The WorkOps Podcast

by Kinfolk

5.0 (1)
Business

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.

22h ago

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

39 min
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

27 min
Jun 9

The hard truth about setting a budget

Summary In this episode of The WorkOps Podcast, Jeet sits down with Ann Watson, Chief People Officer at Cover Genius, to unpack why pay-for-performance creates a structural integrity problem that no amount of manager training can fix. Ann argues that the annual raise has always been a budget decision dressed in performance language, and that pay transparency didn't create the breakdown — it just made it undeniable. She shares how Cover Genius moved to anniversary-based automatic raises, what happened when managers were freed from the comp conversation entirely, and why she still gives low performers their raise every year. Chapters 00:00 Ann Watson's path to CPO (starting at Starbucks)02:30 The three routes into people leadership and which one dominates right now08:00 AI as a workforce topic, not just a tooling decision13:30 The dysfunctional process Ann identified at every job she's ever had15:30 The breakdown of integrity inside every review cycle19:30 What the research actually says about pay-for-performance23:00 Pay transparency and the structural problem it exposed27:00 How Cover Genius inherited a comp quirk and leaned into it29:30 Building the anniversary raise system for 700 global employees32:00 The low-performer objection and loading the seat 35:00 AI in compensation: the accidental flight risk catch Takeaways Pay-for-performance is a budget mechanism, and calling it a performance signal is where the integrity breakdown starts.Managers who can't explain the comp process aren't failing — they've been handed something structurally unexplainable.Anniversary-based raises remove the manager from a conversation they never should have owned.Raising the low performer's salary maintains the market rate of the seat, not the person — so you can hire well when you're ready.When a manager objects to a low performer's raise, that objection is often a performance conversation that's overdue.Connect with the GuestLinkedIn: https://www.linkedin.com/in/ann-watson-5404a48/Website: https://covergenius.com/ SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com

38 min
Jun 4

What makes AI actually stick at a 750-person company

Summary On The WorkOps Podcast, Jean Parchewsky, VP of People Operations at Vendasta, makes a case most AI conversations miss: whether AI takes hold in your company is decided at the hiring table, not in the tooling budget. She traces it back to a training binder that optimized for terminations over hiring, the "hire slow, fire fast" principle she built in response, and the behavior-first "ideal employee profile" her team uses today. Then she shows how that same hiring discipline is what made AI adoption stick, through a citizen developer program, a searchable build board, and a culture where sharing your failures out loud is the norm. Essential listening for any People leader who has been asked to "roll out AI." Chapters 00:00 Why Jean never planned a career in HR 03:50 The binder that optimized for firing, not hiring 06:00 Hire slow, fire fast 07:30 The bar raiser: never interview hungry 11:00 The ideal employee profile: hiring for behavior 13:20 Why AI adoption is a culture problem 14:10 Citizen developers and the build board 18:30 Putting AI enablement in People Ops, not IT 23:00 Pepper and the rise of AI "employees" 26:00 One piece of advice: just jump in Takeaways Optimizing HR for legal risk instead of the team can quietly cost you your best people. Hire slow and fire fast: spend your effort choosing the right person, and be honest quickly when it isn't working. Hiring for behaviors rather than skills builds the culture everything else depends on. Stalled AI adoption is usually a culture problem, not a tool problem. AI enablement belongs close to the work, in People Ops, where it becomes workflow change instead of better emails. Connect with the GuestLinkedIn: https://www.linkedin.com/in/jean-parchewsky/Website: https://www.vendasta.com/ SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com

29 min
Jun 2

How to Separate the Why From the What in HR

SummaryOn this episode of The WorkOps Podcast, Jeet sits down with William West, VP People at Wrapbook, to dig into what happens when HR leaders stop trying to do everything in one place. William shares how a 20-plus-hour calibration process became six hours by separating ratings conversations from development conversations entirely. He also makes the case that HR's distinct job in an AI transformation isn't governing tools — it's owning the human argument for why the change matters. And in his closing remarks, he offers a frame on vulnerability that redefines what effective People leadership looks like right now. Chapters00:00 William West's path from nonprofit HR to VP People at Wrapbook04:00 How HR changes across sectors: pace, complexity, and scale07:30 The calibration problem: 20-plus hours and still unclear12:30 The fix: reading instead of explaining16:30 Separating calibration from development, permanently21:00 AI and human connection: what the technology is actually for25:00 Who leads AI adoption, and why HR owns the why29:00 Vulnerability as a change management strategy Takeaways Calibration and development are two different conversations with different goals — combining them makes both worse.Switching from verbal summaries to a read-and-discuss format cut Wrapbook's calibration from 20-plus hours to around six.HR's distinct role in an AI transformation is owning the why, not governing the tooling; technical teams are better positioned for the what.Late adopters don't move without context-specific reasons; the leader closest to people in each function is best positioned to provide them.Naming openly that you feel behind on AI creates space for others to start learning instead of waiting for certainty. Connect with the GuestLinkedIn: https://www.linkedin.com/in/williamcwest/Website: https://www.wrapbook.com/ SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com

