Ilan Peleg is the Co-Founder and CEO of Lightrun, the autonomous remediation platform built to debug and fix software problems before they ever reach a customer. Lightrun is one of the fastest growing companies in the AI observability space, having raised $110 million from elite venture firms including Accel, Insight Partners, and Sorenson Capital. Its technology now runs inside mission critical systems at Apple, Salesforce, Citibank, and the New York Stock Exchange.

Before founding Lightrun, Ilan spent years as a software developer, watching code succeed in testing and then fail in ways no one could predict once it met real users at scale. That frustration became the founding thesis for a company built around a bold idea: self healing software.

In this episode, Ilan draws on his experience building line level, real time telemetry for some of the world’s most demanding production environments to make the case that AI reliability depends on grounded evidence, not bigger models, and that the future belongs to practitioners who know how to work with it, not around it.

In this conversation, we discuss:

• How AI agents shift software debugging from reacting to outages to preventing them before they ever reach production
• Why site reliability engineers are being asked to rethink their entire relationship with automation and manual firefighting
• The difference between AI workflow automation startups and the ones that will actually survive the next platform shift
• What actually happens when an AI agent doesn’t have the grounded evidence it needs to complete a task correctly
• Why a founder chose to keep his AI observability platform read only, even when customers asked for more autonomy
• The architectural bet behind real time, line level telemetry that makes self-healing software possible at enterprise scale

Explore the Conversation

00:00 Intro and Fun Fact

04:21 Introducing Ilan Peleg

04:52 The Lightrun Origin Story

08:32 Software in an AI Era

10:38 Tracing Code in Real-Time

18:08 Shifting Left Observability

20:19 Scaling Self-Healing Telemetry

25:39 Why Lightrun Stays Read-Only

29:23 Can AI Labs Replace It

32:26 SREs in an AI World

35:15 People Over Product

36:32 Early Days in Herzliya

39:37 Closing and Connecting

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Ilan Peleg on LinkedIn
• AI fun fact article: Precision Proactivity: Measuring Cognitive Load in Real World AI Assisted Work
• On How Meredith Broussard, NYU professor and featured expert in Coded Bias, is confronting the social implications of AI 

Nancy Wang is the Chief Technology Officer at 1Password, where she leads the global engineering team securing the digital safety and identities of millions of prosumers, families, and enterprise workloads.

An expert in building highly scalable systems and data protection platforms, she holds seven patents in cloud infrastructure and serves on the boards of early-stage cybersecurity leaders, including Observo AI, which was recently acquired by SentinelOne to power the data intelligence layer for its SIEM products.

Prior to joining 1Password, she became the youngest person ever promoted to Director and General Manager at AWS, at age 31, leading AWS Data Protection to serve 98% of the Fortune 500 and building a multi-billion dollar business within five years.

She also helped build cloud and data protection products at Rubrik, held engineering roles at Google and in the U.S. intelligence community, and now brings a rare combination of deep infrastructure expertise and security-first product thinking to the age of AI agents.

In this episode, Nancy sits down with Dan to explore the massive security responsibilities of the agentic era.

In this conversation, we discuss:

• Why the transition to autonomous AI agents doesn’t require brand-new credentials, and how familiar principles of human and machine identity extend to the agentic era.
• How a proprietary confidential computing architecture built on specialized enclaves protects sensitive user data, even in the event of a catastrophic central breach.
• Why 1Password actively chose not to release a public Model Context Protocol (MCP) server despite intense market pressure.
• How a specialized DevOps agent trained on human incident response can learn to navigate real-time outages, runbooks, and cloud traffic monitoring.
• Why AI is compressing the cost of execution in software, and why the real career advantage now shifts toward taste, judgment, systems thinking, and deep fluency with AI tools.
• Why prioritizing potential and tenacity over traditional resumes is the key to building diverse engineering teams, and how sponsorship accelerates the rise of high-slope talent

Explore the Conversation

00:00 Intro and AI Fun Fact: EvilToken and the Rise of AI-Driven Phishing

03:48 Introducing Nancy Wang, CTO at 1Password and AWIT Founder

09:07 Secure by Design: Inside the Origin Story and Expansion of 1Password

13:32 The Business of Trust: Why 1Password Is in the Security and Relationship Game
15:31 Zero-Knowledge Architecture: What Actually Happens if 1Password Faces a Breach?

24:06 The Phishing-Resistant Future: Biometrics, Passkeys, and Agent Identity

28:17 Inside the Machine: DevOps Agents and Real-Time Incident Response

31:22 Rejecting the MCP Server: Why AI Safety Trumps Instant Velocity

34:28 The T-Shaped Engineer: Why AI Compresses Execution and Elevates Human Taste

39:18 Be a High Sloper: Sponsoring the Next Generation of Tech Leaders

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Nancy Wang on LinkedIn
• AI fun fact article: Hackers use AI to bypass passwords in large-scale phishing attacks 
• Other episodes mentioned on the show:
  • Episode 167 with Amr Awadallah, CEO of Vectara and co-founder of Cloudera, on the tech behind AI search

Russ Fradin is the co-founder and CEO of Larridin, the enterprise AI measurement platform that raised $17 million in seed funding led by Andreessen Horowitz, with Bloomberg Beta and Gradient Ventures. Larridin sells to CIOs and CFOs, and answers a question most companies still cannot answer for themselves: which AI tools are being used, by whom, at what level of proficiency, and where they are actually driving productivity.

A veteran Silicon Valley entrepreneur with three decades of experience leading high-growth technology companies, Russ previously co-founded and served as CEO of Dynamic Signal (now Firstup), Adify, and SocialShield, and was the first employee at Flycast, one of the internet’s pioneering ad networks.

In this episode, Russ sits down with Dan to share the brutal and beautiful realities of building companies in the Bay Area. Tune in to hear his seasoned perspective on why successful AI integration requires ancient change management principles rather than new software licensing, the operational gap between power users and passive users, and why the most at-risk professionals in the AI era are not the ones you think.

