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 payroll
• 04:46 Inheriting a high-touch onboarding process powered by "human APIs"
• 06:12 Google Forms, missed steps, and a candidate experience built on anxiety
• 08:23 Hours spent hunting down headshots for town hall slides
• 11:00 The three-year fight to get buy-in to automate
• 13:00 Getting the project approved, then resigning right after
• 15:13 Rebuilding similar processes today with full stakeholder buy-in
• 19:47 The "critical thought vs. machine work" test for what to automate

Takeaways

• Audit the hidden labor inside "high-touch" processes before you call them culture
• Quantify manual work in overtime and bottom-line impact, not just employee experience
• Build stakeholder buy-in by making the decision feel like theirs, not yours
• Use "critical thought vs. machine work" as your test for what AI and automation should touch
• Protect the human moments—leave processes, serious diagnoses, tough conversations—no matter how advanced your tooling gets
• Remember: if the process doesn't scale, it's not your culture, it's tech debt

Guest LinkedIn: https://www.linkedin.com/in/amie-taylor-5b99b810/

Sponsor
This episode is brought to you by Kinfolk, the AI service desk built for HR.

See more at kinfolkhq.com

Summary

What if the most honest feedback about why people leave your company isn't in the exit survey at all—it's in the Slack threads, Zoom transcripts, and emails already happening every day?

In this episode of the WorkOps Podcast, host Jeet sits down with David Hanrahan, SVP of People Success at SolarWinds, for a candid conversation about one of the most broken processes in HR: the exit survey.

David walks through his years-long love-hate relationship with exit surveys, including a moment at Zendesk where he got so frustrated with the bad signal that he actually told the team to stop running them altogether. He and Jeet get into why exit data is so unreliable, how bias from both departing employees and their managers rewrites the real story, and why he believes the future is in predictive signals from real conversations rather than post-hoc questionnaires.

David also shares a contractor agent pilot that SolarWinds recently shelved, what it taught them about where AI belongs and where it doesn't, and how he's coaching his business partner team through the shift from tactical request-handling to strategic HR. And he closes with a line that stuck with me: in this era, people leaders need to think of themselves a little more as technologists and a little less as psychologists. If you lead people ops, build HR systems, or are just trying to figure out where AI fits, this one's worth an hour.

Timestamps

• 00:33 From accidental psychology major to SVP of People Success
• 02:13 Why SolarWinds calls it "People Success" instead of HR
• 03:02 The exit survey problem at Zendesk and why David shut them down
• 06:16 How bias from both employees and managers corrupts exit data
• 12:34 Why employees are more comfortable asking AI sensitive questions
• 16:16 The contractor agent pilot SolarWinds shelved and what it taught them
• 21:05 Freeing up business partners for strategic HR through automation
• 23:33 Flipping exit surveys on their head with predictive signals

Takeaways

• Interrogate the data you're treating as gospel; exit surveys carry more bias than most HR teams admit
• Start with one high-impact area when adopting AI instead of trying to flip everything at once
• Understand where a human needs to stay in the loop before building an agent—narrow scope without judgment design usually fails
• Be explicit with your team about why you're automating; relinquishing work requires trust in what comes next
• Look for retention signals in the conversations already happening, not in surveys you have to force people to fill out
• Think of yourself a little more as a technologist and a little less as a psychologist in this era of HR

Guest LinkedIn: https://www.linkedin.com/in/davidhanrahan/

Company website: https://www.solarwinds.com

Sponsor
This episode is brought to you by Kinfolk, the AI service desk built for HR.

See more at kinfolkhq.com

Summary

A CEO signs off on a new compensation philosophy. Two months later, when HR starts rolling it out, that same CEO tells the executive team it was never approved—and blames the HR leader for pushing it.

Sound impossible? It happened.

In this episode of the WorkOps Podcast, host Jeet sits down with Kelsey Browning, VP of People Operations, for a candid and detailed story about what happens when leadership alignment breaks down in the middle of a comp cycle at a Series B-to-C startup.

Kelsey was the first professional HR hire at the company and had to navigate a conflict-averse CEO, an emotionally flooded VP, and a compensation philosophy that was suddenly orphaned—all while protecting employees from the chaos happening above them. She walks through how she de-escalated heated executive conversations, rebuilt the philosophy for the next cycle, and what she'd do differently if she could go back.

