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

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412: Rahul Vohra, Head of Superhuman Mail: From Onboarding Users by Hand to an AI-Native Productivity Suite Nov 02, 2026

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Rahul Vohra is Head of Superhuman Mail and the founder of the email app formerly known as Superhuman, which he led as CEO until its 2025 acquisition by Grammarly. Grammarly has since taken the Superhuman name, and the combined company is building an AI-native productivity suite across Superhuman Mail, Grammarly, Coda, and Superhuman Go to transform enterprise workflows across millions of users and over 50,000 organizations.

A computer scientist and serial entrepreneur, Rahul studied at Cambridge University before launching Rapportive, the first Gmail plug-in to scale to millions of users, which he sold to LinkedIn in 2012. He is also a prominent angel investor whose fund has invested $50 million in more than 120 companies, including Supabase, Mercury, Writer, Placer.ai, and ClassDojo.

In this episode, Rahul draws on more than a decade of building products and a front-row seat to the AI era, to ask whether more capable software leaves humans with less work or far more of it.

In this conversation, we discuss:

Why relying on traditional product launches leads to unsustainable churn, and how white-glove 1-on-1 onboarding builds a feedback loop that achieves product-market fit.
How measuring the percentage of users who would be "very disappointed" without a product provides an actionable engine for writing customer-centric roadmaps.
What Jevons' Paradox reveals about how AI automation surges overall market demand for software engineers, lawyers, and customer support practitioners.
Why the collapse of software development costs shifts long-term startup defensibility from writing code to cultivating taste, restraint, and distribution.
How uniting email, writing, and workspace tools into a proactive AI companion eliminates administrative friction while amplifying human creativity.
What executive advice for professionals facing technological disruption emphasizes about asserting personal agency to become truly AI-native.

Explore the conversation

00:00 Show intro and listener shoutout

02:06 Meet Rahul Vohra, Head of Superhuman Mail

03:21 From Cambridge and Rapportive to an AI-native productivity suite

05:26 Superhuman onboarding and early user feedback

08:44 In-person onboarding, charging from day one, and fixing every bug

11:47 Scaling the Superhuman onboarding into a go-to-market motion

15:02 What product-market fit really means: Graham, Altman, and Andreessen

18:24 The Sean Ellis test and the 40% very disappointed benchmark

20:40 How Rahul chose email as the problem to solve

25:40 Picking a startup problem in the AI era: market, taste, and distribution

28:30 What is easier and harder about building a startup today

29:46 Taste and restraint: the Burbn to Instagram story

30:52 Competition, distribution, and the incumbent advantage

32:00 Human uniqueness and a balanced relationship with AI

36:01 Jevons paradox and AI's impact on jobs

38:28 Coding agents, software engineers, and legal work

40:40 Customer support hiring in the age of AI

42:45 A prediction for 2036

44:57 Advice for workers who feel destabilized by AI

48:57 An invite for part two and where to find Rahul Vohra

Resources

Help your team turn AI tools into everyday skills with Guild AI Academy. Learn more at guild.com/ai

411: Jeremy Burton, GM of Observability at Snowflake: The Data Layer Was Never a Commodity. It’s the Whole Game Oct 26, 2026

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Jeremy Burton is the General Manager for Observability Business Unit at Snowflake following the acquisition of Observe, the developer-centric observability platform where he served as CEO. A veteran enterprise technology executive with a thirty-year career spanning Silicon Valley, Jeremy previously served as Executive Vice President of Marketing and Corporate Development at Dell, President of Products at EMC, and CEO of Serena Software, with earlier leadership roles at Symantec, Veritas, and Oracle. He has served on Snowflake’s board of directors since 2015 and sits on the McLaren Racing Advisory Board.

In this episode, Jeremy draws on watching customers go from collecting a petabyte of data in a decade to generating one every two days to make the case that without a real data foundation, enterprises will either get the wrong answer from their AI, or burn a fortune getting to the right one.

