Welcome back U.S. readers from the long holiday weekend. While you were busy celebrating the big 250 with food invented in Germany and fireworks invented in China, the federal government was gearing up to consolidate the 100+ HR systems that they are responsible for.

Hopefully it won’t take 250 years.

The Office of Personnel Management awarded a contract to Oracle to the tune of 400 or so million freedom dollars to overhaul and consolidate the HR tech mess at the federal level into one unified system. The ten-year project could eventually hit $1 billion, and I’d guess that might be very conservative.

I wrote about it all on Reworked last week.

There is, of course, drama about the award itself. Initially, Workday was picked more than a year ago via a no-bid contract. That seemed just a little suspect. Of course, Oracle is as suspect of choice with co-founder Larry Ellison on the president’s tech advisory council.

But let’s put all of that aside for a second. As hard as it may be, let’s also put aside the severe doubts I have that the OPM and Oracle can do this as well as promised. Time will tell but bringing together these systems will be painful and will have to not be torpedoed by multiple presidential administrations.

Instead, I played it straight and I offer four universal truths for HR leaders. The first one is whether a consolidation-only software thesis can truly work. Consolidation is great for system admins and government budget hawks but if the consolidation doesn’t deliver better results for agencies, it seems destined for politicized failure before it truly gets launched.

The other truths are in the post and if you’re an enterprise HR or IT leader, it’s worth a look.

And look, it is easy to clown on Oracle here for having the audacity to take on this huge task. It’s easy to clown on Oracle for being Oracle these days. They’ve let go of 20k+ people this year and blamed AI for it. They seem to not be getting hammered the same way their ERP peers are while still struggling in the same sort of ways. A project like this seems like a minefield unless you’re well connected politically on both sides of the aisle.

But I feel like that’s a cheap argument and as a U.S. taxpayer, I also feel obligated to hope that it comes in on time and under budget. Regardless of the outcome though, we’ll all get a front row seat to the show. And we can see how off the rails a consolidation of this level can really get.

What else is happening this week?

• The People Analytics Tech Market Just Hit $12.2 Billion. The market’s maturing, and Stacia Garr finds vendors unbundling consulting from the price tag as growth slows. They’re also quietly gutting the ethics guidance they used to give away free.

• Why Has Cost of Living Become The #1 Issue In The US? It’s More Complex Than Inflation.. Josh Bersin traces four decades of wage stagnation to one choice: pay productivity gains to shareholders instead of workers. Now everyone’s acting surprised nobody can afford groceries.

• Artificial Intelligence vs. Employee Wellbeing. AI wrecks employee wellbeing in seven distinct ways, Steven Hunt argues, from co-dependence to algorithmic anxiety to plain old isolation. His prescription is simple: no person should ever feel like they’re working for a machine.

• The Machine Is Only as Exponential as You. Jason Averbook digs into workslop, AI output that looks finished but isn’t, and pegs the cleanup cost at $9 million a year for a 10,000-person company. Everyone has the same AI model now, so what separates good work from garbage was never the tech.

• On Entrepreneurship, Panic Attacks, and Lightning Bolts. A fired client, a team revolt, and a panic attack in a cornfield make up Jason Seiden‘s real founder story, resolved only by a stranger’s voicemail offering to invest.

• It’s Not ‘Will AI Take Your Job.’ It’s Which Choice Your Company Already Made. Entry-level employment is down 16% in the most AI-exposed jobs, per Erik Brynjolfsson‘s research. Jess Von Bank‘s point: the question was never whether AI takes jobs, it’s which side of that choice your CFO already picked without telling anyone.

• The Hallucination of Competence. AI is a Dunning-Kruger accelerator, John Sumser argues: prose so polished we assume the thinking was ours, when a ten-word prompt did 99% of the work. His fix isn’t banning the tool, it’s reintroducing the friction that builds real expertise.

• It’s Hard To Be Principled And Employed. Laurie Ruettimann breaks down how CBS’s new owners fired a 37-year anchor for saying out loud that they were destroying 60 Minutes. Being pivotal to the most decorated show in America didn’t make him untouchable, and neither will your work.

• Introducing the Fraud Squad. “Candidate fraud is organized. Now we are too,” reads the tagline for Fraud Squad, the free community Stacy Zapar just launched for recruiters swapping notes on fake candidates.

• The Best HR & People Analytics Articles Of June 2026. The throughline of David Green‘s monthly roundup has moved from whether you’re using AI to whether anyone can prove it’s worth anything.

• The Traditional Career Ladder Doesn’t Really Exist Anymore. JD Peterson of Perceptyx breaks down the shift from change management to change capacity in this Matt Tatum interview. Really, it’s just leaders admitting employees can smell a training course from a real answer.

• I Came To This Country From Ukraine At 15. George Elfond writes about arriving in the US too scared to spend $4 on a hot dog, and the question that’s followed him since: how do you hand your kids opportunity without handing away the hunger that built it?

• Stories And People Are Everything. Brandon Giella pulled the actual data most of us are just guessing at: stories beat everything, LinkedIn beats every other channel for B2B, and reach without engagement is just noise.

• Someone Is Paying For This AI Summer. Humans training their own $2-an-hour replacements, Teradata funding its AI budget out of employee raises: Kristy McCann tallies who’s actually covering the AI bill. Her dare to CHROs: be the most human person left in the building.

• U.S. Economy Added 57,000 Jobs In June, Less Than Expected; Unemployment Rate At 4.2%. The headline unemployment rate dropped only because 507,000 people left the labor force entirely, which is a strange kind of bad good news.

• Trump Can Fire Federal Agency Heads At Will, SCOTUS Rules. The Supreme Court overturned a 90-year-old precedent 6-3, so independent agencies like the NLRB and EEOC are independent right up until whoever’s in the Oval Office decides otherwise.

Have a great rest of your week!

I am out of office this week so we have a special edition of The Turn as we look at the top work and HR tech stories of the year so far.

We’re halfway through 2026 and it’s been a helluva half year. So how do you sort through the stories?

Not every big story is actually big. Not every small story is actually small. So I attempted to measure how much a story actually moves the world of work, across six dimensions weighted by how much each one matters.

• Reach (25%) — How many workers and organizations are actually touched by this story

• Disruption (20%) — How far it breaks from the status quo

• Durability (20%) — Whether this is a structural shift or a flash in the pan

• Stakes (15%) — The dollar, market, or career magnitude involved

• Precedent (10%) — Whether it sets a legal, regulatory, or industry template

• Salience (10%) — How loud the industry conversation actually is

Each story is scored 1–10 on each dimension. The weighted scores combine into a single gravity total.

1. AI-as-restructuring layoffs go mainstream

This is the story of the year and it is not close.

Tech layoffs blew past 142,000 in 2026, led by profitable companies cutting to fund a roughly $700 billion AI infrastructure buildout. Amazon eliminated around 16,000 corporate roles. Meta cut around 8,000, about 10% of headcount. Oracle confirmed 10,000 plus. Workday trimmed 1,750 people and called it a reallocation toward AI.

AI is now cited in a majority of layoff announcements, even at companies where the actual automation is still theoretical. Oxford Economics has argued it is often cover for ordinary cost-cutting. Both things are probably true at different companies. What changed in 2026 is that "AI made us do it" became an acceptable public explanation, and companies learned fast that it was a better story than the alternatives.

On reach, this touches the entire labor market at hundreds of thousands of jobs and counting. On disruption, profitable firms cutting to fund AI breaks from the historical norm that layoffs signal distress. On durability, this looks like a structural reset of how companies think about headcount, not a one-quarter event. The stakes are enormous in human terms. And on salience, this is the dominant work-and-AI story of 2026 by a wide margin.

2. The entry-level job collapse

The other half of the AI-and-labor story, and arguably the more consequential one.

New-grad unemployment climbed to roughly 5.6-5.7% against a 4.3% national rate. Underemployment hit 42.5%, the highest since the pandemic. A Stanford Digital Economy Lab paper found a 16% relative employment decline for 22-25 year olds in the most AI-exposed occupations. Entry-level postings are down roughly 35% since early 2023.

The people this is happening to do not have LinkedIn audiences or industry contacts. They just have no way in. The career on-ramp is disappearing, and because it is slower-burning than mass layoffs, it gets less coverage. But the durability score here is high because pipeline damage compounds over years and is slow to reverse. Every year this continues is another year harder to fix.