In this conversation, we discuss:

• Why a third party measurement company shows up every time money floods into a category, and what that pattern predicts for enterprise AI.
• What actually happens after you deploy AI to 3,000 employees, and why the gap that opens up is a change management problem, not a technology one.
• Why revenue growth cannot tell you whether to renew a multimillion dollar AI contract, and why the vendor’s own numbers will not either.
• What the stark division between organizational power users and casual users reveals about the actual bottleneck in modern workplaces
• Why token-spend leaderboards can accelerate adoption, and why they become unsustainable once employees learn how to game them.
• What the reality of task automation means for the future of knowledge work, and why the threat to specific white-collar roles is often misunderstood

Explore the Conversation

00:00 Intro and AI Fun Fact: Beyond Job Replacement, How AI Can Improve Work

03:32 Introducing Russ Fradin, Co-Founder and CEO of Larridin

05:38 Startup Humility: Why Early Failure Is Essential for Founders

08:55 Startup Alchemy: The Absurdity and Ambition of Building a Company

11:01 The Larridin Vision: Building the Unbiased Measurement Layer for Enterprise AI

17:14 Beyond AI Security: Measuring Usage, Spend, Productivity, and Workflows

19:43 AI ROI Beyond Revenue: Measuring Productivity, Renewal Decisions, and Change Management

26:12 Blazing Trails: How Facebook Speedran Adoption with Token Leaderboards

34:09 What We Measure Shapes AI’s Impact on Growth, Costs, and Jobs

38:50 AI Replacement Theory: Why Tasks Change, but Most Knowledge Jobs Endure

46:07 Where to Connect with Russ Fradin and Learn More About Larridin

Resources

Subscribe to the AI & The Future of Work Newsletter

Connect with Russ on LinkedIn

AI fun fact article: Labor Market Impacts of AI: A New Measure and Early Evidence by Anthropic

On Making AI Smarter Without Harming Humans

Every August 12, the world observes International Youth Day, and this past July 15 marked World Youth Skills Day. Both are good moments to remember what we owe the people entering the workforce: paths, tools, and advice that inspire them, not warnings that scare them.

In this special August compilation episode of AI and the Future of Work, we bring back four former guests whose conversations point to the same idea: AI is not a threat. It is an opportunity, and the people starting their careers right now hold an unfair advantage. They have not spent years absorbing policies and habits that are already obsolete, so they get to begin from what is possible instead of unlearning what used to be true.

From building AI into daily work, to leadership teams learning from their newest employees, to understanding what becomes more valuable when AI makes creation easier, this episode explores how the next generation is approaching work differently.

The conversations point to a broader shift: as AI takes on more of the repetitive work and makes production cheaper, human judgment, creativity, curiosity, taste, intention, and the ability to identify the right problems become more important.

Featured Guests

• Kourtney Cross, Business Analyst at Leidos and ServiceNow Rise Up graduate. Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/18741521]
• Andrea Iorio, Keynote Speaker and Author of Between You and AI, formerly Chief Digital Officer at L’Oreal Brazil. Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/18662632]
• Jake Saper, General Partner at Emergence Capital. Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/18982636]
• Matt Britton, CEO of Suzy and Author of Generation AI. Listen to the full conversation here: [https://www.buzzsprout.com/520474/episodes/18792172]

What You’ll Learn

• How an analyst early in his career built AI into his daily work, and why he went looking for it before anyone handed it to him
• What it takes to make your work visible when you are just starting out
• How reverse mentoring puts the newest employees in the room to teach the leadership team what it is missing
• What a workday looks like once these tools handle the repetitive parts, and how to reinvest the time that comes back
• Why AI can democratize creation while making taste, intention, trust, curation, and point of view more valuable
• Why “which tool should I use” is the least interesting question, and what rises in value once memorizing information stops being the point

Inspired by something you heard in this episode?

Share your favorite insight about learning, curiosity, or the ideas shaping how work gets done, and tag us on social.

And don’t forget to subscribe to AI and the Future of Work for more conversations with the leaders shaping the future of work.

Other special episodes:

• SE 19: AI and Education: How Artificial Intelligence Is Transforming Learning (International Day of Education Special Episode)
• Lessons from Four Unicorn CEOs Disrupting Massive Markets with AI (Special Episode)
• Artificial General Intelligence: Can Machines Really Think Like Us? (Special Episode)
• Ethical AI in Hiring: How to Stay Compliant While Building a Fairer Future of Work (HR Day Special Episode)
• AI and the Law: How AI Will Change Legal Careers (Special Episode)
• AI and Safety: How Responsible Tech Leaders Build Trustworthy Systems (National Safety Month Special)
• Lessons from Leaders: How AI Is Redefining Work and the Human Experience (Labor Day Special Episode)

Dr. Ben Goertzel is the researcher most often credited with popularizing the term “Artificial General Intelligence,” a phrase he helped bring into wide use when he co-published a book under that title in 2005.

He is the founder of SingularityNET and the architect behind OpenCog Hyperon, open-source cognitive architectures built on the conviction that large language models alone cannot get humanity to true AGI. His current project, ASI:Chain, is designed to put AGI systems on a decentralized blockchain infrastructure so that no single company, government, or actor can ever seize control of them. He is also the founder of BGI Labs, an organization focused on developing decentralized, democratic, and Beneficial General Intelligence (BGI).  

In this episode, recorded live at the AGI-26 Conference, Ben draws on nearly four decades of AI research, from coding neural nets as a teenager to building today’s neuro-symbolic systems, to make the case that the biggest risk in AGI is not the technology itself, but who ends up holding the switch.

