides tips on how).
Thanks to Kate Strachnyi for suggesting Gilbert as a guest!
The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.