What if AI could act as a team of challengers, not just a tool that completes tasks? Yvonne Prang joins Giac Soliman to explain how she built a “digital board” of specialized AI agents to analyze strategy, finance, M&A, and people questions. She shares how she tests their answers, checks sources, and uses human judgment to improve the work. The conversation also explores why leaders need AI fluency and how governance can help promising experiments scale.
27 Sept 2026
From a mirage of spreadsheets to one budget model
A rewards leader needed budget scenarios for the board, and the pay review tool couldn't model them.
Nilan Vagh is Associate Director, People Operations and Systems at Zip, and instead of another mirage of spreadsheets he built the budget model himself in Google Apps Script.
He walks through it live on a fictional 250 person company, from a compa ratio heat map that feeds straight into the budget scenarios to the audit trail that makes the model defensible.
What we get into
Why ChatGPT and Codex were the accelerant and not the architect, with the business logic coming from his rewards lead. Why he builds almost everything in Google Apps Script, where a shared link won't open outside the company's Google login. Why he doesn't think vibe coding will replace HR software, at least for now, when people data needs security you can't vibe code. What he wants to build next, a rewards intelligence view that flags high performers whose equity has finished vesting.
About Nilan
Associate Director, People Operations and Systems at Zip, where his focus is increasingly shifting towards people infrastructure, governance and AI enabled workflow design. He builds internal products across People and Culture that turn fragmented, judgement heavy work into governed decision support. He speaks here in a personal capacity.
13 Sept 2026
The vesting cliff your joiners hit in year five
Four year equal vesting with refreshes on top looks generous until year five, when it drops off a cliff.
Colette Leung is Head of Total Rewards at Chainlink Labs, and she built a simulator to show what a new joiner actually experiences rather than what the grant letter says.
She models the alternatives live, including the front loaded schedules she thinks Robinhood and others have explored, against a market competitive line.
What we get into
The first thing she ever built with AI, which was a working manual of her manager. Why she thinks the development work has shrunk from about 70% of a build to maybe 10%. Moving long term incentive off Google Sheets into a system carrying 1,200 users. What she would fix with a magic wand, which is quantifying the difficult to quantify.
About Colette
Head of Total Rewards at Chainlink Labs, based in the Netherlands. She transformed the long term incentive programme and built an in house equity platform supporting 1,200 plus users. 15 plus years across high growth technology and consulting, including Uber and Deloitte.
Show notes at range.community (http://range.community).
30 Aug 2026
Build the thing nobody asked for
Martin Smit calls his weekend builds nonsense, a gardening site one month and an art site with 200,000 pieces on it the next. The same habit has now read the annual reports of the 10,000 largest companies in the world, and he runs the whole thing on 500 dollars a month.
16 Aug 2026
From 4 hours of job matching to 10 minutes
Greg Laney has spent over twenty years between compensation and HR technology, most of it running Workday and HRIS strategy before pivoting back into comp roles. Job matching is the part of the work almost nobody says they enjoy. A manager sends over a paragraph, and somebody has to turn it into a survey match, an internal level, a salary grade and an explanation that manager will accept.
He built the thing that does it. It started as a ChatGPT agent at home that wasn't good enough, became a Copilot version at work that cut four hours a day down to about ten minutes, and is now an n8n workflow he put together in roughly four hours. Submit a job description and it checks the market survey, the internal job catalogue and the salary structure, returns a primary and a secondary match with a confidence flag, drafts the email to the manager, and writes the whole run back to a spreadsheet so anyone can see six months later why the job was graded the way it was.
01:38 Recruiting, Hay points, and the mentor who taught him Access
03:10 Where to start when work only gives you Copilot
10:20 Job matching, the job nobody says they love
13:49 Screen share, the workflow walkthrough
24:15 How n8n reaches your other systems
29:01 How does it know your pay philosophy
32:37 The judgement AI hasn't caught up to
9 Aug 2026
Treat AI like the hire you'll never get
Theresa Cortese runs total rewards at Nirvana Insurance, with twenty plus years across retail, semiconductors, ed tech and HR tech. Her business operations team owns the metrics and can't see pay data, so every quarter two spreadsheets got checked against each other by five senior people. Too expensive to keep doing by hand, not big enough for an enterprise platform to make sense.