She and Jeet also get into the framework she uses to decide what AI can solve (process problems) versus what still needs a human (people problems), why she builds employee journeys the same way product teams build customer journeys, and her prediction that HR is about to consolidate back into generalists—powered by AI. If you've ever been the HR person caught between a founder who changed their mind and an executive team that needs answers, this one will hit close to home.

Timestamps

• 00:22 Kelsey's unusual path into HR: customer service, supply chain, and FP&A
• 01:43 The scenario: first professional HR hire walks into a compensation philosophy mess
• 05:31 Discovering the CEO was no longer aligned with what they'd approved
• 08:25 De-escalating an emotionally flooded executive mid-conversation
• 12:39 Redesigning the compensation philosophy for the next cycle
• 17:39 Protecting employees from executive-level dysfunction
• 24:10 The "people problem vs. process problem" framework for AI
• 28:38 Automate all you can so you can spend time on the moments that matter

Takeaways

• Reconfirm executive alignment right before executing—sign-off two months ago doesn't mean sign-off today
• Learn to name emotional flooding in the moment; asking "would you like to reschedule?" usually resets the conversation
• Script your CEO on what they need to say to the executive team instead of assuming they'll represent the decision correctly
• Separate people problems from process problems before deciding where AI fits—AI solves process problems well today, people problems not yet
• Build employee journeys the same way you'd build customer journeys, mapping output expectations around key lifecycle moments
• Automate everything you can within the employee lifecycle so your team has time for the moments that actually matter

Guest LinkedIn: https://www.linkedin.com/in/kelseybrowning/

Company website: https://invisibletech.ai/

Sponsor
This episode is brought to you by Kinfolk, the AI service desk built for HR.

See more at kinfolkhq.com

Summary
When the sole operator of a global company’s immigration process left, a critical workflow supporting 10% of the workforce imploded. What remained was an undocumented, email-based system, causing widespread employee anxiety about work authorization and threatening the company’s ability to retain essential US-based talent. This created a strategic nightmare: a global healthcare data analytics firm, where much of its data could not be sent offshore, faced losing critical personnel due to a broken internal process.

Chesney Woodall, an HR Director initially unfamiliar with immigration, inherited this mess. She quickly found herself managing 25 simultaneous immigration cases while operating as a key contributor on a three-person US HR team for a 1,000-employee company. This "messy middle" between top-down goals and bottom-up work created an accountability gap that put talent retention and business continuity at risk. To systematize the process, Chesney leaned on cross-functional collaboration and existing tools, transforming a manual, fear-inducing workflow into a more transparent system. Now, Chesney uses AI as a personal learning assistant, democratizing complex knowledge and freeing up strategic time to focus on people-centric HR.

Timestamps

• 00:10 The undocumented immigration process creating a single point of failure
• 03:29 10% of the company's global workforce impacted by visa uncertainty
• 04:35 "If it touches the employee, it comes to HR": Navigating process ownership
• 06:07 The Excel spreadsheet chaos and undocumented immigration tracking
• 07:47 Employee fear: Losing work authorization and business continuity risk
• 09:22 How ChatGPT became Chesney's accidental immigration SME
• 10:46 Automating admin: Unlocking strategic time for people-centric HR
• 16:40 Building an internal operating system for immigration with Jira
• 18:46 The manual gaps: Jira’s limitations and the need for further automation
• 22:56 AI's role in improving employee experience and information discoverability

Takeaways

• Standardize critical processes to avoid a single point of failure, especially when they directly impact talent retention and business continuity.
• Utilize existing internal tools and cross-functional teams to build solutions, leveraging institutional knowledge before investing in new software.
• Systematize administrative tasks to free up HR for strategic initiatives like proactive talent management and improving employee experience.

Connect with the guest

LinkedIn: https://www.linkedin.com/in/chesney-woodall/

Learn more about Cedar Gate: https://www.cedargate.com/

Sponsor
This episode is brought to you by Kinfolk, the AI service desk built for HR.

See more at kinfolkhq.com

Summary

Most companies have an offer process that looks clean on a whiteboard and turns into chaos in practice. The recruiter fights for more money. The comp team says no. Finance says it's too expensive. The business leader just wants it done.

Everyone's working off different information, and by the time a decision is made, it's conflict resolution—not a hiring process. In this episode of the WorkOps Podcast, host Jeet sits down with Tony Castellanos, EVP of People at Nextdoor, for a sharp conversation about what happens when you replace serial decision-making with shared context.