In this conversation, we discuss:

Why pointing AI agents at hundreds of terabytes of telemetry burns tokens fast, and what Jeremy says has to change first.
How an AI agent facing 10 sources of truth can deliver the wrong answer with total confidence.
Why Jeremy calls the LLM “a new animal in the zoo,” and what that means for anyone trying to monitor AI agents.
How AI agents are starting to build the knowledge graphs that once took human implementation teams to create.
Why evals are becoming essential to running an LLM, and what a single model release can do to existing applications.
What Jeremy would tell his younger self stepping off the plane to meet Mark Benioff, and the career superpower he undervalued.

Explore the conversation:

00:00 Intro and AI Fun Fact: Pope Leo XIV's Encyclical and Anthropic's Vatican Address
04:08 Introducing Jeremy Burton, GM for Observability at Snowflake and Former CEO of Observe
07:09 The Observe Origin: Pitching Observability as a Unified Data Problem Natively on Snowflake
10:20 Observability as a Data Problem: Metrics, Logs and Traces
13:39 Snowflake Culture and Leadership Eras
16:58 Joining Snowflake: Running Observe After the Acquisition
18:57 Data Foundation vs. Frontier Models: Balancing CPU and GPU Burn with Context
22:23 Snowflake's AI Strategy: Data Foundation and Sources of Truth
28:11 Non-Human AI Telemetry: Using Knowledge Graphs to Structure Machine Data
32:31 Probabilistic AI and LLM Observability: Why Evals and Harnesses Are Essential
36:14 Future of Work: The "LLM as Modern-Day Tractor" and Software Engineering Practices
41:18 Career Superpowers: The Value of Networks and Relationships in Silicon Valley
43:06 Closing: Where to Connect with Jeremy Burton and Explore Snowflake Observability

Resources:

Learn how Box connects secure enterprise content with AI to power smarter workflows. Visit box.com/ai to learn more.

410: Johanna Jackman, Chief People Officer at Freshworks: Responsible AI Isn’t Slow. It’s Bold, With Human Judgment Oct 19, 2026

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Johanna "JJ" Jackman is the Chief People Officer at Freshworks, the global cloud-based customer service and IT service management platform serving over 75,000 corporate clients worldwide. With an international career across six countries, JJ began her professional journey in the Australian mining industry before transitioning into high-growth technology.

Prior to joining Freshworks in 2023, she served as Chief People Officer at Airtable, Chief Human Resources Officer at Pure Storage, and Vice President of HR at LinkedIn during its formative scaling era, and currently sits on the Board of Directors at Grafana Labs.

In this episode, JJ sits down with Dan to discuss why modern employee experience requires transitioning from traditional organizational charts to workflow-centric platforms, how HR functions as Customer Zero to eliminate operational friction across enterprise IT and HR services, why executive leaders must share responsibility with employees for continuous AI fluency, and how the convergence of human judgment with digital teammates is redefining workforce planning and career mobility.

In this conversation, we discuss:

Why evaluating enterprise software transformation requires abandoning rigid organizational charts in favor of end-to-end, workflow-centric employee experiences.
How serving as "Customer Zero" allows internal people teams to co-design IT and HR service platforms that eliminate administrative friction for global workforces.
What the creation of dedicated AI enablement roles reveals about shifting corporate strategy from traditional headcount planning to dynamic capability modeling.
Why fostering organizational resilience requires a mutual commitment between employers and workers to maintain continuous AI fluency and career relevance.
How enterprise leaders can establish transparent guardrails to ensure autonomous algorithms inform decision-making without supplanting human judgment.
What a data-driven, structured job search framework teaches early-career professionals about asserting personal agency in an algorithmically filtered hiring market.