3. Vendors pivot to a “platform of agents”

The entire HR tech category repositioned this year, from systems of record to what they are now calling systems of agents.

Josh Bersin framed it as the reinvention of Workday, and the product news backs it up. Early adopters are reporting recruiter capacity gains of 54%. Workday has promised 14 new agents by year-end and launched governance tooling including Agent Passport and Agent-Ready Tools to help organizations manage what the agents are actually doing. The Salesforce Agentforce partnership adds another layer to the platform play.

The reach here is significant: eventually this touches every organization running a major HCM suite, and through them most knowledge workers. The disruption score is high because repositioning HR tech from record-keeping to autonomous work execution is a fundamental change to what the category does. And the precedent score reflects that governance tooling like Agent Passport represents an early template for how organizations deploy and oversee AI agents at work. Whether the market is right that digital workers become the next platform layer is still the question. That every major vendor is making some version of this bet is not.

4. Mobley v. Workday sets the AI-hiring precedent

The first real legal template for algorithmic hiring liability.

In a landmark March 6 ruling, a federal court rejected Workday's argument that the ADEA does not cover applicants screened by a third-party system, letting the AI age-discrimination collective action proceed. The opt-in window closed March 7.

What this case is building is the first real legal framework for who is liable when an algorithm filters out a candidate. That answer matters for every vendor selling AI screening tools and every employer running them. The precedent score is the highest of any story on this list for that reason. Case law has long downstream effects, and this case defines the terrain for algorithmic hiring liability in a way nothing before it has. The reach is broad but indirect: any organization using AI in hiring has a stake in the outcome, even if they are not named in the suit.

5. Return-to-office hardens to five days

The hybrid detente is over at the top of the market.

55% of Fortune 100 companies now require five-day attendance, up from 5% in 2021. The federal government mandated full return. Roughly 47% of strict-RTO firms say they will discipline non-compliance. Actual measured attendance has barely moved.

The reach here is enormous: this affects huge swaths of office workers and the entire federal workforce. But disruption and durability scores are more moderate, because this is an escalation of an existing fight rather than a new rupture. The hybrid conversation has been going on for four years. What changed in 2026 is that major employers stopped leaving room for negotiation. Whether that holds as the labor market shifts is a different question. For now the mandate went one direction and the behavior went another, and that gap is the whole story.

6. The EU AI Act’s employment rules land in limbo

Regulatory whiplash for anyone building or buying hiring AI in Europe.

High-risk employment AI obligations were set to apply August 2, 2026. Then a May 7 provisional Digital Omnibus deal proposed deferring them to December 2027, with the original timeline still in force if the deferral is not formally adopted in time. Fines reach up to 15 million euros or 3% of global turnover.

The uncertainty itself is the story. Compliance teams are now planning against two possible timelines simultaneously. The deferral was supposed to reduce pressure. The result is more complexity, not less. The precedent score here is high because the EU AI Act is the global reference point for regulating employment AI, and what happens with the enforcement timeline will shape how other jurisdictions approach the same question. The framework will govern compliance for years regardless of when the clock starts.

7. The Deel-Rippling espionage war escalates

The juiciest saga in HR tech kept escalating all year.

Federal rulings in February and March let Rippling's RICO and trade-secret claims advance while letting some Deel executives off as individual defendants. Deel filed counterclaims. New banking records surfaced that Rippling says prove Deel paid the person who stole from them. And through all of it, Deel raised $300 million at a $17.3 billion valuation, higher than the year before.

The direct reach is mostly limited to the two companies and their customers. But the stakes are significant: two companies valued around $17 billion each, RICO and trade-secret exposure, and a fundraise that proves the market is not particularly bothered by any of it. The durability score reflects that litigation and reputational effects will run for years. The salience score is the highest of any story in the bottom half of the list. This one has been impossible to ignore.

8. Dayforce taken private

The year’s biggest HCM deal.

Thoma Bravo agreed to acquire Dayforce for roughly $12.3 billion including debt, with a minority investment from the Abu Dhabi Investment Authority. The deal is explicitly framed as a bet on expanding Dayforce's AI capabilities in an environment where public market scrutiny makes long-term investment harder to execute.

It ranks eighth. A $12.3 billion acquisition ranks below a lawsuit with no settlement, a mandate nobody is following, a regulatory deadline in limbo, and a corporate espionage saga. That is what happens when you weight worker impact over dollar amount. The stakes score is high, but reach and disruption are moderate: this affects Dayforce customers and the vendor landscape, not workers broadly. PE consolidating HCM is not a new dynamic even at this size. The immediate experience for the average Dayforce user does not change.

9. The FTC noncompete rule is officially dead

The sweeping federal ban is over.

The FTC formally removed the Non-Compete Rule from federal regulations on February 12 and shifted to case-by-case Section 5 enforcement. A subsequent action against Rollins covered around 18,000 workers, which gives a sense of the scale case-by-case enforcement operates at.

What replaced a national ban is a growing state patchwork that is in some ways messier to navigate than either clean outcome would have been. The workers noncompetes affect most are still subject to them in most states. The reach score reflects that noncompetes touch a large share of the workforce. But disruption scores lower because this restores the prior status quo rather than breaking new ground. The headline moved considerably further than the actual situation did.

10. Mercor and the “train your replacement” model

A genuinely evolving trend for recruiting and knowledge work.

Mercor, now valued around $10 billion, pays professionals hourly to teach their workflows to AI agents and runs an AI-interview-first hiring process for new roles. The company generated significant attention after Bloomberg coverage in the spring.

The reach score is low today: one company and a niche labor pool. But the disruption and precedent scores reflect what this model represents. Paying people to make themselves replaceable as a product built on top of a hiring platform is a structure that has not existed before. The durability score is moderate because it is still unproven at scale. This earns its spot as a signal of where AI-native work models may be heading, not as a story with current mass impact.

What are your top stories for the year so far? What do you think will happen in the rest of the year?

When I heard that Uber had blown through their whole yearly AI budget by April because they promoted tokenmaxxing (like many of their peers), I thought what I usually think when tech companies do something predictably dumb: Why is anybody surprised?

About a month later, the rideshare company let go of nearly a quarter of their HR team.

Okay, that was a little surprising.

Officially, Uber has denied any connection between these two events. But I have my doubts so I wrote about that in my Reworked column this week.

According to Uber leadership, HR was, “too complex and fragmented, with overlapping responsibilities, unclear ownership and teams operating too far from the businesses and partners they support.”

And according to reporting from HR Executive, of those remaining in the HR department, anyone still on a remote work arrangement is having it rescinded.

Here’s a guess that HR won’t be done with losing people.

Like so many tech companies, Uber is not struggling financially. Its first quarter gross bookings were up 25% and its YoY revenue is up nearly 15%. Of course, the stock market continues to not care about that — its share price is down more than 13% for the year as of this writing.

So they did what a lot of companies do: a very loud layoff of corporate’s favorite scape goat with the hope to appease the shareholder class.

Oh, we’re back to not being surprised again.

I am not a huge talker but I have a whole rant about the types of companies that throw HR under the bus like this. Like any HR department ever gets the benefit of the doubt when it comes to increased staffing in their department. Do I believe Uber was overstaffed by 340 HR people? No, I do not.

Do you know how many HR leaders I have talked to who have had to write multi-page business cases for the most ridiculous things? A six-month contract recruiter to cover for maternity leave? A single HR analytics employee when the business has asked for dozens of detailed reports from ancient enterprise systems?

Maybe HR did need a re-org. But the timing, the messaging, and the impact don’t add up for me. HR departments getting cut this significantly are for flailing businesses or mergers, not for a some complexities and overlap in a department.

In my column, my hope is that HR increases their presence in discussions about AI usage across the organization (not just for HR). I keyed in on three discussions HR deserves to be a part of. Take a read if you’re interested.

What else is happening this week?

• What Olivia Rodrigo and Robert Smith Can Teach Us About Enterprise Software Today. A Thomas Otter post with a music observation built in is two of my favorite things at once. He uses the Rodrigo-Smith Glastonbury collab to argue that enterprise incumbents can either coast on back-catalog nostalgia or take real risks and earn new audiences.

• Qualified, Interested, and Affordable Is No Longer a Valid Method for Employers to Measure Applicants. Time to QUAIL. Andrew Gadomski adds two letters to the old QIA framework, Understandable and Legitimate, to account for a world where fake candidates, fake recruiters, and fake job postings mean neither side of hiring trusts the other anymore.