Her CEO had told the company that experimenting with AI wasn't optional and that everyone should build something that week. So she did. The system she shipped runs Google sign in at the database query level, compares any two calculation runs, generates payout letters explaining how each number was reached, and passed Q1 actuals for every employee. She had never opened Terminal on her Mac.
The frame she uses is the useful part. She treats it as an entry level headcount she finally got approved. She teaches it, checks it, and coaches it forward when it gets something wrong. She is clear that it cost her time before it saved any, and that her own knowledge of all eleven variable comp plans is what makes any of it safe.
00:00 Who Theresa is
00:55 How far she trusts the output
01:19 The first thing she built
02:39 Fifteen years of merit spreadsheets
03:10 Where the ideas come from
04:25 No mentor, a team that experiments together
05:10 Shipping V1 to IT
06:35 Version thinking and imposter syndrome
09:00 Whether Claude Code is actually hard
11:03 They process, they do not think
13:04 Does AI save time or create more work
15:34 Why startups underinvest in total rewards
21:14 The story behind the tool
24:24 Screen share walkthrough
30:03 Advice to her earlier self
31:40 What comp teams look like in a year
9 Aug 2026
How Compensation Teams Should Use AI
Arif Ender on why compensation teams need a product mindset, cleaner data, and stronger human oversight to make AI actually work in the real world.
9 Aug 2026
Why Starting with the Problem Drives Better AI Tools for Rewards Teams
Ryan Buhrke and Giac explore how to shift from dependency to empowerment with AI, especially if you’re ready to stop waiting for IT approval and start building.
9 Aug 2026
Pay equity analysis when you're not a data scientist
Ivan Nosov leads HR technology and AI adoption at Campari Group, and he's been running pay equity analysis internally using Claude Code. We get into how he built a protected pay equity repository from scratch, what it's doing to the operating model, and where he thinks team productivity with AI actually goes next.
9 Aug 2026
Why Focusing on Small, Risk Free AI Wins Accelerates Large Scale HR Transformation
Josh Lemon leads Total Rewards at Resideo. He's been embedding AI into his HR function without writing a line of code. This episode covers how.
We get into how he's automating job descriptions, a chatbot he built for employee engagement, and the review process his team runs with legal and cybersecurity before anything goes near production data. He's operating across multiple jurisdictions, so the governance piece isn't optional.
He starts small on purpose. Email drafting, job matching, holiday calendar population. Experiments that are easy to check and quick to walk back. He builds confidence at the edges before touching anything that matters.
We also cover how he measures success. He's looking at whether managers are making better decisions, whether employees are more engaged, and whether his team can revisit calls they used to make once and move on from. Speed is a byproduct.
If you work in Total Rewards and you're trying to figure out where to start, this one's a good reference point.
31 May 2026
From AI skeptic to builder: Evert Kraav’s Journey in Transforming Compensation
Evert and Giac delve into the transformative impact of AI tools in the compensation and benefits domain. They explore the learning journey, risk taking, and the impact of AI tools on productivity. Evert then shares a tool his team built to assist managers in communicating pay outcomes at Bolt.
Reach and audience
Public platform figures. Ratings count people who left a rating, not total listeners.
Apple Podcasts (US)
5.0 / 5
1 ratings
Spotify
5.0 / 5
4 ratings
Contact Range Podcast
Guest appearances
Books guests
Based on episode analysis; this does not confirm that the show is currently accepting guests.
Host of Range Podcast?
Claim your podcast to manage its listing and keep your show details accurate.
Pod Engine is an independent podcast discovery and analytics service and is not affiliated with or endorsed by this podcast. Artwork and show content belong to their owners. Full legal notice.
Explore this show Podcast research with Pod Engine
