How to Get Hired at Top Firms like Netflix and Spotify, with Jeff Li

Many folks dream of doing AI/ML at top firms like Netflix and Spotify. In today's episode, Jeffrey Li spills the beans on how he got hired at these companies... and how you can too!

More on Jeff:

• Data Scientist at Netflix, focused on ads forecasting and optimization.

• Spent the last eight years building ML systems for Netflix, DoorDash and Spotify, specializing in time-series forecasting.

• Outside of work, he's sports-obsessed, incl. surfing, snowboarding, running, cycling and BJJ.

Today's episode gets into the technical weeds on time-series analysis on massive scales so it will appeal especially to hands-on practitioners like data scientists, AI/ML engineers and statisticians. Lots of it, however, will be fascinating to any listener, including Jeff's general tips on getting hired at top firms and his experience launching an AI startup.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

AI is a Joke, with Joel Beasley

This is definitely the funniest episode of my podcast: Software-engineer-turned-comedian Joel Beasley explains how he uses A.I. to quantify and optimize his comedy, with a lot of laughs along the way.

Joel:

• Two decades of experience as a software developer, including several CTO positions.

• Hosts the popular "Modern CTO Podcast", a top half-percent podcast globally.

• Most recently, a comedian who took off professionally as the opening act for comedy big-wig Jeff Allen on a US-wide tour.

Today's episode should be accessible — and hilarious! — to any interested listener.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Why 95% of AI Projects Fail and How to Be the 5% with Jon Krohn

95% of AI projects fail.

Here’s how to be the 5%.

On the latest episode of the Signal to Noise Podcast, I sat down with Michael Newcomer to unpack:

• Why AI capabilities are doubling every seven months

• How to identify and prioritize high-ROI AI projects

• The #1 trait of a great data scientist

… and much more!

If you're leading AI adoption or just trying to stay sane while doing it, this one's essential.

Creative Machines: AI in Music and Art, with Prof. Maya Ackerman

Humans haven't been able to distinguish Mozart from machine since the 1980s... why is it that we're only now freaking out about A.I. creativity? Prof. Maya Ackerman explains in today's episode!

More on Maya:

• Associate professor of computer science and engineering at Santa Clara University, where she specializes in generative A.I. research, a field she’s been immersed in for decades.

• Author of the brand-new book "Creative Machines: A.I., Art & Us".

• Co-founder and CEO of lyric- and music-generation startup WaveAI.

• Holds a PhD in computer science from the University of Waterloo.

Today's episode should be accessible — and fascinating! — to any interested listener.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Introducing the First Book in My A.I. Signature Series

I'm delighted to announce that the first book in my "Pearson A.I. Signature Series" is "Building Agentic AI" by the prolific author Sinan Ozdemir... and it will be published on Sunday!

It's available for pre-order now worldwide from wherever you buy your books! You can also read a digital version in the O'Reilly platform today if you have access to it.

The book is packed with hands-on examples in Python and it allows you to master the complete agentic A.I. pipeline, including practical guidance and code on how to:

• Design adaptive A.I. agents with memory, tool use, and collaborative reasoning capabilities.

• Build robust RAG workflows using embeddings, vector databases and LangGraph state management.

• Implement comprehensive evaluation frameworks beyond just "accuracy"

• Deploy multimodal A.I. systems that seamlessly integrate text, vision, audio and code generation.

• Optimize models for production through fine-tuning, quantization and speculative decoding techniques.

• Navigate the bleeding edge of reasoning LLMs and computer-use capabilities.

• Balance cost, speed, accuracy and privacy in real-world deployment scenarios.

• Create hybrid architectures that combine multiple agents for complex enterprise applications.

Thanks to Debra Williams Cauley, Dayna Isley and many more at Pearson for bringing this series to life. The second book in the series will be available in December and I'll announce that shortly!

Pre-order the book here!

Multi-Agent Human Societies, with Dr. Vijoy Pandey

AI agents will collaborate with us and each other to solve humanity’s biggest challenges. BUT a major hurdle toward this elysian future is being able to TRUST agents. In today's episode, Dr. Vijoy Pandey reveals solutions.

More on Vijoy:

• Brilliantly thoughtful and well-spoken engineering researcher who heads Outshift, a major tech incubator inside of Cisco.

• Focused on the Internet of Agents (specifically, AGNTCY | A Linux Foundation Project) and the Quantum Internet.

• Prior to Cisco, held engineering leadership roles (including CTO roles) at Google, IBM, Nortel Networks and others.