In this conversation, we discuss:

• Why statistical large language models cannot achieve true strategic planning on their own, and the critical cognitive architecture they are missing.
• How a hybrid, neural-symbolic architecture tackles a critical flaw in modern AI agents, preventing them from losing track of their own goals mid-task.
• What the shift toward decentralized AGI on a blockchain accomplishes, and why distributing it across global nodes is designed as a safeguard against centralized control.
• How emerging brain-computer interfaces will redefine how we experience consciousness, and what happens when human brains “Wi-Fi” directly into machine memory.
• Why Ben sees a beneficial AGI as a way to offset humanity’s “chimp-level” ethical limitations when managing advanced weaponry.
• What the accelerating “Singularity is Near” vibe feels like on the ground today, and the recent milestones that have him convinced we’re closer than ever.

Explore the Conversation

00:00 Meet Ben Goertzel: Recording Live at the 19th Annual AGI Conference
01:36 The Prometheus Project: The 1960s Books That Saw the Intelligence Explosion Coming
04:51 A Geek and a Freak: Quantum Mechanics at Seven and Coding AI on 16K of RAM
10:17 What Is a Human: Would the Stone Age Recognize Us With Ear Pods and AI Girlfriends?
14:49 Fake Consciousness: The Scenario Where Humanity Steps Aside for Minds That Feel Nothing
21:27 Why Ben Pursues AGI: From Time Machines and Brain Upgrades to AI for Good
28:15 LLMs Are Not Adequate: What They Leave Out and Why Stacking Tools Around Them Fails
37:24 Decentralized AGI: 100 Server Farms, 20 Countries, and Cryptographic Laterality
43:56 The End State for SingularityNET: Putting AI on Chain and Building Beneficial AGI
46:53 You Can Feel the Acceleration: Legacy, Timelines, and Why None of Us Should Fully Trust Ourselves
52:04 Closing: The Most Important Conversation for All of Humanity

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Dr. Ben Goertzel on LinkedIn

Theresita Richard is Chief People and Culture Officer at Patagonia, where she is approaching her third anniversary with the company. Before Patagonia, she built her career across some of the most recognized names in retail, including Home Depot, Target, Starbucks, and Nordstrom, after starting out as an industrial engineer leading a two-year project on how new technology was reshaping manufacturing work.

At Patagonia, Theresita carries the responsibility of stewarding a culture built around a single, deceptively simple mission: to be in business to save the home planet. That means holding the tension between profit and purpose in every decision, and now, figuring out where AI fits into a company that has always insisted on doing things the harder, more human way.

In this episode, Theresita draws on a career that began in manufacturing automation and has led her to guard the soul of one of the most purpose-driven companies in the world, to argue that AI will not fix a broken culture. It will only reveal it, and the responsibility to get that right has never been more real.

In this conversation, we discuss:

• Why Patagonia evaluates potential hires based on purpose alignment rather than culture fit, and how the company builds an environment where people stay for a reason, a season, or a lifetime.
• How Patagonia’s “pair clarity with choice” principle lets culture self-select who belongs, without anyone having to enforce it.
• Why AI does not create new problems inside a company, and why AI will always amplify the cracks and biases already present in our foundations.
• Why enlightened leadership in a rapidly shifting technological landscape requires extreme vulnerability, community building, and the courage to sit with difficult questions.
• How the conversation around AI in the workplace must shift from driving pure efficiency to genuinely nourishing the human soul and promoting human flourishing.
• How a grandfather with a third-grade education taught the one skill that no shift in technology has ever made irrelevant.

Explore this conversation:

00:00 Introducing Theresita Richard: From Industrial Engineer to Patagonia CHRO

03:25 Inside Patagonia’s Culture: Life at the Anti-Corporate Corporation

04:35 The Company Has a Soul: Stewarding Patagonia’s Legacy and Its Future Stories

06:49 Made or Born Patagonian: Why Alignment Matters More Than Culture Fit

09:36 In Business to Save Our Home Planet: Why Profit and Purpose Are Not a Trade-Off

11:03 Pair Clarity With Choice: How Culture Self-Selects Without Enforcement

13:26 Beyond HR as Compliance: Nourishing the Human Soul at Work

15:48 The Ground Is Shaking: Why AI Cannot Be a Conversation About Efficiency Alone

19:52 Ally or Adversary: Honest Conversations About What Gets Automated and Augmented

22:23 Two Approaches to Leadership: Vulnerability, Community, and Sitting With the Questions

25:47 Measuring AI: Why It Reveals the Cracks in Your Foundation

28:27 Not What AI Can Do but What It Should: Bias, Guardrails, and Safe-to-Fail Experiments

33:04 The Racist Soap Dispenser: What Meredith Broussard’s Work Reveals About AI Bias

36:37 Willie and Pearl: The Origin Story Behind Following the Question

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Theresita on LinkedIn
• Other episodes mentioned:
  • Meredith Broussard, NYU professor, AI ethics authority, and featured expert in Coded Bias, discusses the social implications of AI

Wade Foster is the CEO and co-founder of Zapier, the workflow automation and AI orchestration platform used by more than 4 million people to connect over 7,000 work apps. Since launching in the Y Combinator Summer 2012 batch, Zapier has automated more than 81 billion tasks, users have built more than 25 million Zaps, and the company has bootstrapped its way to a valuation north of $5 billion.

He holds degrees in industrial engineering and business administration from the University of Missouri, and has spent more than a decade on a single problem: making the tools people work in every day work for them instead of against them. He is also one of the show’s rare repeat guests. His first conversation with Dan was in January 2024, back when coding agents mostly did not work.

In this episode, Wade draws on running the automation layer that sits between thousands of enterprise tools to argue that the frontier model leap of late 2025 handed every knowledge worker an engineer, and that the companies still waiting on returns are the ones that never changed how the work itself gets done.