Tony has spent his career watching offer processes break down because every stakeholder applies their own lens in isolation—and nobody has the full picture. He walks through how Nextdoor rebuilt the process to bring all parties into the room at the beginning instead of passing decisions down a chain, why the proudest moments in his career are when a recruiter says no to a hire they could have closed, and how the shift from "HR" to "people" isn't just branding—it changes the scope and responsibility of the entire function.

Tony and Jeet also get into why information architecture is the unsexy foundation that makes AI-first people operations possible, how Nextdoor runs a dedicated build day once a month for AI experimentation, and why the biggest thing leaders can do right now is create space for their teams to be "courageously creative." If you lead a people function, run a recruiting team, or are trying to figure out where AI fits, Tony's framework of context over control will change how you think about the work.

Timestamps

• 00:18 Tony's path from recruiting agency to EVP of People
• 02:16 The evolution from HR to People—and why it's intentional, not just branding
• 07:35 The offer process: why the blueprint breaks in practice
• 10:16 Solving for context over control: bringing all stakeholders in upfront
• 13:11 The proudest moment: when a recruiter says no to a hire they could have closed
• 16:07 Who makes the final call when there's a deadlock
• 19:20 Building AI on top of solid information architecture
• 23:00 A day a month for AI experimentation and the "courageously creative" mindset

Takeaways

• Replace serial offer approvals with a shared context model where TA, comp, finance, and the hiring leader are all in the room from the start
• Celebrate when recruiters say no to a hire based on long-term team impact—that's the shift from closing at all costs to creating long-term value
• Invest in information architecture before building AI services on top; your underlying data has to be rock solid
• Create dedicated time for AI experimentation—a half hour between meetings isn't enough, context switching kills it
• Embrace "context over control" as a design principle across your people function, not just in comp decisions
• Trust your leaders to own the trade-offs; the people team that's always the blanket "no" disempowers the organization

Guest LinkedIn: https://www.linkedin.com/in/tcastellanos/

Company website: https://about.nextdoor.com

Sponsor
This episode is brought to you by Kinfolk, the AI service desk built for HR.

See more at kinfolkhq.com

Summary
Vidyard's performance system was broken. Managers placed employees in nine-box grids with no clear expectations, no career framework, and no two-way conversation. Decisions on compensation and promotions happened in silos, riddled with bias. Employees felt the process was opaque and unfair — yet Sarika Lamont, Vidyard's Chief People Officer, had no technology, no team bandwidth, and a business contracting through a SaaS downturn.

Three and a half years later, she's rebuilt the entire system — career frameworks, competencies, performance reviews, and now an AI-powered interactive tool that took five minutes to prototype. What once required two quarters and a team of specialists now happens in a week. In this episode, Sarika walks through how she dismantled a one-sided performance process, designed for scale during contraction, and used Claude to compress months of work into days — all while solving for what employees and managers actually need, not what HR traditionally builds.

Timestamps
00:01 How Sarika fell into HR from management consulting at a federal contracting startup
05:59 The broken nine-box system she inherited: no expectations, no framework, pure manager bias
11:28 Why cross-functional partnerships with finance and business leaders matter more than HR credentials
17:22 Building a career framework from scratch: IC paths, management tracks, and leveling for scale
23:35 The SaaS downturn, AI disruption, and why the system went stagnant
28:19 Using Claude to redesign competencies in days instead of quarters
33:55 What replaces the time saved: ongoing enablement, adoption, and human-to-human coaching
38:12 Where to start if you're overwhelmed: validate the real problem first, then ask AI where to begin

Takeaways
- Build your performance system from the business problem backward — not from what HR traditionally designs — or you'll solve for process instead of outcomes.
- Career frameworks need differentiation level-to-level so employees see the gap between "intermediate" and "senior" in concrete, actionable terms, not themes.
- AI compresses iteration cycles from quarters to days, but the time saved goes to enablement and adoption — the work HR has always neglected because building took too long.
- Start by validating what employees and managers actually need through exit data, engagement surveys, and one-on-ones — then use AI as a thought partner to fill the gaps you can't solve manually.
- Performance transparency isn't about revealing ratings — it's about documenting expectations, competencies, and decision-making frameworks so people understand how to grow.

Connect with the Guest
LinkedIn: https://www.linkedin.com/in/sarikal/
Learn more about Vidyard: https://www.vidyard.com/

Sponsor
This episode is brought to you by Kinfolk, the AI service desk built for HR.

See more at kinfolkhq.com