The WorkOps Podcast

by Kinfolk

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The WorkOps Podcast is your weekly conversation with HR leaders and People Ops practitioners doing the real work. In every episode we dig into one story. A process that went sideways, a system that just didn't work, and what someone actually did about it. Packed with practical lessons you'll want to bring back to your team. Whether you're supporting 500 employees or 5,000, this is how the best People leaders are building for what comes next.

4d ago

The three levels of work: Where AI belongs, and where it never will

Summary What happens when a CEO hands unlimited AI access to every employee, and adoption still stalls? In this episode of The WorkOps Podcast, host Jeet Mukerji sits down with Kimberly Nerpouni, Global VP of People & International Operations at Pearl, the parent company of JustAnswer. Kimberly shares why AI transformation is a human enablement problem rather than a technology problem, how her People Ops team built Pearl's AI accelerator and a 1 to 10 adoption scale with no bad scores, and her three levels of work framework for deciding what AI should absorb first. She also explains the feedback facilitator agent her team is building, the hard line she draws (AI never gives feedback, it helps managers facilitate it), and why PIPs don't exist at Pearl. This conversation is for people leaders, HR teams, and anyone navigating AI adoption inside their organization. Chapters 00:00 Introduction 00:45 From IT manager to people operations 04:25 JustAnswer, Pearl, and human plus AI 06:15 Inside Pearl's AI accelerator 10:55 Build, buy, or borrow 13:15 The three levels of work 17:05 AI that facilitates feedback instead of giving it 19:50 The AI agent hub and transparency 23:35 Why PIPs don't work and what replaces them 35:05 Don't wait, just do Takeaways -AI adoption is a human enablement problem, not a technology problem, and people ops is uniquely positioned to lead it. -Move AI into level one work first, the tasks that don't require your expertise, so your team can focus on level two and level three work. -Build, buy, or borrow: piloting with AI startups can reveal exactly what's worth building bespoke in-house. -AI should facilitate feedback conversations by scanning context and prompting managers, but it should never give the feedback itself. -Front-load clarity with job descriptions, career ladders, and employee-owned development plans so PIPs are never needed. Connect with the Guest LinkedIn: https://www.linkedin.com/in/kimberlypignolet/ Website: https://www.pearl.com SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com
Jul 23

When Your HR AI Pilot Works Too Well to Stay a Pilot

Summary What happens when your AI pilot works too well to stay a pilot? In this episode of The WorkOps Podcast, host Jeet Mukerji talks with Ivan Nosov, Head of HR Tech and Global Total Rewards Director at Campari Group, about taking AI in HR from proof of concept to production. Ivan shares why he started with Copilot Studio knowing it wouldn't last, where RAG breaks down at enterprise scale, and how his team built a digital twin router app on Claude that loads only the context each question needs. He also lays out the adoption playbook that made it stick: winning over regional directors and COE champions first, running hackathons for awareness, and addressing the work people hate instead of the work they love. A practical conversation for HR, people ops, and workplace technology leaders navigating AI transformation. Chapters 00:00 Introduction 01:30 From IT engineer to HR leader 03:45 Should AI transformation sit in HR or IT 05:55 How non technical HR can get started 07:20 Copilot Studio as a proof of concept tool 09:30 Harness, routing, and the limits of RAG 15:00 Building the digital twin router app on Claude 17:40 Context engineering and distilling tacit knowledge 19:30 Winning adoption through champions 29:55 The future of junior roles and build versus buy Takeaways Start with the accessible tool to prove the concept, then move on. Copilot Studio validated Campari Group's AI ideas, but production required control over the harness that abstracted platforms can't offer.Routing beats RAG at scale. Loading only the relevant context for each question makes AI more targeted, more efficient, and far less likely to hallucinate.Campari Group's digital twin runs on Claude with deliberate model selection: Sonnet for efficiency, Haiku for helper queries, and Opus for final artifacts because of its design taste.Adoption spreads through champions. Win over regional directors and COE heads first, stay with them until the outputs click, and they will share it further than any rollout plan.Context engineering is the real work. Distill tacit knowledge into a compact, unambiguous knowledge base: 250,000 tokens in total, with no session loading more than 50,000. Connect with the Guest LinkedIn: https://www.linkedin.com/in/ivan-nosov/ Website: https://www.camparigroup.com/ SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com
Jul 21