In this conversation, we discuss:

• Why the late 2025 model leap means every knowledge worker now has an engineer, and what that changes about ordinary work.
• Where deterministic workflows still beat AI at work, and why the most sophisticated teams refuse to choose between the two.
• What happens when white collar workers start pasting API keys into files, and the third option most security leaders are missing.
• Why Wade says culture, not tooling, is the real constraint, and what leaders get wrong when the board demands AI first.
• Why individuals report real AI gains while their organizations report none, and what has to be rethought before that gap closes.
• How Zapier built its AI Fluency Framework from its own teams, and why version one was already dated the day it shipped.

Explore this conversation:

00:00 Welcome to Episode 400

02:01 AI Fun Fact: Is Agentic AI the End of SaaS Tools?

04:35  Introducing Wade Foster: How Zapier Bootstrapped to 81 Billion Automated Tasks

06:01 From Coding Agents That Kind of Worked to an Engineer for Every Knowledge Worker

07:53 What Zapier Does Today: Deterministic Workflows Meet Non-Deterministic AI

11:12 Hybrid Workflows: Build It With AI, Run It Like a Program

13:30 MCP and the Orchestration Layer: API Keys, Agent Harnesses, and the Daily Recap

20:23 The Third Option for CISOs: Governing AI Agents Without Saying No

24:00 Foot Guns and Default Settings: The Product Judgment Behind Agent Permissions

27:03 Accountability When Software Is No Longer Deterministic: Evals and Spec Adherence

28:34 AI Strategy Office Hours: Why Individual AI Gains Are Not Becoming Institutional ROI

33:03 The Zapier AI Fluency Framework: Why Version One Was Dated on Arrival

36:15 Looking Ahead to 2028: The Hive Mind Company and a New Management Playbook

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Wade on LinkedIn
• AI fun fact article
• On How One Good Decision Made Thomas Otter The Accidental HR Tech Pioneer

Vasant Dhar teaches data science at NYU’s Stern School of Business and has spent more than 45 years at the frontier of artificial intelligence. He brought machine learning to Wall Street in the 1990s and founded SCT Capital Management, one of the first machine learning based hedge funds.

He hosts the Brave New World podcast, downloaded more than a million times, where he has interviewed Nobel laureates, technologists, and global thinkers on the implications of AI. His work has appeared in The New York Times, The Wall Street Journal, Financial Times, Wired, and MIT Technology Review. His latest book, Thinking with Machines, traces AI from its origins to the present.

For more than forty years, Vasant has built systems that sat right on the edge of human trust. People had to decide whether to rely on them or walk away.

In this episode, he makes a stark claim: AI will not just change how we work; it will sort us into two groups. One uses it to extend their judgment. The other slowly hands that judgment over. The gap comes down to habits you are forming today, not some distant future.

In this conversation, we discuss:

• Why trusting AI comes down to just two variables, and the simple test Vasant has applied since his Harvard Business Review piece a decade ago
• The bifurcation Vasant believes AI is about to create, splitting humanity into two groups, and which side you do not want to be on
• What tennis great Roger Federer’s win rate reveals about succeeding with algorithms, and the counterintuitive math behind every winning edge
• Why the edge returns to humans the moment everyone runs the same algorithms, and what only people can do in situations no system has seen
• The one word in the title Thinking with Machines that Vasant says matters most, and what it asks of how we work alongside AI
• The areas of life where Vasant argues we may need to restrict AI entirely, and the legal framework we already have to govern it

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Vasant on LinkedIn
• AI fun fact article
• On the decision sprint process with Atif Rafiq, CEO & Bestselling Author

Ariel Assaraf is the CEO and co-founder of Coralogix, a leading observability platform that most recently raised $115 million at a unicorn valuation. He started the company in 2014, and today Coralogix serves more than 4,000 customers, monitors more than 500,000 applications, and processes over 3 million events per second.

Before co-founding Coralogix, Ariel served in Israel’s Elite Intelligence Unit 8200, where the sheer scale and complexity of data he worked with made one thing clear: existing architectures weren’t built for what was coming. He later joined Varent Systems, a homeland security company, leading automation, integration, and QA.

In this episode, Ariel draws on more than a decade of building at the frontier of data infrastructure to argue that observability is no longer just a tool for preventing downtime. It is becoming the most truthful, real-time source of intelligence any company owns.

In this conversation, we discuss:

• The evolution from the data collection era (“oil phase”) to a landfill crisis, and now the AI-driven “brain phase” where telemetry has become the most valuable raw material for business decision making
• How Coralogix separates the data plane from the control plane, storing data in open format on the customer’s own infrastructure to enable data ownership, infinite retention, and freedom from vendor lock-in
• Why Ariel invested over $100 million in R&D to build query engines that always return answers, not constrained by predefined schemas that agents will quickly exceed
•  How SREs evolve from reactive incident responders into autonomous operators as agents like Ollie, Coralogix’s AI agent, take over incident triage, root cause analysis, and narrative generation
• The emerging role of the AI-forward product manager who sits between customer needs and autonomous agents, reshaping how software gets built, priced, and sold in real time
• How Ariel thinks about linear versus exponential impact as a leadership principle, and why the intuition to prioritize exponential value is something agents will never replicate

Explore more in the conversation:

00:00 Welcome & AI’s societal impact paradox

01:53 AI Fun Fact: New data on productivity and employment

04:15 Introducing Ariel Assaraf and the Coralogix origin story

05:15 Evolving data architecture: from oil to landfill to brain phase

07:28 Coralogix’s data ownership and open format advantages

13:27 From telemetry data lake to autonomous, agent-driven analytics

20:00 Building scalable, answer-guaranteeing query engines for complex data

25:44 The future of natural language interfaces like Olly for SREs and DevOps

28:15 Orchestrating multiple AI agents for better decision-making

30:20 Responsibility, autonomy, and the evolving role of customer success

35:37 How Coralogix turns telemetry into strategic business decisions

38:18 Linear vs. exponential value in your career

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Ariel on LinkedIn
• AI fun fact article
• On How Personalized Healthcare Is Being Transformed Through AI and the Human Microbiome

Maryjo Charbonnier is the former CHRO and Executive Advisor at Kyndryl, the world’s largest provider of IT infrastructure services , with more than 70,000 employees across roughly 60 countries. When Kyndryl was spun out of IBM in 2021 as one of the largest public company spin-offs in history, Maryjo helped build its culture and people strategy from the ground up, which is why she and others have called it the world’s largest startup.