• Crash Out With Me: A Letter to Corporate. Madison Butler published this anonymously because the pattern matters more than the details, and any Black woman who has tried to earn safety inside systems not designed to provide it will recognize it immediately.

• You Don’t Have to Say Yes to Money. Laurie Ruettimann on the Peter Thiel Dialog list and the prominent leadership authors on it: people who make a career preaching integrity should know who is signing the check.

• Pro-Worker AI, Explained. MIT economists cover the difference between AI that replaces labor and AI that expands what workers can do, and why most companies are defaulting to the easier path.

  The Work AI Can’t Do. Moe Carrick on connective labor: the unscheduled conversation, the noticed silence, and the manager who actually knows her people.

• What Jalen Brunson Can Teach Us About Team Building. David Manaster at ERE is with me on this: Brunson left money on the table so the Knicks could build a real roster around him, and they won the chip. You have to do a lot of things right, and it all starts with people.

• Is DEI Dead? Not According to New Catalyst Data on Workplace Inclusion. New data shows 80% of organizations remain committed to DEI, and that 55% have publicly signaled a retreat while only 34% have actually reduced their inclusion efforts. Sorry not sorry: still kicking.

• Toxic Workplaces Are Winning—For Now. New Businessolver data shows that the worst corporate cultures are 2x more likely to report significant financial growth. The pendulum will swing the other way… eventually.

• Ragan’s 2026 HR Tech Hot List Honorees Announced. Twenty companies on the list this year, some new names alongside the familiar ones like UKG, Rippling, Lattice, and Eightfold.

• How Remote Work Has Helped a Generation of Working Parents. Mothers of children under 5 have been in the labor force at higher rates since 2023 than before the pandemic, and some say they wouldn’t have had kids at all without remote flexibility.

• Growth of Data Centers and AI Expose Tensions in Organized Labor. Building trades want the construction jobs data centers bring; other unions are worried about AI taking theirs. The reality of diverging economic incentives can be brutal for working folks.

• Newsom Promised to Help Californians Build New Careers. Now, the Money Is Running Out. California’s high road training partnerships are getting little or no new funding in the 2026-27 budget. Promising a workforce agenda and not funding it is just a press release.

• Fake Candidate? Recruiting Impostor? Check Here. Stacy Zapar built a free, searchable database of suspicious emails, profiles, and domains used by scammers: 1,200+ flagged addresses and 170+ recruiter impersonators. Bookmark it.

• Now of Work Weekly Digital Meetup with Jason Lauritsen. If you haven’t tuned into Jason Averbook and Jess Von Bank‘s weekly show, catch up on this one with Jason Lauritsen and sign up to join on Fridays.

• When the Prediction Becomes the Verdict. Part two of Jess Von Bank‘s seven-part series: the Kentucky pretrial risk assessment tool deployed to reduce racial bias ended up giving racism a more defensible interface. Your AI governance team should read this one.

• Another Word for Technical Debt Is Maintenance. John Sumser on agents: the harness is 90% of the model, ages on a different clock than the LLM, and when the model improves, the guardrails built around its old blind spots quietly stop working. “Agent reliability engineer” might be the next job title nobody saw coming.

Make your writing more interesting

Last week, I shared a short guide about how to fix your brand writing. Of course, I had to promote myself at the end, but even if you don’t want to work with me, there are a few takeaways to make your writing stand out.

I actually don’t blame AI for all of the terrible writing you see from B2B brands. This has been happening for years before AI could write an em dash. Whether you use AI or not, there are some pretty simple fixes, though.

Swipe through the guide here, typo and all because I decided to push publish instead of sitting on it for days.

Have a great rest of your week!

Every time I think about Orlando, I think about the band O-Town and their 2001 hit All or Nothing. They were formed on the TV show Making the Band, created by the same guy who formed the Backstreet Boys and NSYNC.

(This was the pre-Diddy version of Making the Band, btw. I’m not looking to get cancelled.)

It’s not good music but when you are 19 and all the girls you liked watched it and sang along to it, well, now I know it for probably the rest of my life.

The earworm of that overproduced single came back to me as I saw folks online descending into Orlando for SHRM’s annual conference.

The first annual conference I attended was in New Orleans in 2009. It was tiny by SHRM standards but still pretty damn big. Something along the lines of 7,000 or so attendees. I met so many people. And as a credit to them, I talked on a panel on about using social media as an HR professional. They even paid for travel. Shortly thereafter, I lost my HR job for good and made the pivot into whatever this is.

I also have so many good stories about that trip that I won’t publish because walking to my hotel barefoot came after some memories that are now seared into my eyeballs.

I’ve been writing about SHRM for two decades now, though. I started my blog, Your HR Guy, in May 2006 and wrote about missing the annual conference then. My last post about SHRM was three days before Christmas. In between has been a rollercoaster of (a few) ups and (more) downs.

I get annoyed at the world’s largest HR association for a lot of (I think) valid reasons. They have lobbied on the profession’s behalf to make the laws that protect people in the workplace less effective. They sometimes act as if Toby’s flaw in the sitcom The Office was that he didn’t side with management more.

It also seems like not a great place to work. In addition to the two lawsuits I wrote about late last year, the whole “come to the office or we’ll send your job overseas” thing wasn’t great. As “The Voice of All Things Work,” they should at least be specific about what kind of workplace they want to represent.

As I’ve spent the last two decades picking at SHRM, they have only become bigger and more influential. There will likely be something on the order of 25,000 people at the show this week. Their membership has grown. The CEO has a bigger microphone than ever.

And personally, friends and colleagues are more intertwined with the organization too. They make hay at the conference. They publish books with them. They speak there. They write for them. They advise for them.

I get it. Some of them are fans and others are making the tradeoffs you have to make to pay the mortgage. Yet, I still can’t get behind SHRM. All or nothing, I guess. And maybe I’m worse off for it.

The great thing is that there are so many more communities for folks who want an alternative. And honestly, I’m a little jealous because my former HR career had very few other options. But I might not have started writing which means I wouldn’t be here writing to you.

So it worked out, and I am mostly at peace with the all or nothing part. I can only wish the SHRM attendees in my life the best time as you can have in Orlando. Good luck out there, learn something, make some connections or money, and come back refreshed.

And a quick Orlando airport tip: If you can’t get access to a lounge for some peace from all of the loud kids, the smoking lounge is quiet and probably only knocks a few days off your life. They would’ve sucked anyway.

What else is going on this week

• 80% Cut Jobs for AI but Got No ROI: Gartner Study. Gartner surveyed 350 executives at billion-dollar companies and found that cutting headcount to fund AI didn’t move the returns needle. The companies that saw gains used AI to amplify people, not replace them.

• The AI Outcomes Gap Is A Waiting Problem. Business leaders have decided the technology will get better and solve the outcomes problem on its own, so they’re waiting instead of changing culture, upskilling people, or measuring anything, argues Gabby Burlacu. That bet is not going well.

• The AI Layoff Wave Is Becoming a Powder Keg. AI insiders are minting generational wealth in the same quarter tens of thousands of workers are hitting the door, and Connie Loizos notes the historical precedent for what happens when that gap gets wide enough.

• What It Felt Like to Be an Applicant. Nearly two decades helping build the HR tech industry, then Shannon Pritchett entered the job market and found the whole thing remarkably broken even with her level of access and relationships.

• More Than Half of Young US Hospitality Workers Would Give Up 5% Pay Raise to Feel More Confident. New research from Attensi finds younger hospitality workers would trade a raise for training that actually builds confidence. Two-thirds said current training delivers information instead of practice, which is a polite way of saying it doesn’t work.

• Tech Layoffs 2026 Hit 149,935: Uber Cuts HR Days After AI Drained Its Coding Budget. Uber burned through its entire 2026 AI coding budget in four months, with nearly 70% of committed code now AI-generated, then cut 23% of its HR division. The company insists the two facts are unrelated.

• Amazon Warehouse Workers Allegedly Asked for a Raise and Were Given a Bounce House Instead. Amazon upgraded the pizza party to a bounce house when workers asked for higher wages. Thanks?

• Tollbooth. Indeed made sponsored listings the default and buried free postings. Brian Fink has the apt metaphor: a road everyone assumed was public just got fenced.