• Holds a PhD in Computer Science from University of California, Davis.

Dr. Pandey explains complex concepts so clearly and eloquently that anyone interested in AI or the future should enjoy today's episode.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

In Case You Missed It in October 2025

ICYMI... October's guests on my podcast were exceptional. Our most recent episode highlights the best part of my conversations with them:

1. Sheamus McGovern, founder of ODSC (the world's largest data science conference), details how to "rewire" your skills for the age of AI.

2. Gurobi Optimization's in-house guru Jerry Yurchisin provides real-world examples of how enterprises (specifically Toyota and Total Wine) have used mathematical optimization to save millions.

3. Researcher, broadcaster and bestselling author Dr Stephanie Hare opines on how we can use AI to build a fairer, more equitable world.

4. Pathway's brilliant Dr. Adrian Kosowski explains how their Transformer-killer BDH architecture, remarkably, allows multilingual models to be created by simply concatenating together two single-language models.

5. Unframe AI co-founder and COO Larissa Schneider explains how her firm (which recently raised $50m) has achieved so much success with a business model that she herself admits “did everything against the book.”

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Mixture-of-Experts and State-Space Models on Edge Devices, with Tyler Cox and Shirish Gupta

Mixture-of-experts models? State-space models? Easily running these cutting-edge LLM approaches on any device? In today's episode, deep experts Shirish and Tyler masterfully reveal all.

Shirish Gupta:

• Returns to my podcast for the third time this year!

• Director of A.I. Product Management at Dell Technologies, where he's been for over 20 years!

• Holds a Master's in Engineering from the University of Maryland.

Tyler Cox:

• Distinguished Engineer at Dell in the Client Solutions Group CTO.

• Leads on-device A.I. innovation programs across a wide range of products, including A.I. PCs, workstations, and edge computing platforms.

• Holds a Master's in Software Engineering from The University of Texas at Austin.

Today's episode will be particularly appealing to hands-on practitioners (e.g., data scientists, AI/ML engineers, software developers) as well as anyone who could benefit from considering shifting A.I. workloads from the cloud to local devices.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

Where to Find Me at Web Summit 2025

Hello from Lisbon — hope to see you at Web Summit this week! I'll be speaking, emceeing, hosting a meetup and judging a startup competition. Here's where you can catch me:

• Tue Nov 11 at 11:30am: I'll be hosting a "Beyond the Stage" Meetup for founders and execs on successful Agentic A.I. projects (at Meetup Location 2).

• Tue Nov 11 at 3pm: I'll be a judge in the "Startup Pitch" competition (on Stage 9).

• Wed Nov 12 at 1:20pm: "Intro to Agentic A.I." afternoon-opening keynote on the Developer Summit stage.

• Wed Nov 12 from 1:40pm to 4pm: Emceeing the Developer Summit stage.

• Thu Nov 13 at noon: I'll be providing one-to-one guidance to tech startups on scaling effectively (this is at the official "Mentor Hours" location).

Thanks to Brendan Garrett and Jack Knox for inviting me back! Can't wait :)

Frontier AI Agents for Data Science, with Sphinx’s Rohan Kodialam (Copy)

Rohan Kodialam has raised $9.5m to have A.I. agents work alongside you in Jupyter Notebooks, working as fluently with data as ChatGPT does with language. Hear all about Sphinx in today's episode!

More on Rohan:

• Founder/CEO of Sphinx.ai — you can check out their free tier right now.

• Previously head of A.I. development in the data strategies group of Citadel.

• Holds an M.Eng. in A.I. from the Massachusetts Institute of Technology.

Rohan is an exceptional speaker covering a fascinating topic so anyone might enjoy listening in but this episode will be particularly appealing to folks who work hands-on with data such as data scientists and analysts.

This episode was filmed live at Bessemer Venture Partners — thanks to Bhavik Nagda and Charles Birnbaum for hosting us! Videography by Eliana Alvarez Martinez.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

AI Catalyst: Enterprise Agent Deployments

In two weeks, I'm hosting a special half-day event in the O'Reilly platform on "Agents in the Enterprise". The speakers — Sadie, Luca and Tony — are sensational, ensuring it'll be informative and fun :)

The full event title is "A.I. Catalyst: Enterprise Agent Deployments" and it'll be held on Tuesday November 18th at 9am PT / noon ET.

Here are the specific speakers/topics:

1. Lightning AI CTO Luca Antiga will kick the event off by providing hands-on demos on how to deploy enterprise-grade multi-agent systems at scale — fast.