She has spent nearly two decades as a public company CHRO on both sides of the Atlantic, including Wolters Kluwer (traded on the Dutch exchange) and Broadridge Financial Solutions, after a formative run at PepsiCo where she led change management for Frito-Lay. She was named CHRO of the Year in the Netherlands and earned her MBA at Southern Methodist University.

In this episode, Maryjo draws on a career spent leading messy transformations and building a 70,000-person workforce to argue that as AI automates tasks and chunks of jobs, the work that defines a career is moving from what you know to how you judge, lead, and decide, and most organizations are not teaching for it yet.

In this conversation, we discuss:

• Why Mary Jo “seeks the heat” in messy transformations and what she learned leading HR through turnarounds, spin‑offs, and large‑scale change.
• How Kyndryl defined the “Kindryl way” with six core behaviors and uses culture as an operating plan in the world’s largest startup.
• Why HR must focus on which skills are rare and most valuable, and how Kyndryl’s Make Yourself Discoverable campaign turned skills into a strategic asset.
• How AI-powered career profiles, skills-based redeployment, and role-specific AI curricula were intentionally designed to show Kyndryls that AI is an asset to their career, not a threat to it.
• Why Mary Jo believes HR has three roles in AI, including reshaping commercial work and building an AI governance council that balances speed with risk.
• How leadership “ORE” (job design, risk management, empathy) and human skills like change management and people leadership will define careers in an AI‑enabled workplace

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Maryjo on LinkedIn
• AI fun fact article
• On How Rory O’Driscoll Explains Success Modes for AI Companies and Three Essential Startup Strategies
• Episode with Keith Sonderling, then an EEOC Commissioner and now the U.S. Deputy Secretary of Labor

Trond Undheim is a futurist, innovation expert, and research scholar at Stanford University whose work spans governments, startups, and leading academic institutions. His ideas have been featured in outlets including Forbes, The Boston Globe, Fast Company, Fortune, and MIT News, and he previously hosted the Futurized podcast.

He holds a PhD in AI and cognition from the Norwegian University of Science and Technology and is the author of eight books, including The Platinum Workforce, which explores how to train and hire for the twenty-first century’s industrial transitions.

In this episode, Trond draws on decades of interdisciplinary work on emerging technologies, systemic risk, and workforce transitions to argue that system awareness, not traditional knowledge, will determine who thrives in an AI-defined economy.

In this conversation, we discuss:

• Why Trond says knowledge has become superfluous, and what that claim means for how we define expertise in an AI era.
• Why cutting junior hires to cash in on AI efficiencies bakes a failure mode into your organization.
• What “system awareness” looks like in practice, and how it changes the way leaders think about skills and careers.
• Why socio-technical thinking matters, and how treating humans and machines as mutually constitutive systems reshapes AI design and governance.
• Why humanity is unprepared to operate at gigascale, and what megaproject research suggests about the cost of that gap.
• How The Platinum Workforce maps twelve durable skill domains, from socio-technical capabilities to maker and maintenance skills, that will outlast multiple AI waves.

Explore this conversation:

00:00 Intro and AI Fun Fact: Pew Research Americans More Concerned Than Excited About AI

04:22 Introducing Trond Undheim, Futurist and Author of The Platinum Workforce

05:09 Why the Workforce Is the Single Biggest Lever for Human Survival

09:08 System Awareness: The Only Knowledge That Matters in the AI Era

15:06 Socio-technical Systems: Co-Evolution of Humans and Technology

17:54 Human Agency Over Technology: Who Really Sets the Rules

23:24 The Human Skills AI Cannot Replace: Making, Maintaining and Place Maximizing

31:12 Workforce Preparation for the AI Era: Training Juniors and Experimentation

34:08 Macro Challenges: Giga-Scale Projects and Management at Scale

45:33 The Augmented Workforce: What AI Integration Must Look Like in 10 Years

54:39 Where to Connect with Trond Undheim and Learn More About The Platinum Workforce

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Trond on LinkedIn
• AI fun fact article
• On How AI Will Transform Tax Filing: Insights from Daniel Marcous, Founder and CTO of April and Former CTO of Waze

Lev Gonick is the CIO at Arizona State University, one of the largest and fastest-growing universities in the United States, with over 200,000 students across campuses in Phoenix, Los Angeles, Washington, and 35 partner institutions around the world. He won an ORBIE Award in 2023 as a top large Enterprise CIO, was named a Top 50 Educational Technology Influencer by EdScoop in 2022, and holds a PhD in International Political Economy from York University.

Before joining ASU, he was one of the rare CIOs who came from the classroom, having spent the first decade of his career as a teacher and researcher before pioneering online learning in the 1990s, long before it became an industry. 

In this episode, Lev draws on more than 40 years at the intersection of technology and education to make the case that AI is not the disruptor of higher education, it is the accelerant, and that the institutions treating it that way are already building what everyone else is still debating.

In this conversation, we discuss:

• Why AI is not the disruptor of higher education, and what has actually been driving the disruption for decades
• How ASU went from survival mode during the 2009 financial crisis to building the largest online learning operation in the country, and why the same instinct is now driving its AI strategy
• What ASU’s data from 200,000 students using AI daily actually reveals about which skills will endure and which ones will not
• How the role of university faculty is fundamentally changing in the AI era, and why the hardest question has nothing to do with cheating
• What the “Agentic self” means for creatives, and how a unique course taught by Will.i.am is helping students protect and amplify their creative futures.
• How the traditional responsibilities of the Chief Information Officer are expanding beyond basic operations to actively shaping institutional strategy and innovation.