• Very Dry but Necessary. AI governance is prospective where financial governance is retrospective, and the people good at defining constraints are almost never the people doing the discovering, writes John Sumser.

• Ask the Analyst: What Are Best-Performing Organizations Doing to Move Beyond Traditional Best Practices? The best organizations ask what problem they’re solving before they ask what everyone else is doing, according to Nicole Roberts, Nehal Nangia, and David Perring. Turns out copying what worked somewhere else at a different growth stage is mostly how you get trapped.

• Sorry, Your Job Is Awesome! Laurie Ruettimann is launching a limited-run podcast for people who actually like their jobs and want to get better at them, and this is a great idea. There’s no shortage of content about broken workplaces.

• Your AI Content Problem Is Actually a Data Problem. The blandification problem isn’t a writing problem, it’s a missing inputs problem, argues Steve Smith. The shortest stave in the barrel is almost always real customer voice, and no amount of prompting fixes that.

• It’s Not an AI Problem. It’s a Bad Idea Problem. My post isn’t so sure this is an AI problem or a bad idea problem. A lot of brand writing was already bad before the models showed up.

• The House Always Trades Up. McDonald’s premiumization, Vegas losing its middle-class customer, employers hollowing out the dependable middle of the workforce: Mike Wood connects all three. The person being priced out of the drive-thru and the person being automated out of the job are the same person.

• 25 Days Off Wasn’t Enough to Recover From Burnout. Surgery, burnout, a lifetime of working since 16, and the finding that time off alone doesn’t fix it: Kat Kibben writes about all of it honestly.

• The Titanic in Plain Sight. AI deployment decisions and their workforce consequences are being governed by different people on different timelines with no one accountable for the gap, opens Jess Von Bank in a seven-part series. Subscribe if you aren’t already so you can read the whole thing.

• Making Sense of the Labor Numbers. The labor headlines and what’s actually behind them, from Mel Plett and Francesca Ranieri in a new Your Work Friends episode.

• Introducing The Humanity in AI Awards. Sounds like an oxymoron, but Beth White is working to make sure the people on the other side of tokenmaxxing are recognized too.

• Human Capital Insider: June 2026. Kyle Forrest gives his monthly rundown of Gartner research and what’s moving in human capital strategy.

• Advocates Release New Report Urging Congress to Restore Federal Contractor Employees’ Rights After Trump’s Rescission of E.O. 11246. The right message aimed at the wrong audience, given the current composition of Congress.

• Oracle Wins $396M Federal HR Systems Overhaul Contract. OPM picked Oracle to consolidate more than 100 HR systems covering two million federal employees on a 10-year contract. Set your alarms for a decade from now.

• A Farewell to the Pay Transparency Newsletter. After three years, Anita Lettink is wrapping up her Equal Pay newsletter and moving to her Pay Time! newsletter. Subscribe there and follow her work.

• John Wilson Steps Down After 20 Years Leading Wilson HCM. Happy trails to John Wilson, one of the good ones. The kind of exit that generates comments like this doesn’t happen by accident.

Have a great rest of your week!

I’ll be 45 this year. Going back to the second half of the last century, this would be considered the mid-point in my career. Twenty years (give or take) ahead and behind of me. A kid growing more independent. Parents retired. A spouse in the midst of the same journey.

Things are changing quick.

While there has been a lot of talk about the impact of AI on employees earlier in their careers and decades of discussions about how, when, and what impact the Baby Boomer retirement would have on the workplace, not much has been written about people in the middle of their careers.

Some new research from Lynda Gratton, a professor of management practice at London Business School, has shed some light on what’s going on. Gratton has specialized in studying our increasingly longer lives and its implications for work.

That was what I covered in my Reworked column last week.

What stuck out to me about the research was how much about the mid-career journey was about identity, not performance. Nobody talks to you about exploring new potential paths as much. They assume if you’re in a role, you’ve been there for awhile, and you’re performing well, you’re on your way.

It can feel a bit like a career on auto-pilot. I know how it feels to be on that track. And once you’re earning a certain amount of money, changing course will likely cost you. You might have to get new credentials like my wife did when she became a teacher. You might have to build different skills.

If AI is going to change roles so completely, we have to be thinking about what a shift looks like for everyone, not just entry-level employees. Give it a read and tell me what you think. Any novel programs for mid-career folks out there?

Learning more about the career pivot

What has helped me as I think about what I might want to do for the next 20-30 years is reading what some of my peers have done. Lexy Martin, a legendary researcher and advisor, has taken to telling stories about it on her blog (aptly named) Redirecting.work.

The stories section is less a collection of mini-biographies and more snapshots of a critical moment in people’s lives.

Lexy has covered some of my favorite people, including Sarah White, Jess Von Bank, Chris Havrilla, John Sumser, and Ed Frauenheim. But some of the best stories are from people who I didn’t know as well or who seem so dissimilar to me or my current reality.

The whole series really opens your eyes to those moments that things change and what it can look like for people in a wide variety of circumstances. There’s something really comforting about that.

What else is happening this week?

• Labor Market Adds 172,000 Jobs in May, but Growth Remains Uneven. The number beat expectations, but most gains came from leisure, hospitality, and local government, and the majority of industries were flat or down. We’ll see if these numbers hold up through the revisions.

• AI Has Broken Hiring. Here’s How to Fix It.. Based on 120 TA leader interviews and 6,000+ screening sessions, Shraddha Sunil and Mudit Saraf make the case that companies are selecting for people best at navigating hiring, not best at the job. The fix is redesigning early-stage screening around reasoning and judgment instead of polished credentials.

• It’s Not Your Resume. The Stanford research everyone is quoting doesn’t screen resumes at all. It uses gamified assessments that sort by traits correlated with race, which is a very different problem, and Keirsten Greggs reads the actual study and explains what it found, including the part the “beat the ATS” crowd left out entirely.

• Two Things Everyone in Hiring Should Know. Same Stanford research, slightly different take (but with video) from Katrina Kibben.

• You Can Now Get a Religious Exemption From Using AI at Work. A software engineer filed a Title VII religious accommodation to opt out of AI at work and won. If ever there was a time to find religion.

• AI Saves Time but Most Companies Waste the Gain, Study Shows. Workers are saving hours every week and those hours evaporate because nobody told the organization what to do with them. This is how all innovation goes.

• Workers Turn to Social Media for AI Training as Employers Lag. If you don’t want employees learning AI from TikTok, you better figure this out.

• AI Is Creating a ‘Joy Paradox’ at Work, BCG Finds. Sixty-seven percent of regular AI users say job satisfaction is up, but 47% say they’re spending more time managing AI than doing actual work. Turns out getting gaslit by and correcting AI outputs has a cost: our sanity.

• Opinion, Not Evidence, Is Driving RTO Decisions. RTO mandates are following CEO sentiment and competitor headlines rather than any real analysis, and Peter Cappelli lays out the case plainly. Still so much management by feel.

• What My Son’s Graduation Taught Me About Rewiring, and Why It Has to Happen Twice. The commencement speaker quoted Keats on “negative capability,” the capacity to sit in uncertainty without reaching for easy answers, and Jason Averbook spent the rest of the piece applying it to every executive he knows. The Keats is real and it’s still relevant.

• Everything’s an Infomercial. The modern long-form LinkedIn post uses the same value-stacking structure as the 1949 Vitamix infomercial, and John Sumser nails what’s true about the content landscape right now.

• EU Pay Transparency Directive. June 7th marked a key implementation date with only three of 27 EU member countries compliant so far. Anita Lettink covers where things stand and why the rest will probably wait until enforcement bites.

• A Tiny Guide on Starting ChatGPT Ads. Want the TL;DR on ChatGPT’s ad platform? Viola Eva put together a quick-start guide covering formats, specs, and setup.

• The 2-Hour Job Search: Why Steve Dalton’s Advice Still Holds. The resume is not the problem. The strategy is. Good job advice from Laurie Ruettimann, who has doled out a lot of it.

• The HR Tech Landscape Moves Fast: New Podcast Worth Adding. In case your podcast list isn’t full, Stacia Sherman Garr and the RedThread Research team launched a new pod that promises to call out vendor BS alongside the signal.

• The Enormous Potential for Microsoft Frontier Fine-Tuning. It always felt like the enterprise was Microsoft’s to lose, and they were trying their hardest. Josh Bersin covers Frontier Fine-Tuning from Build 2026, which lets companies train Copilot on their own IP with reinforcement learning that improves over time, and makes the case for why they may still win.