Explore The Conversation

00:00 Intro and listener mailbag: Allison in Trenton on special episode 21 and WEF global job trends
02:35 Introducing Johanna "JJ" Jackman, Chief People Officer at Freshworks
04:09 From mining underground to tech executive: Formative lessons in human-centric leadership
06:22 The Freshworks culture trifecta: Manager support, peer collaboration, and goal clarity
08:47 From org charts to workflows: Framing "People Platform as a Service" with IT leadership
12:08 HR as customer zero: Streamlining Lives HR and eliminating friction across the employee journey
15:32 Rewriting the employment contract: Executive role-modeling and shared AI fluency
21:45 Capacity over headcount: "AI in Motion" days and hiring an AI enablement leader
29:48 Responsible AI in HR: Safeguarding human judgment in promotion and performance decisions
33:34 Empowering early-career professionals: Agency, unlearning, and Josh's mathematical job hunt
41:52 The 2031 vision: Digital employee IDs, merging CPO-CIO roles, and remote leadership
45:01 Closing: Where to connect with Johanna "JJ" Jackman and explore Freshworks

Resources:

Subscribe to the AI & The Future of Work Newsletter
Connect with Johanna "JJ" Jackman on LinkedIn
Other episodes and research mentioned on the show:
- Special Episode 21 featuring Charlene Li, Daphne Jones, Patty Hatter, Mona Sabet, and Tess Posner on female leadership in AI

See why Freshworks was named a Leader in the 2026 Gartner® Magic Quadrant™ for ITSM. Learn more → freshworks.com/dant

409: Ryan Gavin, CMO at Slack: AI Is Single-Player. Slack Is Betting on Multiplayer Oct 12, 2026

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Ryan Gavin is Chief Marketing Officer at Slack, the global collaboration platform used by more than 200,000 organizations across 150 countries. Since joining Slack, Ryan has helped drive a 250% increase in revenue while championing the launch of Slack's AI-first capabilities and agentic integrations.
A seasoned technology executive, Ryan previously served as Chief Growth Officer at Convoy and held senior leadership roles at Amazon Web Services and Microsoft, where he managed multi-billion-dollar business units.

In this episode, Ryan draws on watching hundreds of enterprise AI rollouts up close to make the case that dropping agents into an organization without a strategy doesn't just fail to help, it actively backfires.

In this conversation, we discuss:

Why single-player AI tools fail to deliver enterprise productivity gains, and how deploying autonomous agents into collaborative, multiplayer environments unlocks hidden software value.
How a conversational interface connects unstructured team dialogue with structured CRM data, allowing employees to query enterprise systems without opening underlying software tabs.
What the concept of "headless software" reveals about democratizing access to sales and operational insights across non-technical departments.
Why transparent, step-by-step reasoning and strict permission inheritance are essential for building trust when introducing AI tools into enterprise workflows.
How leading organizations elevate Slack from a conventional IT collaboration expense into a core strategic driver for company-wide AI adoption.
What executive advice for emerging professionals highlights the enduring value of curiosity, creativity, and adaptability in a rapidly changing job market.

Explore the conversation

00:00 Show Intro, a Team Human Success Story, and Meet Ryan Gavin

03:44 Ryan Gavin's Path to Becoming CMO of Slack

04:57 Slack's New Job in the Age of AI Agents

07:53 Designing SlackBot to Strengthen Human Collaboration

12:31 Headless Salesforce and Slack as the New Front Door

16:50 Slack as 2% of Your AI Budget and the Problem With 'Work About Work'

21:37 Trust, Transparency, and the AI Black Box in SlackBot

25:28 From Slash Commands to Every Employee as a Builder

31:40 Winning Share of Wallet in a Zero-Sum AI Budget

35:54 Advice for Workers Who Feel Left Behind by AI

39:35 Where to Find Ryan Gavin and Slack

Resources

See why Freshworks was named a Leader in the 2026 Gartner® Magic Quadrant™ for ITSM. Learn more → freshworks.com/dant

SE 31: Kartik Sakthivel, CIO at John Hancock | Live from Ai4 2026 Oct 08, 2026

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Kartik Sakthivel is the Chief Information Officer at John Hancock, the life insurer that turned 164 years old in April 2026 and is part of Manulife. Before joining, he spent eight and a half years at LIMRA and LOMA, the oldest and largest trade association in financial services, which gave him a view across carriers few technology leaders ever get.