Explore this conversation:

00:00 Intro and AI Fun Fact: Blue Books vs AI Rethinking Academic Integrity

04:25 Introducing Lev Gonick, CIO at Arizona State University

05:17 From Classroom Teacher to Academic Disruptor at ASU

08:16 ASU Principled Innovation and the Design Build Approach to AI

13:23 Co-Creating with Industry: AWS Zoom and the GSV Summit at ASU

17:35 Soft Skills Are Smart Skills: Rethinking AI Literacy in Higher Ed

23:25 Rethinking Assessment: What Faculty Must Adapt to in the AI Era

27:01 Why a College Degree Still Matters in the Age of AI

30:37 From YouTube to ASU: Meeting Learners Where They Are

34:22 Disrupt or Be Disrupted: ASU Mission to Reach 300000 Students

35:57 From Operator to Strategist: The New Playbook for the Modern CIO

40:26 Connect with Lev Gonick and Arizona State University

RESOURCES

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Lev on LinkedIn
• AI fun fact article: Blue Books Are Making a Campus Comeback via Axios, by Josephine Walker
• On what most entrepreneurs get wrong when pitching to VCs.

Dr. Muthu Alagappan is the Founder and CEO of Counsel Health, the company automating access to high-quality, personalized medical advice from doctors. Counsel recently closed a $25M Series A led by Andreessen Horowitz and Google Ventures, following an $11M seed round that included A16Z, Asymmetric Capital Partners, Floodgate Fund, and Pear VC.

He holds an MD from Stanford Medicine and a B.S. in Biomechanical Engineering from Stanford, and was among the earliest AI researchers to publish on clinical applications of machine intelligence.

In this episode, Muthu draws on 15 years at the intersection of AI research and frontline clinical medicine to explore the shift toward semi-autonomous care.

In this conversation, we discuss:

• How AI addresses the limitations of traditional primary care by offering a highly personalized, knowledgeable, and always available medical experience.
• Why patients might leapfrog clinicians in their willingness to adopt AI for medical advice, and how this shift challenges the traditional identity of physicians.
• What semi-autonomous care actually looks like in practice, and how Counsel Health uses a clinician cockpit to augment human compassion with real-time machine intelligence.
• How to leverage population-level patterns without compromising patient privacy.
• Why the double standard applied to AI is misplaced, and why Muthu argues we should hold AI to a much higher benchmark than human doctors simply.
• What the future of global healthcare could look like when cognitive medical expertise is fully democratized, ensuring that a patient’s zip code no longer dictates the quality of care they receive.

Explore the Conversation

00:00 Intro & AI Fun Fact: Big Data Limitations and Bias in Clinical AI
03:52 Meet Dr. Muthu Alagappan: From Stanford AI Researcher to Counsel Health CEO
06:51 Why Primary Care Falls Short: The Case for AI-Augmented Medicine
09:05 Human Doctors Are Human: How Patients Are Adopting AI Medical Advice
12:20 Patient Privacy and Population Health: Learning Without Training on Data
14:17 Inside the Clinician Cockpit: Real-Time AI Support for Doctors
16:17 Why Counsel Health Employs Its Own Physicians: Messaging-Based Care
19:00 From Semi-Autonomous to Fully Autonomous Care: Healthcare’s Next Era
24:19 AI Ethics in Medicine: Safety Standards, Model Values, and Data Ownership
27:22 The AI Double Standard: Why Machines Deserve a Higher Benchmark Than Doctors
31:07 Founder Lessons: Building a Category-Defining Healthcare AI Company
33:53 Rewriting the Commencement Address: Medicine as Lifelong Learning
35:37 Where to Connect with Dr. Muthu Alagappan and Counsel Health

Resources

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Muthu on LinkedIn
• AI fun fact article: Artificial Intelligence in Health Care: The Ethical Frontier via Conexiant
• On future of AI, Silicon Valley and Venture Capital 

In this special compilation episode of AI and the Future of Work, we are bringing you four conversations recorded live on the show floor at HumanX 2026. This is the second and final compilation of our three-part HumanX Live series.

Our first compilation explored how AI amplifies the human potential it can never replace. This one turns to the technical side, and to a question that gets harder the more these systems touch our lives: how do you build AI you can actually trust not to fail when it matters most?

As technology reaches further into the moments that count (the systems that monitor our health, drive our cars, and work alongside us on the job), these four builders share how they design for accountability, safety, and harmony between people and machines.

What You’ll Learn

• Why reading code is no longer enough, and how observing real outcomes (not system metrics alone) is the only way to know whether AI is actually serving the people who depend on it
• What “AI values” are, and why companies will soon need shared norms for how people disclose, review, and engage with work produced by agentic systems
• How robots earn trust on a job site by measuring their own uncertainty, asking questions, and communicating their intentions before they act
• Why the most valuable place for automation is the dirty, dull, and dangerous work humans were never meant to do, and what that means for keeping people safe
• Why physical AI should be built first as a reasoning and communication model that can explain its thinking to people, rather than one that jumps straight to action
• How “harness engineering” moves teams beyond prompt and context engineering, and why orchestrating several frontier models together can outperform any single one

Featured Guests

• Christine Yen, CEO and Co-Founder of Honeycomb. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19362645
• Dr. Ali Agha, CEO and Co-Founder of FieldAI. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19362711
• Dr. Jaime Lien, Co-Founder & Chief Scientist of Archetype AI. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19363341
• XD Huang, Chief Technology Officer of Zoom. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19363454

Dan Roth is the Editor in Chief and a Vice President at LinkedIn, where he has led the world’s largest professional editorial operation since 2011. Business Insider once called him the most powerful business journalist on the internet, and over more than a decade he has helped turn LinkedIn from a networking site into a global media platform, building out its editorial team, top voices, and Influencer Program. He also hosts the popular This Is Working podcast.