• What Is Being Human? When intelligence stops being scarce, what’s left that’s distinctly human? Big questions in the age of AI from Kevin Wheeler.

• We Don’t Make All the Talent Tools. We Make Them Better. The real problem in talent tech is a lack of shared context across them, and AI is only as good as what you feed it. Master Burnett talks about the criticality of context, something worth being a little obsessed with.

• How AI Is Changing What It Means to Be a High-Potential Employee. Dan Schawbel asks what HiPo even means when expertise has a shrinking half-life and learning agility is the thing that predicts success.

• AI Gets Political. Recruiting Will Feel It. Public opinion on AI has soured fast enough that regulation feels inevitable, and hiring is the obvious target. David Manaster lays out what that means for TA: defensibility, transparency, and governance are no longer nice-to-haves.

• As-a-Solution: The Software and Services Convergence. The next era isoutcomes delivered smarter (not just cheaper), with agentic AI rewriting the unit economics so delivery stops scaling with headcount. Charles Bedard‘s new newsletter is already off to a strong start.

Have a great rest of your week!

I was still a teenager in the late 90s when all marketers apparently got together and determined that our lives were stupid and boring.

What did we need to make our lives better? Whatever we needed, it needed to be EXTREME.

Your sports? Extreme.

Your chips? Extreme.

You video games? Extreme.

Your deodorant? EXTREME.

Adding Xs or just dropping the E in front of extreme just added to how extreme something was. I even had one of the most extreme cars of the early 2000s: a Chevrolet Malibu Maxx.

I wish I was kidding.

The extreme marketing eventually (and thankfully) faded away. Until it didn’t.

Return of the maxx

There’s a whole Wikipedia page on the term “-maxxing.” You might’ve heard about looksmaxxing from the media somewhat recently but the suffix has been in use for longer.

If you don’t follow internet or gaming culture though, you probably have heard it in another context: tokenmaxxing.

With tokenmaxxing, companies set up leaderboards to encourage developers to max out their AI usage (typically measured by token usage). While your personal subscription to an AI tool may eventually run out of usage for a set period of time, these big organizations use AI via API, which will let you run it until you run out of money.

Some of the agents people were running were consuming 1000x more tokens than you would consumer from a regular chat session. People were using AI tokens for personal projects just to ensure they would stay top of the leaderboard.

Not surprisingly, this went poorly.

People who pay attention to pesky little details like money are sounding the alarm. CFOs are freaking out. The COO of Uber said that it was hard to justify the money spent on tokenmaxxing. An anonymous company blew through half a billion dollars of usage in a single month.

Maybe employees aren’t actually that expensive.

In spite of that, financial analyst say layoffs may continue as it is the only way some of these tech companies can fund their AI infrastructure, even if it’s not delivering value in the way they might hope.

This reckoning is coming at a bad time in particular for Anthropic, which has filed for IPO. Still, we shouldn’t feel too bad for them. After all, when is the last time the market acted rational? They’ll get their semi-truck full of cash.

What and how we measure matters

The real lesson here is that metrics matter when it comes to behavior. Companies told their developers to use AI. That they would be judged based on their use of AI. That high usage is what they wanted to see.

So employees followed suit.

Anyone who has studied human behavior knew what would happen. As The Conversation covered recently:

Metrics do have their place in an ordered and complex society. There are many instances in which we might happily defer to the scores produced by simple metrics, trading nuance for convenience. Aggregate ratings on product or restaurant review sites, for example, can simplify our decision-making, even if they aren’t tailored to our specific preferences.

The problem is what Nguyen calls “value capture” – when we uncritically allow external metrics to determine our own goals and behaviour. Resisting this process involves questioning what is being measured and reframing it.

You can’t solely manage a workforce based on the consumption of resources and hope that it translates to the outcome you want. When has that ever made sense as a long term strategy?

But in the AI land grab era, it seems to be par for organizations to do dumb things first and ask questions later.

What else is going on this week

• The Best HR & People Analytics Articles of May 2026. David Green built May’s roundup around Gartner’s finding that 80% of companies implementing AI reduced headcount without improving financial returns. Take some time with this one.

• Our Fears About AI Are Really Fears About Capitalism. The rogue AI scenario people fear is mostly just a description of what corporations already do, and the technology is amplifying the misalignment, not creating it. How well our needs are taken care of determines how scary the tool feels.

• Remote Work, Not AI, Has Sidelined Recent College Graduates. New York Fed researchers say remote work explains nearly two-thirds of the unemployment spike among young college grads, which is a less satisfying villain than AI and also, conveniently, fixable with return-to-office mandates.

• What’s Happening to Talent Acquisition Careers? (2026 Edition). TA employment declined for the first time in BLS data history in 2025, down 0.5%, and David Manaster lays out the honest version: the COVID correction may be nearly done, but whether AI has permanently moved the baseline is a question the trendline cannot answer yet.

• Five Years of Recruiter Research, Revisited. Madeline Laurano and Aptitude Research went back with Greenhouse to see what changed in the recruiter experience over five years. Calling it a sequel undersells how different 2026 looks from 2021.

• Master the Pivot: Resilient Leaders Need Learning Agility. The leadership content industry has thoroughly saturated the resilience topic, and most of it tells you to breathe deeply and embrace uncertainty. Donald Thompson actually addresses how to build the structures that survive it.

• What Cornerstone OnDemand Is Actually Up To. Dani Johnson was at Cornerstone Connect in New York and came back with a clear-eyed look at what the company is building, Workforce AI included. Way more useful than a press release.

• Fairness Is Not a Season. Structured interviews are twice as predictive as unstructured ones and remove most of the surface area where bias does its work, and if your commitment to fairness evaporates the moment it gets expensive, it was a campaign and not a value. Brian Fink writes this in June on purpose.

• While You Were Working: May 2026’s HR Regulatory Whiplash. EEO-1 reporting proposed for elimination, the Biden overtime rule officially dead, Colorado narrowing its AI Act, Illinois proposing new AI employment rules, USCIS disrupting green card processing for millions. Robin Schooling rounds it all up, and the list is not a metaphor for whiplash, it is whiplash.

• Salt in the Eyes. Mike Wood puts the EEOC’s push to kill EEO-1 reporting next to the Workday AI discrimination class action and names what’s happening: we’re sharpening the penalty and unscrewing the smoke detectors at the same time.

• Long Live a Liberal Arts Education. Learning to read history, argue from evidence, and write clearly turns out to be useful regardless of what technology does to everything else, and Josh Bersin makes the case on his 70th birthday. The timing with the college grad employment panic is not coincidental.

• Jevons’ Paradox, Engels’ Pause, and the Jobs Question. IKEA automated 57% of customer support, retrained 8,500 reps as Remote Interior Design Consultants, and generated $1.4 billion in new revenue instead of cutting headcount. Thomas Otter uses that as the anchor for an honest reckoning with AI and jobs.

• The Case for Recognition That Still Works. Recognition, appreciation, and gratitude are still the most effective tools for engagement and retention, per the HBR research Laurie Ruettimann is sharing. A little embarrassing given how much organizations spend on software to solve the same problems.

• The Hiring Manager of 2030. By 2030, the recruiter-as-coordinator is largely gone and the hiring manager loses the alibi that came with having someone else run the process, argues Kevin Wheeler. When the agent does what it’s told based on your inputs, the bad hire is yours.

• The Trust Collapse: Why Your Workforce Has Stopped Believing Your AI Strategy. Jason Averbook names the crisis underneath the AI deployment numbers: trust. Forty-eight percent of Q1 tech layoffs got attributed to AI while the same organizations were publishing content about augmentation, and workers can read.

• A Pattern Unlike Anything in 25 Years of HR and Work Tech. Decades in this market and George LaRocque says the current moment is unlike any of them. Article one of his new WorkTech intelligence series is live.

• I Ran the Experiment. Here’s What Sameness Costs. Five recruiting CRM hero sections tested blind produced a 57-point engagement spread with identical layouts and only the copy changed. Bennett Sung ran it, and the finding is that the category converges on abstraction because “strategic transformation” survives internal review and concrete claims don’t.

• What One Week and One Prototype Teach Us About HR Tech. Cliff Jurkiewicz spent a week building an HR tech prototype with AI-assisted coding and it exposed the same thing practitioners have been saying for years: most hiring software manages legal risk, not people.