Recorded live from the floor of Ai4 2026, this lightning round explores what it takes to bring AI into a company founded during the Civil War, and why he tells his teams that what they build today becomes the legacy for the next 164 years.

Kartik and host Dan Turchin dig into why he believes every technology leader should think of themselves as a business leader first, how a regulated industry decides what to fast track and what to slow down, and what he says to people who are watching a machine learn to do the thing that made them valuable.

What You'll Learn

Why uptime and mean time to repair are table stakes for a modern technology organization, and what Kartik measures instead
How a highly regulated business draws the line between internal AI that gets fast tracked and anything customer facing that does not
Why there are more AI pilots in insurance than planes at a major airport at peak hour, and how to find use cases that are neither too small to matter nor too large to finish
The question he asks every time the business brings him an AI idea, and why the answer is sometimes something far simpler
What he tells colleagues watching automation absorb part of their role, and where the time that comes back should be reinvested

🎙️ Part of our Ai4 2026 compilation series.

Listen to the full compilation here: https://www.buzzsprout.com/520474/episodes/19816277

Resources

408: Cesar Carvalho, CEO of Wellhub: The Risk Isn't AI. It's How Fast You Grow. Oct 05, 2026

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Cesar Carvalho is the co-founder and CEO of Wellhub, the corporate well-being platform connecting millions of employees to top-tier fitness, mindfulness, therapy, nutrition, and sleep partners across 18 countries.
Since founding the company as Gympass in 2012, Cesar has raised nearly $900 million in venture funding, reached a $2.4 billion valuation, and grown Wellhub to serve over 50,000 corporate clients worldwide.
In this episode, Cesar sits down with Dan to discuss why treating employee wellness and business performance as opposing forces is a false dichotomy. Tune in to hear his perspective on why AI should be leveraged to fund employee reskilling rather than justify job cuts, how Wellhub's AI wellness coach scales hyper-personalized care to millions of subscribers, why less than 10% of global healthcare spending goes toward prevention, and how pivoting during the 2020 pandemic transformed a near-death crisis into a multi-product wellness ecosystem.

In this conversation, we discuss:

Why framing corporate wellness as an adversary to business performance is a false dichotomy, and how employee health directly drives bottom-line execution.
How granting employees 30 minutes of paid work time daily to experiment with AI tools fosters a culture of innovation and continuous reskilling.
What the structural imbalance between preventive "well care" and reactive "sick care" reveals about the urgent need to redesign enterprise benefits.
How an AI-powered wellness coach expands personalized fitness and mindfulness guidance from hundreds of thousands to millions of corporate subscribers.
Why strict data minimization policies and phased beta testing provide a trusted framework for deploying AI in sensitive health environments.
What pivoting a global business model during the 2020 pandemic teaches founders about mission alignment, resilience, and turning near-death moments into catalysts for growth.

Explore the conversation:

00:00 Show Intro and Newsletter Shoutouts

02:07 AI Fun Fact: Chatbots and Mental Health Risks

04:01 Introducing Cesar Carvalho, CEO of Wellhub

05:03 From Harvard Dropout to Corporate Wellness: The Founding of Gympass

06:56 The "Team Human" Ethos: Making Well-Being Ubiquitous at Scale

09:14 Performance vs. Health: Why Employee Well-Being Directly Drives Execution

12:37 Calling Out AI Layoffs: Are Employees Expendable?