Over 15 years watching professionals navigate every major shift in the workplace, from the rise of social media to the agentic AI era, Dan has developed a clear and counterintuitive view of what actually drives a durable career. In this episode, he draws on LinkedIn’s data from over a billion members to make the case that the skills employers are hunting for right now are not the ones most professionals are building, and that the gap between what AI can produce and what humans can offer is closing faster than anyone is prepared for.

In this conversation, we discuss:

• Why AI has commoditized knowledge itself, and what professionals actually come to LinkedIn for that no chatbot can give them
• What separates content that spreads beyond your network from content that stays stuck inside it, and what LinkedIn’s systems are really looking for
• Why AI is a great tool for getting your voice out, and the exact moment it starts working against you instead
• The mindset Dan drills into his team about passion and failure, and the one thing he says you are never allowed to get wrong
• How a mission-driven company resists the pull to chase clicks and ad revenue, and what Dan’s old-world instincts taught him to unlearn
• The two categories of skills surging in demand right now, and why the second list is the one most people overlook

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Daniel on LinkedIn
• AI fun fact article
• On How AI is making networks smart
• Other episode mentioned in the show: 315: Tony Stubblebine, CEO of Medium, On Human Curation, Subscription-Driven Quality, and Fixing the Internet

LIVE EVENT:

See how leading enterprises are using agentic AI to give employees back 4–6 productive hours every week. Join PeopleReign CEO Dan Turchin for a live demo on June 25, 2026.

Register here: https://go.peoplereign.io/live-demo-how-agentic-ai-is-being-used-by-global-enterprises

Sophia Kianni is the co-founder and CEO of Phia, an AI shopping agent with more than 1.4 million users that has raised over $43 million from an investor list that includes Kris Jenner, Sara Blakely, and Hailey Bieber. Sophia and her co-founder built the company out of their Stanford dorm room on a single thesis: in the future, every consumer will have a personal AI shopping assistant.

Sophia is also the co-host of The Burnouts, a podcast with more than 600,000 followers and over 200 million downloads. Earlier in her career, she founded Climate Cardinals, the world’s largest youth-led climate nonprofit with more than 20,000 volunteers, and became the youngest United Nations advisor in U.S. history.

In this episode, Sophia draws on her experience building high-velocity ventures before the age of 25 to challenge how founders think about feedback, team culture, content creation, experimentation, and workflow efficiency. She also makes a compelling argument for how AI should be used at work: removing friction from the parts of a workflow that drain time and energy without adding value.

In this conversation, we discuss:

• Why the intersection of social and shopping looked like a solved problem to most founders, and the gap that Sophia and her co-founder saw inside their Stanford dorm room
• How Sophia thinks about team building as company building, and the specific qualities she screens for before resumes, credentials, or experience
• How a consumer-first mindset and relentless customer feedback help Phia iterate faster and build a product users love
• Why building close to your user is still the most underrated advantage in AI, and what most founders miss when they try to scale it
• Why Phia and The Burnouts built data-oriented content engines that operate like scientific labs, testing hooks, fonts, retention curves, and B-roll as measurable variables rather than relying on creative instincts alone
• How Sophia uses AI tools like Adobe Firefly to increase workflow efficiency by removing friction from repetitive tasks, not to replace creative work, but to protect it
• The framework Sophia uses to decide whose feedback shapes her decisions and whose she treats as noise

Resources

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Sophia on LinkedIn

In this special compilation episode of AI and the Future of Work, we are bringing you four conversations recorded live on the show floor at HumanX 2026. This is the second episode of our three-part HumanX Live series.

In an era dominated by headlines about displacement and disruption, these four founders share a grounded optimism about what AI cannot replace: human judgment, creativity, and the drive to do work that matters.

Each of these leaders is building in a different space, but they arrived at the same conviction. The companies and people poised to win in the AI era are not the ones moving fastest to automate. They are the ones who understand what humans are uniquely built to do, and build systems that make space for it.

What You’ll Learn

• Why most organizations cannot answer a basic question: how does work actually get done here, and why that gap is now a strategic liability
• How AI-powered learning can shift employee development from a compliance obligation to a genuine driver of engagement
• Why storytelling will remain a human craft, and what the Pixar transition teaches us about navigating creative disruption
• The case for asynchronous AI collaboration, where systems work overnight and humans return to exercise judgment
• Why optimism about the human worker is not naive, and what the data actually shows
• How to balance AI use cases that replace humans with those that create new value and grow the economy

Featured Guests

• Jennifer Smith, CEO & Co-founder of Scribe. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19257070
• Robin Daniels, Chief Business Officer at Zensai. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19257107 
• Jon Snoddy, CEO of Operative Games. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19257113
• Florian Douetteau, CEO of Dataiku. Listen to the full conversation here: https://www.buzzsprout.com/520474/episodes/19257131

Andrew Palmer is a long-time editor and columnist at The Economist, where he writes the widely read Bartleby column on work and life. He also hosts Boss Class, one of The Economist’s most popular podcasts, whose most recent season explored generative AI in the workplace, a topic Andrew approached not just as a journalist, but as a self-described unsophisticated user determined to get smarter by doing.

In this episode, Andrew draws on his reporting and interviews with leaders across industries to offer an outside-in view of where AI adoption actually stands, and why the gap between the hype and the reality is not a sign of failure, but of how complex change really is.