Job Security, Not Role Security: How to Future-Proof a Workforce

Summary What happens to careers when AI makes more than half of all roles look fundamentally different within two years? In this episode of The WorkOps Podcast, host Jeet Mukergi sits down with Lisa Sherwell, Chief People Officer at SUSE, to unpack her answer: strive for job security, not role security. Lisa shares how SUSE's Future Selves program transformed engagement for its over 50 workforce, why internal gigs are the new engine of career growth, and why performance management fails not because of broken processes but because leaders avoid honest conversations. A practical, candid conversation for HR leaders, people operations professionals, and executives navigating the AI era. Chapters 00:00 Introduction 01:15 From sales and call centers to chief people officer 02:30 Building commercial curiosity in HR 04:15 Future Selves: investing in the over 50 workforce 07:00 Job security vs role security 08:55 Hiring for AI potential, not expertise 10:30 How SUSE rolled out AI across the business 16:45 Running HR for 8% less while delivering more 24:30 Performance is a clarity problem, not a process problem 33:00 A new playbook for the AI era Takeaways -Strive for job security, not role security: broad competencies and internal mobility protect people as AI reshapes their roles. -More than half of all roles could look fundamentally different within two years, so career agility is now a core business responsibility. -SUSE's Future Selves program proved that investing in the over 50 workforce lifts engagement, internal mobility, and community, while preserving invaluable business context. -Performance is a clarity problem, not a process problem: honest meets, fails, exceeds conversations beat new ratings scales and OKR frameworks. -Ownership of performance belongs with the individual contributor, because nobody cares more about your career growth than you do. Connect with the Guest LinkedIn: https://www.linkedin.com/in/lisasherwell/ Website: https://www.suse.com SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com
Jul 17

High agency, low ego, and the future of HR at Tubi

Summary On this episode of The WorkOps Podcast, host Jeet Mukergi sits down with Natasha Valani, Chief People Officer at Tubi, the number one free ad-supported streaming service in the US. Natasha shares how her people team built a live calibration tool in Replit in just two days, connecting it back to Workday and saving roughly two weeks during year end review season. The conversation goes well beyond one tool: Natasha unpacks how she hires for high agency and low ego, why subtraction is her favorite leadership discipline, and how she sees junior and people roles evolving as AI takes on more of the routine work. It's a practical, candid look at running a lean, builder-minded HR function, ideal for people leaders, HR practitioners, and anyone rethinking how their team operates in the AI age. Chapters 0:45 Welcome and Natasha's story 1:45 From 26 schools to belonging and the people space 3:45 Building a culture where everyone builds 6:45 Hiring for high agency and low ego 9:45 The year end calibration problem 10:45 The two day tool built in Replit 15:45 Why build instead of buy 19:45 Trade-offs and the power of subtraction 21:45 The honest gap, headcount management 26:45 The future of junior roles in the AI age Takeaways -You don't need a vendor RFP to solve an HR problem. Someone who knows the guts of the process built a live calibration tool in Replit in two days and connected it to Workday, saving roughly two weeks. -High agency is the differentiator in the AI age. Natasha screens for it with one question: tell me about a time you built a solution nobody asked you to. -Pair high agency with low ego. Stay curious and ask questions, but don't assume nothing good existed before you. -Subtraction is a strategy. Force-rank priorities, openly showcase what you removed, and protect your team's bandwidth by refusing to do everything. -Junior roles won't disappear, they'll shift. The people closest to the guts of a workflow become operational advisors and orchestrators, and AI still needs a human eye to catch the slop. Connect with the Guest LinkedIn: https://www.linkedin.com/in/natasha-valani-1758a418/ Website: https://tubitv.com SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com
Jul 16

This Isn't an AI Revolution. It's a Human Revolution.