14:12 Reskilling Over Layoffs: Why Wellhub Invests in Existing Talent

16:34 Personalization at Scale: Expanding the AI Wellness Coach Across Millions

20:19 Responsible AI at Wellhub: Data Minimization and Governance Standards

22:36 Sick Care vs. Well Care: Quantifying a 20-35% Drop in Healthcare Costs

26:36 Eliminating Friction: Redesigning Employee Benefits Outside Open Enrollment

32:02 Human-First Design and Why AI Will Disrupt Legacy Companies

33:23 The Pandemic Pivot: Turning a Near-Death Event into Wellhub's Evolution

37:27 Advice to His Younger Self and the Best Time to Start a Company

39:45 Closing Thoughts and Sign-Off

Resources:

See why Freshworks was named a Leader in the 2026 Gartner® Magic Quadrant™ for ITSM. Learn more → freshworks.com/dant

SE 30: Todd Barr, CEO at Axonis | Live from Ai4 2026 Oct 01, 2026

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Todd Barr is the CEO of Axonis and has spent his career in high growth software infrastructure, living through the shift from Unix to Linux, the rise of DevOps, and the blockchain era before landing in AI. Axonis was built by technical founders with 25 years each in large scale infrastructure across government, defense and intelligence, where sharing the underlying data was never an option.

Recorded live from the floor of Ai4 2026, this lightning round explores why you do not have to centralize your data to start doing AI, and what it takes to make a decision you can defend later.

Todd and host Dan Turchin dig into what an auditable decision actually records, how governance can live at the data node instead of the application layer, the distance between collecting sensor data and acting on it, and why Todd believes decisions themselves are about to become a category of data.

What You'll Learn

Why centralizing your data is not a prerequisite for AI, and how a federated architecture holds up when nodes go offline and come back
What an auditable decision captures: the data used, the model and its version, the reasoning, and the person who attested to it
How attribute based access control decides what each operator or agent is allowed to see, enforced at the data itself
The sensor to decision gap, and how a flood management team went from raw readings they could not interpret to acting on them in real time
Why collecting data and acting on it are two different problems, and what opens up once that distance closes
What becomes possible once decisions are stored as data, from the cost of each decision to who in the organization decides better

🎙️ Part of our Ai4 2026 compilation series. Listen to the full compilation here: https://www.buzzsprout.com/520474/episodes/19816277

Resources

407: Daniel Chait, CEO at Greenhouse: Inside the Doom Loop Where AI Screens AI-Written Resumes Sep 28, 2026

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Daniel Chait is the co-founder and CEO of Greenhouse, the industry-leading hiring software platform designed to help enterprise organizations build fair, structured, and effective recruiting processes. He has been a technology entrepreneur in New York for more than 20 years.

He started Greenhouse about 15 years ago on a simple conviction: companies that follow structured hiring practices get better results, and job seekers deserve a process that is fair and transparent. Today he is leading the company through a reinvention for the AI era, including the acquisition of Ezra AI Labs to bring transparent, conversational AI tools to job seekers and hiring teams alike.
In this episode, Daniel draws on two decades of building companies where every hire lands directly on the bottom line to ask what candidates and employers both need answered: can AI make hiring more human when it is already making it feel less so?

In this conversation, we discuss:

Why candidates and employers using AI at the same time is creating a doom loop that shuts real humans out.
Why AI-led interviews worry so many job seekers, and what it takes for a conversation with an AI to feel fair.
Why using AI to automatically reject most applicants is tempting, and why Greenhouse said no to itWhy AI-polished resumes are making every candidate look the same, and how hiring can move beyond the resume.
How AI can replicate human bias at light speed, and why Daniel says no vendor should ask you to take their word for it.
What Daniel tells anxious workers, from new grads to senior leaders, about disruption, opportunity, and reinventing a career with AI.