In this conversation, we discuss:

• Why AI adoption faces three distinct barriers (behavioral, technical, and organizational) and why solving one without the others leaves productivity gains stranded.
• Why structural reskilling frameworks (like Denmark’s flexicurity model and Singapore’s voucher-based lifelong learning system) offer a more credible response to AI disruption than waiting for policy to catch up.
• Why Johnson & Johnson’s “let a thousand flowers bloom” approach to AI experimentation produced a Pareto effect (15% of projects generating 85% of value) and what they changed as a result.
• How the AI productivity boom is real at the individual level but not yet showing up in aggregate data, and why Andrew believes that gap is a question of time, not technology.
• Why enlightened corporate leadership requires transparency about potential job disruption and a commitment to adjacent career planning rather than performative optimism.
• What work in 2036 might look like, and why Andrew’s most unsettling prediction has nothing to do with jobs, and everything to do with privacy.

Explore this conversation:

00:00 Introduction to AI and the Future of Work episode 391

01:14 AI fun fact: AI legislative speed versus technological advancement

03:51 Meet Andrew Palmer The Economist Bartleby Column Boss Class

06:14 Digital Doppelganger and AI Personality Traits

07:57 AI Adoption Barriers Behavioral Technical and Organizational

11:01 AI Impact at Work Startups vs Large Organizations

14:15 Leadership Humility and AI Uncertainty in the Workplace

17:41 AI Experimentation at Scale Lessons from Johnson and Johnson

24:26 AI vs SaaS Productivity Data and the Speed of Adoption

27:35 Balancing AI Automation with Human Meaning at Work

31:26 AI Policy Reskilling and Lifelong Learning for the Future

36:03 Work in 2036 AI Monitoring Privacy and Constant Surveillance

38:47 Who Really Controls AI and What That Means for Workers

44:08 Connect with Andrew Palmer and Boss Class The Economist

Resources:

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Andrew on LinkedIn
• AI fun fact article
• On How Arvind Jain Is Shaping the Future of Enterprise Search 
• Another episode mentioned in the interview: How we can take back control from Big Tech with Tom Wheeler, former FCC Chairman, CEO, VC, and author of Techlash.

Arnnon Geshuri is Chief People Officer at Snowflake, where he leads culture development, talent strategy, and organizational design at one of the world’s leading data cloud companies. His career spans decades of scaling high-growth technology organizations, including leadership roles at Google, Livongo Health, and Tesla, where he oversaw its growth from a 400-person startup to a 35,000-person transportation juggernaut.

Throughout his career, he has consistently chosen companies that demand a people function as innovative, as creative, and as forward-thinking as the business itself. And across every role, he has focused on one core idea: the people function must evolve as fast as the business itself, grounded in data, experimentation, and trust.

In this episode, Arnnon draws on that experience to challenge how leaders think about AI in the workplace, arguing that the real opportunity is not automation alone, but redefining how humans contribute, decide, and grow inside modern organizations.

In this conversation, we discuss:

• Why the people function must speak the language of data and analytics to influence engineering-led organizations and earn credibility in high-growth, technical environments
• The shift from transactional HR to a strategic role focused on connection, education, and rebuilding trust after workforce disruption and disconnection during COVID
• How Snowflake frames AI adoption by automating repetitive work, augmenting creative tasks, and preserving human judgment in decisions that require empathy and context
• Why employees adopt AI faster when leaders encourage curiosity, remove fear of experimentation, and make tools accessible through simple interfaces like natural language
• The risks of over-automating decisions like hiring and performance reviews, and why removing human accountability breaks trust inside organizations
• How building a culture of experimentation, measurement, and iteration allows people leaders to scale organizations without relying on intuition alone

Explore the Conversation

00:00 Intro & Fun Fact: How AI manipulation threatens autonomy

05:06 Meet Arnnon Geshuri: CPO at Snowflake, from Google, Tesla, and Livongo Health

10:24 The Evolution of HR: From Transactions to Amplifying Humanity

13:37 Snowflake’s AI Framework: Automate, Augment, and Preserve Human Judgment

21:44 Driving AI Adoption: AI for Everybody and a Culture of Experimentation

26:26 Data Privacy and Trust: Building Guardrails for Enterprise AI

28:36 AI in Hiring: Mitigating Bias to Rescue Human Connection

32:28 Setting AI Boundaries: Why Algorithms Should Never Conduct Performance Reviews

34:16 Scaling Culture in Hyper-Growth: The Power of People Analytics

41:33 The AI Ride-Along Prediction and What Comes Next

43:15 Where to Connect with Arnnon Geshuri and Snowflake

Resources

• Subscribe to the AI & The Future of Work Newsletter
• Connect with Arnnon on LinkedIn
• AI fun fact article
• On How Rodrigo Liang, Raised Over $1B to Build the First Generative AI Unicorn

In this special episode of AI and the Future of Work, we are bringing you an exclusive conversation recorded live on the show floor at the HumanX 2026 event. This full interview kicks off a special three-part series, with the upcoming two episodes releasing in a compilation format. To start things off, we are sharing our uncut conversation with the man who made this entire gathering possible.

Stefan Weitz is the Co-founder and CEO of HumanX, an organization and premier event dedicated to cutting through the AI hype to find practical, world-changing applications. He joined Microsoft in 1996, working alongside leaders like Bill Gates and Steve Ballmer on iconic product launches and foundational tech like Bing and Windows.

In this live episode, Stefan draws on his extensive product development background to explain why our survival in the AI era depends on treating technology as an evolving tool and why the most powerful thing a leader can say today is “I do not know”.

In this conversation, we discuss: 

• Why relying on focus groups and lean product development is the wrong approach for building breakthrough AI hardware and software.
• The reason established tech giants risk losing the AI race if they rely solely on distribution over building superior products.
• How AI differs fundamentally from all previous human tools and why its ability to learn creates unprecedented exponential growth.
• Why the speed of current technological adaptation threatens to outpace our natural ability to transition roles and find new purpose.
• The danger of anthropomorphizing artificial intelligence and why framing it as human creates unnecessary fear and resistance.
• How saying “I do not know” has become the most powerful leadership tool in a non-deterministic technology landscape.

Resources:

• Connect with Stefan on LinkedIn