• Hiring: Sr. Director, Portfolio Marketing at UKG. John Schneider is hiring at UKG for all my marketing folks.

• Hiring: Analyst Relations Director at Workday. AR in enterprise HR tech is an underrated discipline and this role touches most of the major research firms. Jennifer Neumann posted it.

• An Independent Resource for Research and HR Tech. Tami Nutt left Jumpstart HR and is available for research and HR tech advisory work.

• Open for People Leader Work. T. Tara Turk-Haynes is available as a fractional and advisory resource for people leaders.

• A New Chapter with a Benefits Disruptor. Kristy McCann met the Previ team at Transform two months ago, liked what she heard, and joined as a brand ambassador.

Have a great rest of your week!

I saw one share. Then a LinkedIn post. Then 10. Then all of the thought pieces came flooding in next.

Yes, a fintech unicorn-turned-dumpster-fire named Bolt “fired” their HR team. The Bolt CEO dropped this banger during an interview on stage:

It’s a dumb statement but there is an element of truth hidden in there somewhere, isn’t there?

HR is often built to create problems for bad leaders. In a regulated environment like financial services, that’s probably a good thing.

But HR isn’t above criticism. Sometimes they are too risk averse. Sometimes they do slow things down. Sometimes they are out of alignment with the organization. And their position makes them easy to target.

It happens.

But this isn’t getting coverage because every loves to hate on HR. It’s because Breslow is not a good leader and people love piling on. I love a good pile on and he deserves it. He built Bolt based on inflated metrics and what The New York Times called stretching the truth.

That’s called lying when you’re not the CEO of a Silicon Valley startup.

He stepped down from his role as CEO in 2022 when he called out Stripe and Y Combinator as being tech mobsters and gatekeepers. Even out of the CEO seat, problems followed. He hired a fraudster to build his social impact project Movement DAO and that predictably turned out bad. When he loaned himself $30M from Bolt and then defaulted, the company responded not by asking Breslow to pay back the loan but by buying out the investor causing a stink.

He returned as CEO and the hits continued, with valuations plummeting to just 3% of its eight-figure highs. Bolt’s promised SuperApp has fizzled. They continued layoffs and gave the old post-layoff pep talk to the remaining 100 or so people: “Everything will suck more but at least you still have a job.” Or something like that.

He even caused problems for another company named Bolt based in the EU, which had to clarify that their HR team still was around (and that they were hiring).

I think bad leadership press like Bolt’s is fun because the stakes seem relatively low. Like when Adam Neumann of WeWork or Elizabeth Homes of Theranos captured the attention of business press, the most consequential victims seemed to be a bunch of bankers, billionaires, and VC funds (in reality, employees got the short end of all of those sticks).

I also believe part of it is escapism. There have been so many consequential leadership failures, both in business and in the world, that a CEO that declares his problems solved by ignoring those problems is just plain funny. If Bolt flames out, we’ll feel bad for the employees and customers who bought in but we can live without it.

There’s probably something to learn here but not for leaders. Still, it can feel like we are growing as people if we can point out the mistakes and wonder what sort of lessons we can learn from the Bolt CEO.

There’s no lesson, though. A poorly behaved CEO of a hundred person company are a dime a dozen. Investors getting taken by a slick guy who cooked his books happens to even some of the best firms.

But hey, at least we had some fun reads.

What else is going on this week?

• AI Prices Are Going Up, Up, Up — Maybe Workers Are More Productive Than You Thought. Josh Bersin does the math on roughly a trillion dollars of annualized AI infrastructure spend and makes the case that Moore’s Law doesn’t apply here: prices are going up, the “adoption before value” era is ending not by choice but by invoice, and the organizations that thrive will be the ones treating AI as a capital investment with a real return requirement.

• How 100s of People Feel About AI Interviews and 5 Questions for You. Glen Cathey classified 486 comments on AI interviewing, found 79% objecting in some form, and then asked the harder question: what does the deal-breaker position mean for the 97% of Fortune 1000 applicants who are already invisible to human recruiters anyway?

• Hiring Is Missing One Thing. Her Name Is Sarah. Basketball meets hiring in Susan LaMotte‘s piece on Texas Longhorns walk-on Sarah Graves, whose case for the personality hire is sharper than most consultants can articulate. Sports has been scouting for ceiling over polish for decades, and early talent hiring still hasn’t caught up.

• Poppulo Acquires Sociabble to Forge the Future of Employee Experience. Congrats to Mark Brandau and the Poppulo team. I love the EX space and it feels like it will be coming back stronger than ever once we figure out that AI investment isn’t a panacea.

• Work Is Broken and Nobody’s Being Polite About It. Francesca Ranieri and Mel Plett pull in David Rice and Adam DeRose for a frank conversation on how messed up work is right now.

• Skills Are Particles. Stop Trying to Bottle Air. Jess Von Bank takes on the whole skills-based apparatus and argues that the industry spent a decade building infrastructure to measure a simulation of learning rather than learning itself. The real thing missing was permission to try something before you’re certified to try it.

• The Hiring Market Is Lying to You. Steve Smith reads past the record-high job posting headlines and finds a broken entry-level pipeline, a federal lawsuit suggesting the resume distribution industry may be a single monopoly operating under multiple brand names, and 44% of Gen Z workers sabotaging AI tools in ways the data says are accelerating their own obsolescence.

• AI, Productivity and the Bigger Question We Need to Ask. Mervyn Dinnen calls out the work design problem the productivity conversation keeps avoiding: AI gains concentrating in a handful of firms and regions don’t automatically translate to better outcomes for workers or places. That’s a design choice, not an inevitability.

• The Missing Workforce: Capacity Planning in the AI Era. Charlotte Zhang tells us what most workforce plans are still ignoring: agents doing real work and consuming real budget while appearing nowhere in the org chart, headcount model, or capacity plan. The case for a unified planning layer that treats token capital alongside salary cost is the kind of thinking that will feel obvious in three years.

• How SMBs Are Turning AI Into Growth. Gabby Burlacu shares Upwork research showing smaller businesses are moving faster on AI than the enterprise because they don’t have the luxury of waiting: 17% of SMBs have fully integrated AI-first process design and nearly 80% are increasing AI spend.

• The Primordial Credit Argument for Unconditional Basic Income (UBI). Scott Santens builds a UBI argument from David Graeber’s anthropology of debt and reframes the whole conversation: it’s the smallest possible acknowledgment of a debt civilization owes every person it brings into existence and can never repay. One of the best long reads you’ll come across on the subject.

• Leadership as the Operating System of Scale: Meg Bear. Marcin Murawski interviews Meg Bear on what it takes to scale leadership in the AI era, and her answer is that companies buying identical tools will be differentiated by the culture and mindset work no vendor can deliver.

• Is It Time to Measure Burnout? Heather Bussing cites research showing 86% of workers at moderate to high burnout and burnout as the single strongest predictor of diminished innovation capacity, with unclear AI role expectations now among the leading drivers. We should be talking about this a lot more than we are.

• Flexible Recruiting Expertise, On Demand. Congratulations to friend Robin Schooling and the BelleSage Partners team on the launch of this service.

• The AI Resist List. A catalog of workers organizing and pushing back on AI deployments that treat people as machine-interchangeable, from Kaiser Permanente hunger strikers to Amazon employee open letters. Hat tip to John Sumser for the share.

• What Good Thought Leadership Actually Looks Like. Jonas Barck on what separates thought leadership worth reading from content that just takes up space, and the observations land.

• Three Insights About HR Technology from the 2026 Acadian Ventures Conference. Steve Hunt finds the investor-organized HR tech conference clarifying because money focuses conversations on problems that actually matter. The sharpest takeaway: established vendors are restricting data access now that sharing it means funding agents competing with their own revenue streams.

• Things I Want Founders to Know. Alexis Fink also came away from Acadian Ventures with 15 things she wants HR tech founders to hear, starting with “be more curious about my problems than you are excited about your solutions” and getting sharper from there.

Have a great rest of your week!

“Now tell them we value our employees while laying a quarter of them off via e-mail.”

A meme circulating around based on a scene from The Truman Show is hitting on something we’ve all experienced: the world conspiring against us in a very specific way.

Going to work is starting to feel this way for many folks. As companies reverse course on being people-first, all while doubling or tripling down on AI investment, it feels like a rug pull that’s personal.