Summary Carmel Smith, Director of People Operations and Programs at Tenstorrent, joins host Jeet Mukerji on The WorkOps Podcast to make the case that the AI moment is really a human one. Fresh off building people operations inside a company that grew headcount 43% past 1,300 employees, Carmel explains why she's rebranding her team from "people operations" to system architects and experience creators, why she refuses to mandate AI or track tokens and agents, and what she means when she says she's leading a human revolution rather than an AI one. It's a refreshingly optimistic, practical conversation for HR and people leaders, operations teams, and anyone trying to bring humans along through rapid change. Chapters 00:00 Cold open, the scary part of getting AI right 00:45 Meet Carmel Smith and Tenstorrent 03:45 From people operations to system architects 06:45 Why she never mandates AI 07:45 The painting lesson and psychological safety 11:45 Leading a human revolution 12:45 People data as an open source foundation 20:45 Redefining productivity beyond AI ROI 30:45 The monthly hackathon her leader defends Takeaways -HR's real identity shift is internal: help your team see themselves as system architects and experience creators, not process executors, and their confidence follows. -Mandating AI backfires. Counting tokens, hours, and agents produces box checking, not rethinking. Curiosity, safety, and a genuinely excited leader scale far better. -AI rewards the most human skills. Having strong opinions and articulating them clearly matters more than technical knowledge, because the systems part is the easy part. -Don't track ROI on AI directly. If it's implemented well it bleeds into everything, so measure faster processes, redesigned workflows, and reduced fear instead. -Protect creative time on purpose. A defended monthly hackathon, even when the output fails, changes how a team works by redefining what productivity means. Connect with the Guest LinkedIn: https://www.linkedin.com/in/carmelmoyal/ Website: https://tenstorrent.com Disclaimer: The views and opinions expressed here are my own and do not reflect the official policy or position of Tenstorrent. SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com
Jul 7

Kate Stewart reveals the trade secrets on building AI for HR tasks

Summary On this episode of the WorkOps Podcast, host Jeet Mukergi talks with Kate Stewart, Staff People Operations, AI and Automations Lead at Horizon3.ai, about what really happens when you put an AI agent into a live people-operations workflow. Kate shares the story of the offer-validation agent she built in Slack to check every job offer against approved comp bands and job architecture, how a Slack update broke it after two months, and the two weeks she spent secretly becoming the agent herself to keep the quality bar from slipping. Along the way she unpacks why a hallucinating agent is more dangerous than a silent one, why automation raises the bar instead of lowering it, and how to ship, break, and maintain automations without burning out. It's a candid, practical listen for anyone in people ops, HR tech, or operations moving from curiosity about AI to actually running it in production. Chapters 00:00 From the retail floor to people ops 06:30 Staying curious without a second job 07:45 The broken process behind every offer 09:45 Building the offer validator in slack 11:45 Two months in, the agent breaks 12:45 Becoming the human agent 13:45 Why a hallucinating agent is a liability 14:55 Automation raises the bar 15:45 From perfectionism to shipping V1 28:45 Build it, let it break, protect the time Takeaways -When an automation breaks, you don't fall back to your old baseline, you fall below it, because automation raises the bar for what your team considers acceptable -A silent agent is confusing, but a hallucinating agent is a liability, a confident wrong answer is far more dangerous than no answer at all -Job architecture is not a data hygiene problem, it is an IT provisioning problem, the wrong title in the HRIS means the wrong system access on day one -Build one agent to do one job at the right moment, rather than spreading the same check across three people and three separate touchpoints -Ship V1, let it break, and protect the time to maintain it, the build teaches you the problem and the break teaches you what you actually built Connect with the Guest LinkedIn: https://www.linkedin.com/in/kate-stewart00/ Website: https://www.horizon3.ai SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com
Jun 30

