AI and the Future of Work: Artificial Intelligence in the Workplace, Business, Ethics, HR, and IT for AI Enthusiasts, Leaders and Academics

By Dan TurchinBusiness Entrepreneurship Technology Management

AI and the Future of Work: Artificial Intelligence in the Workplace, Business, Ethics, HR, and IT for AI Enthusiasts, Leaders and Academics episodes

September 14405: Nick Mehta, Former CEO of Gainsight, on Agentic Overload, Machine Consciousness, and Leading with Radical Humility
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Nick Mehta is a serial entrepreneur, executive leader, and the former longtime CEO of Gainsight, where he helped define and scale the multi-billion-dollar category of modern Customer Success.

Widely revered across the technology ecosystem as a beloved mentor and a CEO's role model, Nick pairs sharp business instincts with an infectious, human-first leadership style and an insatiable curiosity for philosophy, mathematics, and cognitive science.

In this highly anticipated annual conversation, Nick sits down with Dan for an unfiltered, cathartic deep dive into the psychological toll of the AI era.

In this conversation, we discuss:
Why the transition from passive software tools to autonomous agents triggers acute "brain fry," and the psychological friction that occurs when machines begin directing human managers.
How the anthropological framework of BANI (Brittle, Anxious, Non-linear, and Incomprehensible) explains workplace anxiety, and why the traditional fear of missing out is shifting into the cognitive strain of managing agents that demand constant input.
What Richard Dawkins' dialogue with Claude reveals about the debate between functionalists and biological essentialists, and why Nick remains skeptical of claims surrounding synthetic consciousness.
How Douglas Hofstadter's concept of "strange loops" and self-referential observation offers a powerful mental model for the future of recursive machine intelligence.
Why pursuing automation purely for commercial efficiency creates massive personal and societal opportunity costs, and how tech leaders can weigh business optimization against life-altering scientific breakthroughs.
What a tech executive's front-row seat as a parent to college seniors reveals about the job market crisis facing new graduates in business and computer science.

EXPLORE THE CONVERSATION
00:00 Welcome to Episode 404: Dan and Nick's Annual Public Therapy Session
04:34 When AI Shifts from Passive Tool to Demanding Manager
08:23 The BANI Framework: Decoding the Brittle, Anxious, and Fragmented Mind
11:05 Yelling at ChatGPT: What Our Reactions to LLM Mistakes Reveal About Us
14:25 The Consciousness Debate: Functionalism, Qualia, and Richard Dawkins' Experiment
19:22 Self-Referential Loops and the Nature of the Self
23:33 Mimicry Versus Learning in AI and Humans
29:35 The Efficiency Trap: Why Automating for Automation's Sake Loses the Plot
32:30 The Opportunity Cost of Tech: The Societal and Ethical Implications of AI Progress
37:12 The Role of Philosophy in Understanding AI and Consciousness
40:35 What Our Kids Are Facing: The Lived Reality of the 2026 Job Market
44:37 Radical Humility: Why Great Leaders Must Abandon the Visionary Facade
47:26 But What If We're Wrong? Viewing Today's Historical Phase Shift from the Future

Resources:
Subscribe to the AI & The Future of Work Newsletter
Connect with Nick Mehta on LinkedIn
Books referenced in this episode:
Gödel, Escher, Bach: An Eternal Golden Braid by Douglas Hofstadter
The Beginning of Infinity: Explanations That Transform the World by David Deutsch
But What If We're Wrong? Thinking About the Present as If It Were the Past by Chuck Klosterman
Player Piano by Kurt Vonnegut
51 min
September 07404: Ilan Peleg, CEO of Lightrun, on Shifting Observability Left, and Why He Keeps AI Agents Read-Only in Production
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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 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
41 min
August 31403: Nancy Wang, CTO at 1Password, on Why Identity Is the Tech Problem of the Decade
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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
45 min
August 24402: Russ Fradin, CEO of Larridin, on the AI Power User Gap and Why Change Management Is the Real Bottleneck
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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
04:22 Introducing Russ Fradin, Co-Founder and CEO of Larridin
06:27 Startup Humility: Why Early Failure Is Essential for Founders
09:45 Startup Alchemy: The Absurdity and Ambition of Building a Company
11:51 The Larridin Vision: Building the Unbiased Measurement Layer for Enterprise AI
18:03 Beyond AI Security: Measuring Usage, Spend, Productivity, and Workflows
20:33 AI ROI Beyond Revenue: Measuring Productivity, Renewal Decisions, and Change Management
27:02 Blazing Trails: How Facebook Speedran Adoption with Token Leaderboards
34:59 What We Measure Shapes AI’s Impact on Growth, Costs, and Jobs
39:41 AI Replacement Theory: Why Tasks Change, but Most Knowledge Jobs Endure
46:57 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
Learn more about Larridin at https://larridin.com/
AI fun fact article: Labor Market Impacts of AI: A New Measure and Early Evidence by Anthropic
On Making AI Smarter Without Harming Humans
48 min
August 20SE 27: AI and the Next Generation: What We Can Learn from Them (International Youth Day Special Episode)
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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)
25 min
August 17Dr. Ben Goertzel, SingularityNET CEO and BGI Labs Founder, on Why Stacking Tools Around an LLM Won't Get Us to AGI
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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
54 min
August 10401: Theresita Richard, CHRO at Patagonia: AI Won't Fix Your Culture, It Will Expose It
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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
43 min
August 03400: Wade Foster, Zapier CEO: What Happens When Every Knowledge Worker Gets a Coding Engine
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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
41 min
July 27399: Vasant Dhar, NYU Stern Professor, on the New Divide: Superhuman With AI or Dependent on It?
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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
Explore the Conversation

00:00 Intro & AI Fun Fact: Trustworthy AI from Principles to Practice
04:13 Meet Vasant Dhar: From the Internist System to Machine Learning on Wall Street
07:10 The Origins of Thinking with Machines: The Biggest Surprise in 45 Years of AI
09:33 Written for Everyone: AI's Accelerating Pace and the Call to Get Engaged
11:23 When to Trust an Algorithm: The Green Zone and the Human Edge
20:24 The Bifurcation of Humanity: Superhuman Amplification or Cognitive Decline
24:52 The Four Eras of Machine Intelligence: From Specification to General Intelligence
29:22 The Ethics of AI Agency: Where Machines Need Limits and Obligations
34:14 Who Governs AI: Tort Law, Liability, and Emerging Legal Precedent
37:44 AI in 2036: Multisensory Machines and the Integration of the Senses
40:33 Teaching Machines to Smell: AI, Olfaction, and Disease Detection
43:35 Where to Find Thinking with Machines and Connect with Vasant Dhar

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
46 min
July 20398: Ariel Assaraf, CEO and Co-Founder of Coralogix, on How AI Turns Observability into Business Intelligence
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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
44 min

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