I’ve been working on some research, comparing what companies in the S&P 500 said in their 10-Ks in 2021 versus 2025. No shock that the language shifted, with 1 in 5 companies significantly pulling back language that focused on employee experience while amping up AI-focused language.

(BTW, one of the companies with the biggest shifts isn’t Silicon Valley tech at all. It’s Honeywell.)

These shifts aren’t unusual, even as AI feels like a more existential threat to folks we used to call white collar. In 1981 when Jack Welch took over GE, he spent his first four years ruthlessly cutting the organization down. Over 100,000 jobs from one company. All gone.

Industry Week called him “the most acclaimed SOB of the decade.” It was praise, not an insult. It shifted how companies managed people. Widespread downsizing worked its way across industries, even if there was no crisis. It was ruthless and probably a little coke fueled, perfect for the eighties.

Then in the 1990s, modern HR departments were launched. We started caring about the employee experience (before we knew what to call it). We invested more heavily in development, better recruiting practices, and the phrase “People are our greatest asset” spread faster than a cold at a daycare.

Did CEOs suddenly feel regret about downsizing as a workforce management strategy?

Probably not. Instead, the boom of the nineties created record low unemployment, skills gaps, and worker shortages. Demographics and economic success forced company’s hands. They had to be people first. People had choices.

That’s what I wrote about in this week’s Reworked column. While I don’t think we are doing a 90s repeat (which is too bad because I’d really like to see some of those bands again), there is something to learn here about how we get back to a more people-focused workplace.

Unfortunately, it’ll probably be because you’re in a competitive industry, a needed skill set, or we hit a level of demographic collapse that AI and automation can’t keep up with.

There are companies still living by the idea that people are their greatest asset but it’s not very cool anymore. But it will come back eventually. I think.

Take the Sapient Insights Group HR System Survey

Now nearing three decades, this report from Sapient Insights Group is one of my favorites to read and cover. It’s also a researcher’s dream. Decades of longitudinal data about the systems companies use to manage people, from the mainframe days, through SaaS, and now AI-led systems.

If you are familiar with your HR systems, I encourage you to take the survey and tell Stacey, Cliff, and the rest of the Sapient team what you’re currently doing.

Take the Survey

What else is going on this week?

• Road Report 2026: Workday Innovation Summit. Stacia Garr covers five bets Workday is making coming out of Innovation Summit, and the throughline is that the company believes its installed base and data depth are walls. Whether those hold against AI-first HCM challengers is a separate question from whether Workday believes they will.

• The Case for a Four-Day Week: What the Research Shows. David Green hosts Joe O’Connor and Jared Lindzon to argue the question isn’t how to get more from people, it’s how to get more from the time people already spend at work.

• Most Hiring Automation Stops at the Apply Button, Study Finds. 57% of organizations say they use automation agents in hiring; fewer than 1% have connected those tools into workflows that affect who gets hired. Jill Barth has it.

• Human Capital Insider, May 2026. Kyle Forrest builds on the Deloitte HC Trends finding that only 7% of organizations are truly adaptable, which means 93% of them think they are.

• ‘Doomjobbing’ Can Hurt Your Job Search. The term was coined by an 8-year-old watching her laid-off parent scroll LinkedIn for hours. At this point a book would be an improvement.

• Entry-Level Productivity Expectations Have Increased Due to AI, Report Says. 30% of HR professionals now favor hiring fewer junior workers, and 74% of those same organizations have no development programs to replace the on-the-job learning being lost. Efficiency win today, leadership gap in five years.

• What’s Coming for Meta This Week. Francesca Ranieri coins “Sitting Duck Syndrome” for the 78,865 Meta employees who know something is coming, don’t know what, and can’t do much about either. Productivity is not the prediction.

• Rebranding With Purpose. Pete Tiliakos and Amberly Dressler on rebranding in a category moving faster than the messaging, and they’re honest about what doesn’t work.

• Amazon Employees Forced to Hit AI Quotas Immediately Start Using It for Everything Except Work. Amazon introduced AI usage leaderboards and workers responded by gaming their token counts for personal tasks, a practice now called “tokenmaxxing.” Mandating a behavior with a metric is a reliable way to hit the metric.

• A New Labor Market Tracker at The Wrap. Mike Wood built a live unemployment tracker into The Wrap’s site, which is better than navigating the BLS directly.

• Reserved, Coveted and Contested: Decoding the Office Parking Lot. Robin Schooling argues who gets the reserved spot tells you more about the culture than the values wall ever will, and she’s not wrong.

• Kroger Facility’s Parking Lot Policy Violated Federal Labor Law, NLRB Judge Finds. An NLRB judge ruled a Kentucky Kroger distribution center unlawfully barred off-duty employees from the parking lot to solicit union support, and the HR rep made it worse by not telling the employee she could move to the sidewalk.

• The Most Useful AI Use Case So Far. Meg Bear on using Open Brain for meeting prep and synthesis, and why the value only compounds once you’ve used it consistently enough to see the pattern. More practical than most exec posts on the topic.

• Why AI-Obsessed Companies Should Care About the Aging Workforce. Workers 55 and older will account for more than 25% of the G7 workforce by 2031 while nearly every boardroom conversation is about AI and cost control. Dan Pontefract notes demographics do not care about your transformation strategy.

• Why So Many AI Initiatives Fail to Launch. Kristy McCann on why so many AI rollouts never get off the ground, and the explanation is more structural than most organizations want to hear.

• Who’s Your AI Bias Auditor? Bennett Sung frames bias audits as real data science work and walks through three pathways for who actually owns the function. Who you assign matters as much as whether you do it.

• CHRO Confidence Hits Record Highs as Hiring Surges. The Conference Board’s CHRO Confidence Index hit a record 59 in Q1 2026, with 59% of HR leaders planning to increase hiring, and retention listed as the “persistent weak spot” that will most likely undo all of it.

• TA Livestream Takeaways: The Humanity Premium in Hiring. As AI saturates the candidate experience, any moment with a real human has become the premium version, and most TA teams are cutting exactly those moments to fund their AI investments. Roberta Gogos writes it up from Lighthouse Research’s survey of nearly 2,000 candidates and hiring leaders.

• The AI Access Axis: The New Dimension of SaaS Pricing. Kyle James on how AI is adding a new access axis to traditional SaaS pricing models. The pricing layer is where real access decisions get made, long before anyone frames it as an equity conversation.

• The Million Dollar Sourcing Assessment. Balazs Paroczay argues watching a sourcer build a Boolean search in real time tells you more about their quality than reviewing their results. The gap between what teams think they’re doing and what they’re actually doing is expensive.

• Kids Claim Child Labor Law Violations at Roblox. A class action alleges Roblox profited from the unpaid labor of minors, with the lead plaintiff claiming he worked 40-plus hours a week between ages 11 and 13 doing game design for adult-led teams with no wages. Yikes!

Have a great rest of your week!

Back in the summer of 2024, Lattice rolled out digital workers on the org chart, complete with onboarding and (of course) performance management. I wrote on Reworked at the time that it was both bold and misguided. It was quickly shelved and forgotten by all but a handful of folks.

It turns out they were ahead of their time, both for their embrace of AI agents as kinda employees and for turning away from it.

Welcome back to The Turn. This week, we’re covering digital workers and unintended consequences.

New research covered in HBR shows what happens when we humanize the machines at work rather than treat them as they are: brittle, lacking accountability, and ultimately deployed by humans who should be monitoring their digital lackeys more closely.

First, let’s talk about accountability. The research showed that when an AI “employee” made a mistake, people blamed the AI. One participant even said, “The blame isn’t on a person; it’s on the technology.”

But who created, deployed, and monitored the agent? What happens when an agent delivers substandard work? What if it does something against the law? Certainly a person, not a machine, will be held to account.

When an AI “employee” created work, not only does the burden of review shift to a person (which has been well covered); they also reduced the confidence in reviewers. Of note from the article: “Several participants explicitly referenced questioning their own skills, doubting whether they had identified all issues, or feeling the need to re-verify work they would typically accept at face value.”

That also led to them catching fewer errors from worked framed as done by AI “employees” rather than an AI tool. Nearly 20% fewer errors caught on average.

Framing AI tools as employees also made people concerned about their own identities, with concerns about job security and lower trust in how the organization would use AI. As one person said, “If you want people to feel like they will lose their job to AI, or can be easily replaced by AI, then put it on the org chart.”