Explore the Conversation

0:00 Welcome Back and This Week's AI Fun Fact

4:48 Meet Daniel Chait, Co-Founder and CEO of Greenhouse

7:55 From a Soulless Consulting Job to Founding a Company

10:43 Reinventing the Applicant Tracking System

15:23 How AI Has Already Reshaped Hiring and Job Seeking

21:11 What the Candid AI Interview Report Reveals About Trust

24:25 Why Auto-Rejecting Candidates With AI Backfires

26:08 Sorting Through the Flood of AI-Generated Applications

30:46 Confronting Bias in AI-Powered Hiring Tools

36:46 Reframing AI Anxiety Into Opportunity

40:11 Time Capsule: Advice to His Younger Self

42:14 Where to Find Greenhouse and Closing Thoughts

Resources

Subscribe to the AI & The Future of Work Newsletter
Connect with Daniel on LinkedIn
AI fun fact article
On How Paolo Ardoino, CEO of Tether, is exploring whether decentralized AI can fix banking, crypto, and the future of finance

SE 29: Andrew Rabinovich, former Upwork CTO | Live from Ai4 2026 Sep 24, 2026

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Andrew Rabinovich is the former CTO of Upwork and has spent 25 years in machine learning and computer vision, long before AI was fashionable. After a PhD in computer vision at UCSD, he worked at Google. He then spent five years at Magic Leap building mixed reality devices before founding Headroom, a video conferencing company that Upwork acquired.

Recorded live from the floor of Ai4 2026 in August, this lightning round explores what happens when you actually measure how much of a real job an AI agent can finish.

Andrew and host Dan Turchin dig into Upwork's shift from a matching marketplace to a work delivery platform, the meta agent that breaks a job into atomic units of work, how the platform proves a freelancer is human, and more.

What You'll Learn

How Upwork is evolving from a matchmaking marketplace into a work operating system, and how its meta agent decomposes a single job into atomic units of work
What Upwork's AI productivity index revealed when agents were tested against real jobs already completed by human freelancers
Why every agent on the platform is paired with a human expert, and how that pairing changes both the speed and the quality of the result
How proof of humanness works in practice, from identity verification to AI video interviews, and what happens when the system gets it wrong
Why agents may soon become the demand side of the marketplace, calling human experts in real time to verify what they cannot

🎙️ Part of our Ai4 2026 compilation series.

Listen to the full compilation here: https://www.buzzsprout.com/520474/episodes/19816277

Resources

406: Mahe Bayireddi, CEO of Phenom: AI May Be Replacing Your Job Right Now, But Not the One You'll Have Next Sep 21, 2026

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Mahe Bayireddi is the CEO and co-founder of Phenom, the global HR technology platform he launched in 2011 with the mission to help a billion people find the right job.

Under his leadership, Phenom has raised over $160 million, achieved unicorn status, and consistently ranked among the Inc. 5000 fastest-growing private companies. A serial entrepreneur with a deep technical foundation, Mahe previously co-founded SnipSnap and Bijol Health. He holds BE and MS degrees in computer science.

In this episode, Mahe sits down with Dan Turchin to unpack why "AI is taking your job" is the wrong framing, and why the real question is where you sit, what you do, and how deeply you understand the business around you.

In this conversation, we discuss:

Why replacing jobs and replacing the job you'll have tomorrow are two very different things, and why irreplaceability comes down to understanding the business, not just being intelligent.
Why raw machine intelligence falls short in enterprise HR, and why true workforce alignment requires AI systems built on deep business understanding.
How culture, structure, and strategy form a company's "organizational DNA," and why most companies fail at execution, not strategy.
How a five-dimensional rubric of talent zones, industries, roles, locations, and culture creates hyperpersonalized workflows instead of one-size-fits-all automation.
Why frontline workers and specialized knowledge practitioners experience AI as an amplifier of capability rather than a displacement force.
What enduring over 100 venture capital rejections teaches founders about developing "cockroach" resilience and leading through persistent industry skepticism.

Explore the Conversation

00:00 Intro & AI Fun Fact

04:27 Meet Mahe Bayireddi, Phenom CEO

06:36 AI Is Your Ally, Not Enemy

09:29 What Hiring Got Wrong

10:43 Culture as Organizational DNA

12:26 Why Agent Interviews Won't Scale

16:47 Bias and AI Responsibility

19:00 Fraud Agents by Region

24:23 Frontline vs. Desk-Based AI

28:53 A Billion People, Right Jobs

31:24 Lessons From the Founder Journey