2. Renowned data science instructor, serial entrepreneur and data-community builder Sadie St Lawrence will cover how executives, managers and practitioners alike can thrive in the new "A.I. era" of work.

3. Tony Kipkemboi will detail how enterprises can operationalize multi-agent teams with tools like CrewAI.

There will be plenty of time for interactive Q&A with each of the speakers.

This event is produced by the learning-publishing giant Pearson and part of the "A.I. Catalyst" series I've been hosting in the O'Reilly platform for a couple of years now. Thanks to Debra Williams Cauley and Dayna Isley at Pearson in particular for creating and supporting this "A.I. Catalyst" special-event series.

Learn more / register here: learning.oreilly.com/live-events/ai-catalyst-enterprise-agent-deployments/0642572250188/

If you don't have access to the O'Reilly platform already, you can get a free 30-day trial with my code "SDSPOD25".

The Two Types of Agentic Systems

There are two types of agentic systems: workflows (simpler, safer) and agents proper (more capable but tougher to control). Hear more detail on this critical distinction in today's short video.

This clip was taken from a four-hour "Agentic A.I. Engineering" workshop that I delivered with Ed Donner (that has now been watched over 128,000 times on YouTube!)

Over the coming weeks, I'll continue to release more clips from the full workshop that explain additional discrete topics and, like today's video, I'll publish it in full on LinkedIn so you can enjoy it here if you prefer.

My agentic A.I. YouTube playlist that includes the other short clips and the full four-hour workshop.

How to Design AI-First Products, with Marc Dupuis

How can you glean business insights from your data 10x faster? With an "A.I.-First" analytics tool, of course! In today's episode, Fabi.ai CEO Marc Dupuis details A.I.-First Product Design.

Fabi is a Bay Area-based business-intelligence platform designed from scratch for accelerating productivity with A.I. models. It combines SQL, Python and clever automations into one platform so anyone can explore, discover and share data insights in real time. If it can do all that, do we even need data scientists anymore? Listen in and find out!

More on Fabi CEO Marc:

• Having led analytics and AI teams, experienced firsthand how much time gets wasted on routine data tasks instead of solving meaningful problems.

• During his time as an early product manager at Clari, Marc led the platform, analytics, and A.I. efforts, helping turn the company into a RevOps leader.

• Holds a degree in electrical engineering from Villanova University and an MSc in neurotechnology from Imperial College London.

Today's episode will be particularly appealing to anyone who works with data (e.g., data analysts, scientists) as well as anyone who wants to design A.I.-native products.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.

LLMs Are Delighted to Help Phishing Scams

Reuters recently tested 6 major LLMs (Grok, ChatGPT, Meta AI, Claude, DeepSeek, Gemini) to assess whether they'd create phishing content... with minor prompt adjustments, 4 out of 6 complied — yikes!

THE INVESTIGATION

Reporters from Reuters requested phishing emails targeting elderly people, fake IRS/bank messages, and tactical scam advice.

THE RESULTS

• Despite initial refusals across the board, relatively simple prompt modifications bypassed safety guardrails.

• Grok, for example, generated a fake charity phishing email targeting the elderly with urgency tactics like "Click now to act before it's too late!"

• When tested on 100 California seniors, the A.I.-generated messages successfully persuaded people to click on malicious links, often because messages seemed urgent or familiar.

REAL-WORLD IMPACT

• The FBI reports phishing is the #1 cybercrime in the U.S., with billions of messages sent daily.

• BMO Bank, as one corporate example, currently blocks 150,000-200,000 phishing emails per month targeting employees... a representative says the problem is escalating: "The numbers never go down, they only go up."

• Cybersecurity experts state criminals are already using A.I. for faster, more sophisticated phishing campaigns.

IMPLICATIONS FOR THOSE OF US IN THE AI INDUSTRY

• LLM misuse is an industry-wide challenge affecting all major frontier labs.

• Reveals fundamental tension between making AI "helpful" vs. "harmless", highlighting the need for more robust safety guardrails across AI systems.

KEY TAKEAWAYS

• For A.I. Builders: Keep security implications front and center when developing applications.

• For users: The same LLMs that helps you write emails can help bad actors craft convincing scams... stay vigilant and educate vulnerable populations (e.g., seniors) about A.I.-enhanced phishing threats. They're only going to get more and more compelling and frequent.

The SuperDataScience podcast is available on all major podcasting platforms, YouTube, and at SuperDataScience.com.