What got you here won't get you there: the murky middle in the age of AI

Summary In this episode of The WorkOps Podcast, host Jeet sits down with Colleen McCreary, Chief People Officer and Head of Internal Systems at Confluent, for a candid conversation about people, productivity, and what AI is really doing to the workforce. Colleen makes the contrarian case that early-career talent is a company's edge in the AI era, while the "murky middle" faces the hardest reinvention. She explains why she's torn out the performance review everywhere she's worked, how she compressed a five-month review cycle to three and a half weeks, and how a company-wide "find the b******t" campaign cut hundreds of meeting hours. Along the way she shares her first-principles approach to choosing tools, her "tasty, not wastey" philosophy on spending, and her definition of the people officer as the product manager of how a company actually runs. It's a sharp, practical listen for HR and people leaders, founders, and anyone rethinking how work gets done. Chapters 00:45 Welcome and Colleen's path into HR 02:45 Leaving venture capital to operate again 05:30 Keeping humans at the heart of AI 07:15 The murky middle and betting on early career talent 12:15 Why HR and internal systems belong together 17:30 Swim teams versus soccer teams 22:15 The bureaucratic misery index 28:25 Why performance reviews are broken 34:35 Tasty, not wastey, and hiring for taste 37:15 First principles and the people officer as product manager Takeaways The people most at risk from AI aren't juniors, they're the "murky middle" six to twelve years in, whose old playbook is being flipped on its head. Performance ratings don't predict performance: 90% of the people managed out at Confluent had been rated successful or exceptional. You can cut a five-month review cycle to a few weeks by subtracting, fewer rating tiers, fewer questions, and a real deadline as a forcing function. Solve for the problem first, then pick the tool. Choosing the tool first is how good teams get stuck. In an age where AI can build almost anything, taste (good judgment about what's worth building and spending on) is the scarcest skill. Connect with the Guest LinkedIn: https://www.linkedin.com/in/colleenmccrearychiefpplofficer/ Website: https://confluent.io SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com
Jun 16

Why AI won't do the hard part of HR ops

SummaryWhat happens when the push to automate HR collides with the humans inside the process? In this episode of The WorkOps Podcast, host Jeet Mukherjee sits down with Nancy Luschkowski, Director of HR Infrastructure & Operations at PagerDuty, to unpack a live onboarding redesign happening amid restructuring, attrition, and the AI wave. Nancy explains why a perfect automation can still ruin the employee experience, why every cross-functional process needs an end-to-end owner, how PagerDuty created a new infrastructure and operations function to keep handoffs clean, and exactly where AI helps (accelerating the starting point) versus where it doesn't (the collaborative hard part). A practical episode for HR ops, people ops, and anyone responsible for employee experience. Chapters00:00 Cold open: the risk of over-indexing on automation01:45 Meet Nancy: why HR operations is the center of everything04:15 The story: onboarding amid reorgs, attrition, and the push to automate06:15 Notification black holes and "enabling the automation"08:45 PagerDuty's new HR Infrastructure & Operations function10:15 End-to-end process owners: one person, the whole experience12:15 Moving fast enough: rebuilding every time an owner leaves13:45 Manual work, tool stack decisions, and source of truth vs. agents18:15 AI as the starting point: process maps, drafts, and the legal persona trick22:45 The ideal onboarding experience: intuitive, customized, human27:45 Measuring onboarding success29:05 Final thoughts: come find me and talk to me Takeaways- You can build the perfect automation, but if the people in it don't know their step or lack context, the experience fails — design automation and the human touch in tandem.- Automation is point-in-time and adoption isn't: managers who hire rarely experience onboarding as brand-new, so one-size-fits-all workflows rarely work and continuous re-enablement is mandatory.- Cross-functional processes need an end-to-end owner — one person accountable for the experience from start to finish, not just a collection of contributors.- Slow down on tool-stack decisions to avoid tech debt: assess current state, define owners, and improve incrementally rather than in one big release.- AI accelerates the starting point — process maps, drafts, persona critiques — but it doesn't do the hard part: incorporating stakeholder feedback, testing, and iterating with a product mindset. Connect with the Guest LinkedIn: https://www.linkedin.com/in/nancy-luschkowski-pmp-shrm-cp-1a955665 Website: https://www.pagerduty.com SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com

The WorkOps Podcast is your weekly conversation with HR leaders and People Ops practitioners doing the real work. In every episode we dig into one story. A process that went sideways, a system that just didn't work, and what someone actually did about it. Packed with practical lessons you'll want to bring back to your team. Whether you're supporting 500 employees or 5,000, this is how the best People leaders are building for what comes next.

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by Kinfolk
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2026
Episodes

19
Rating

Explicit
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© 2026 by Kinfolk

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