31 min
May 26

Context is the new currency for HR

SummaryA top performer walks out the door at Qualtrics holding an outside offer for double their salary. Michael MacArthur, then Head of People, has a choice: pretend the market is wrong, or admit the comp process was. His read, years later from the COO seat at Recharge: the 2x counter-offer isn't a market signal. It's an audit finding. This is one of the cleanest diagnostics we've heard for whether a comp process is really working. And it's the same logic Michael applies to AI, engagement, and the build-versus-buy questions every HR leader is wrestling with right now. The unifying argument: context, not better tools, is the layer that separates the HR teams winning with AI from the ones spinning cycles. Timestamps01:00 Michael's path from sales comp to head of people at Qualtrics to COO at Recharge03:00 The Qualtrics dysfunction: forced curves and 18-month time-in-seat gates04:00 The "double their salary" diagnostic signal for a broken comp process06:30 Recharge's fix: 6-month cash cycle, no forced curve, multi-level calibration10:00 Process transparency versus salary transparency13:00 Nectar's anonymous follow-up and the context thesis for AI in HR14:30 Why Anthropic's engagement score doesn't matter to Recharge16:00 Build versus buy on the people side: when trust outweighs context21:30 The CEO move that put Recharge's exec team on terminals23:00 Audit the workflow before you prompt the model Takeaways- The fastest test that your comp process is broken: a leaving employee getting offered double their current salary at the next job.- Forced curves and time-in-seat promotion gates work at 250 employees. They quietly stop working at 2,500.- AI value in HR shows up in context-gathering, not dashboards. Anonymous follow-up conversations beat static survey scores.- Internal-historical engagement trends beat external benchmarks. Anthropic's engagement score doesn't tell you what's happening on your team.- Audit the workflow before you prompt the model. Most failed AI projects in HR are unmapped-workflow problems, not tooling problems. Connect with the GuestLinkedIn: https://www.linkedin.com/in/mimcarthur/Recharge: https://getrecharge.com/about/ SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com

26 min
May 19

How to Fund Your HR Transformation

Summary In this episode of The WorkOps Podcast, Jeet sits down with Weston Fillman, Director of People Operations and Employee Relations at 1Password, to unpack what it actually takes to get an HR transformation funded, and what changes when AI enters the room. Wes describes the months of pre-work that won him more executive budget than he asked for at a 10,000-person enterprise tech company, the reframe he'd apply to the same project today (people systems as infrastructure, not engagement), and the role-redesign conversations he's having on his team at 1Password as AI starts to automate the operational layer of HR ops. A field guide for any People leader heading into their next budget cycle. Timestamps 00:00 Welcome and Wes's career path (TFA kindergarten to 1Password) 02:45 Inheriting a broken hiring process at a 10,000-person company 07:00 "You can build a new house, but the floor plan's wrong" 08:00 The structured plan, executive buy-in, and a budget bigger than expected 11:00 Sideways socialization: leading without authority across HR peers 13:30 1Password rolls out org-wide agent-building, and modeling AI as a leader 17:30 Build vs. buy in 2026 (and why it's really build AND buy) 22:30 The role redesign conversation: AI rewrites the JD, doesn't cut the role 26:00 The reframe Wes would apply today: people systems as infrastructure 30:00 Where People leaders should start their own AI journey Takeaways - HR transformation budgets are won in the months of pre-work before the e-staff ask, not in the room itself. - The reframe from "employee experience" to "business infrastructure" is the single change that turns the same HR project from nice-to-have into board-level fundable. - AI lands well when leaders treat it as a role-redesign conversation, not a layoff conversation. Most operational work was never on the JD anyway. - Cross-functional buy-in (sideways across peer HR leaders) matters as much as executive sponsorship for any large People transformation. - The best AI on-ramp for an individual contributor is to start with the work they're not great at, not the work they already excel at. Connect with the GuestWeston Fillman on LinkedIn: https://www.linkedin.com/in/westonfillman/1Password: https://1password.com/ SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com

34 min
May 13

The "Human API" problem hiding in your onboarding process

Summary What looks like a warm, boutique onboarding experience on the outside is often powered by something much less glamorous on the inside: a person copy-pasting LinkedIn headshots into slides at midnight. In this episode of the WorkOps Podcast, host Jeet sits down with Amie Taylor, Senior Director of People Operations, Rewards and Technology, for a refreshingly honest conversation about the hidden cost of "human API" processes. Amie walks through a three-year saga at a previous hyper-growth tech consulting company where the entire day-zero-to-day-one new hire experience ran on Google Forms, manual IT tickets, and one very overworked TA coordinator hunting down headshots for the CMO's town hall slides. She shares how she eventually built the business case, the internal politics she had to navigate, why it took a team member filing overtime to finally break through, and the bittersweet twist at the end when she left right after getting the project approved. She and Jeet also get into how she's applying those lessons today—consolidating HR systems at her current company, using critical thought as the test for what to automate, and why some processes (like leave for someone facing a serious diagnosis) should stay stubbornly human. If you've ever inherited a process held together by goodwill and overtime, this one will hit close to home. Timestamps 00:23 Amie's path from psychology to global payroll04:46 Inheriting a high-touch onboarding process powered by "human APIs"06:12 Google Forms, missed steps, and a candidate experience built on anxiety08:23 Hours spent hunting down headshots for town hall slides11:00 The three-year fight to get buy-in to automate13:00 Getting the project approved, then resigning right after15:13 Rebuilding similar processes today with full stakeholder buy-in19:47 The "critical thought vs. machine work" test for what to automateTakeaways Audit the hidden labor inside "high-touch" processes before you call them cultureQuantify manual work in overtime and bottom-line impact, not just employee experienceBuild stakeholder buy-in by making the decision feel like theirs, not yoursUse "critical thought vs. machine work" as your test for what AI and automation should touchProtect the human moments—leave processes, serious diagnoses, tough conversations—no matter how advanced your tooling getsRemember: if the process doesn't scale, it's not your culture, it's tech debtGuest LinkedIn: https://www.linkedin.com/in/amie-taylor-5b99b810/ SponsorThis episode is brought to you by Kinfolk, the AI service desk built for HR. See more at kinfolkhq.com

23 min

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
Years Active

2K
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13
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Explicit
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© 2026 by Kinfolk