For organizations, all of that may not matter. We can deride people who reject AI “employees” as horse buggy enthusiasts, self-interested, or simply and stubbornly human. Yet adoption also shows no meaningful improvement when positioning AI as an “employee” vs a tool. Instead, adoption is driven the old fashioned way. Human dynamics, manager encouragement, and clear expectations drove actual adoption.

So all of those downsides and for what? You get to pretend you’re ahead of the curve, actively harming the work and employees with no improvement in outcomes?

It’s worth a read to understand how you can avoid all of this but the biggest learn: Words and positioning matter.

What else is happening this week?

• Life, Agency, and the Pursuit of Ozempic. Missed this one but Max Bayram ties Kyla Scanlon’s Ozempicization essay to Palantir’s manifesto to AI tools and lands on the same mechanism underneath all of them: the appearance of agency is the product, and the actual agency is what gets extracted in exchange for it.

• The Engineer Who Won’t Use AI with Andrew Norcross. Laurie Ruettimann interviews Andrew Norcross, who built the architecture for NASA.gov, the New York Times, and Disney, and now paints fences in Florida while waiting for the AI bubble correction he’s certain is coming. He won’t ship code he doesn’t understand, and “quadruple your AI costs,” he says, “and tell me it’s saving money.”

• Ten Years Later, I Still Believe in Better Technology. Shannon Pritchett is back with a new newsletter, and her reread of a 2016 sourcing article lands on the same indictment: the industry confused automation with innovation and the original assignment, giving recruiters visibility into people they couldn’t see before, still isn’t done.

• AI and Hiring Alignment Report 2026. Tim Sackett shared this, and Metaview’s data on AI in recruiting is worth a read for anyone who wants numbers behind the conference talk.

• Research: Why You Shouldn’t Treat AI Agents Like Employees. BCG and Boston University put it on paper: giving AI agents employee-style roles drops individual accountability, lowers review quality, and increases escalation, all without improving adoption.

• I Built My AI Brain 3 Hours. Jess Von Bank keeps building in public, and her “Judgment Stack” framework explains precisely why most people’s AI output sounds like everyone else’s: they stopped at identity and never got to reasoning.

• Agentic AI in Talent Acquisition. Madeline Laurano’s hosting a webinar on what’s changing in TA. This one is worth getting on the calendar (tomorrow!).

• OK Doomer: AI Isn’t Killing Jobs, Brought to You by AI Investors. Wait, What?. Steve Smith on Galloway and a16z both publishing “relax, AI won’t kill jobs” essays the same week Freshworks laid off 11% and credited AI: “That’s not analysis. That’s asset protection with a Substack account.”

• White House’s Hassett: AI Isn’t Costing Anybody Their Job Right Now. Kevin Hassett says there’s no sign in the data that AI is displacing workers, joining a chorus that keeps getting harder to hear over the layoff announcements.

• Most HR Leaders Think Their Job Is to Support the Business. That’s a Ceiling. Jennifer McClure puts it plainly: the seat at the table conversation is over, and the question now is whether you’re shaping the agenda or still asking for a chair.

• Job Descriptions Are Quietly Becoming the Dividing Line. Jason Lauritsen and Lisa Sterling on the podcast this week: job descriptions were built for factories a hundred years ago, and the best work on your team is probably happening outside the box you put people in.

• The Talent Assessment Market Has a Risk Problem. Charles Handler built an AI to track 400-plus assessment vendors and the finding that should stop you cold: at the highest AI risk levels, only 9% have an I/O psychologist anywhere in the process.

• The Workday-A16z Debate Has Five Smart Takes. Here’s What They’re All Missing. George LaRocque adds the one angle nobody brought: $24.5 billion into Workday-competitive categories since 2017, and the enterprise ceiling has held every single time.

• The AI Bill Is Coming Due, and CHROs Need to Be Ready. George is on a roll. Consumption costs are moving through vendor P&Ls into your renewals, and the average enterprise AI budget went from $1.2 million to $7 million in two years. Your CFO has entered the building.

• Hundred Years, All New People. Tyler Weeks on the time his boss couldn’t fire him so she announced his reassignment to the entire HR department, and what he learned from surviving it: the only real license to lead comes from discovering that the worst case was finite.

• The How #25, May 7, 2026. Kate Achille, newly promoted to CEO of The Devon Group, lost her dog Ruby Sue and went back to work the next day, and uses that to make the case that grief policies shouldn’t require anyone to justify who they loved.

• I SIOPed So Hard This Year. Alexis Fink on the Hot Ones session at SIOP: engagement surveys without follow-through are worse than doing nothing, and most analytics teams maintain dashboards nobody visits. Both true, both will be ignored.

• TechWolf, Deep Tech Meets Work Tech, Context Graphs, Transforming Work. Thomas Otter has money in TechWolf and says so, then makes the case that the context graph layer won’t be owned by the frontier model providers or the ERP incumbents, and explains why that’s the most important open question in work tech right now.

• Workplace Misconduct Hits Near 7-Year High as Reporting Confidence Rises. 55% of employees experienced or witnessed misconduct in 2025, nearly back to the 2019 peak, reporting confidence is at record levels, and the question of whether AI caused any of this or will fix any of it remains, so far, unanswered.

Have a great rest of your week!

“Hire by Google is the actual game changer recruiting needs.”

That’s what some idiot wrote in 2017 about an ATS launched by Google that would eventually only last about three years and change the game exactly nil.

Unfortunately, that idiot was me.

Welcome back to The Turn. Today, we’re chatting about tech giants that dabble in HR tech.

When you write for decades, you’ll inevitably have some misses. In my defense, it looked perfect for SMBs embedded in the Google ecosystem. I mean, this is what they launched with.

So it seemed really good, but it eventually (and, likely, inevitably) failed. It was a good lesson on when to balance nuance with a good, grabby headline. Maybe more importantly, it was also a lesson about software market dynamics, especially in HR technology.

Now a new tech giant thinks they have something to offer.

Last week, Amazon announced the launch of Connect Talent. It’s an AI-powered agentic hiring platform that conducts voice interviews, scores candidates on competency frameworks and hands recruiters a dashboard with transcripts and rankings. Amazon states it’s built on decades of the company’s own hiring science, and that it’s designed for employers who need to hire a lot of people fast.

My full analysis is on Reworked but after writing my column, the question I keep coming back to is a simple one: Why? Out of all the companies to copy a hiring playbook from, why would anyone in a high-volume hiring industry choose to copy Amazon’s?

From the outside, their high-volume hiring science looks more like something cooked up by Frankenstein. How do hires go from decision to onboarded to paid? At scale, those steps really matter if you want to do anything besides just make a better initial decision. And it really makes more sense when something like Connect Talent is embedded into a broader platform layer. Just ask Paradox. They already have real-life stories that Amazon wants to tell, too.

Also, what happens when Amazon figures out that selling HR tech at the enterprise level is a multi-year endeavor? At least Google was targeting SMBs with Hire, a market that often had less than a handful of decision-makers and incumbent technologies in-house. The change management alone at this scale won’t be fun for anyone.

That doesn’t mean Amazon is completely screwed. As an integration into existing hiring systems, it might make more sense to adapt what Amazon has built instead of building it yourself. And if you’re already developing on AWS infrastructure, it makes even more sense.

But hiring tech isn’t slowing down or waiting for Amazon. Ultimately, it still might go down as more successful than Hire or the Fire Phone. That’s not a high bar to cross though.

AI talent infrastructure is still catching up

How hard is it to find AI talent? Your view likely depends on where in the org chart you sit. New research from my friends at X-Team shows company leadership is super confident in their abilities to bring in AI talent. The people closer to where those people operate? They aren’t as sure.

While focused primarily on AI development talent, we are going to see the same trends as other functions adapt AI. Projecting high confidence from leadership while taking a sort of fake-it-as-you-make-it approach on the ground has a short expiration date, though.

The report also goes into my annoyance: Governance in name only, even for those concerned about governance risks.

If you are hiring AI talent, this is a good one.

What else is happening this week

• The Best HR & People Analytics Articles of April 2026. David Green has the sit-down reading for April, and the frame he opens with earns the whole list: this is less a test of technology than a test of leadership.

• The Definitive Guide to AI Adoption in Talent Acquisition. AI is everywhere in hiring, impact is not. Madeline Laurano finds most organizations have moved quickly across TA but are still running isolated use cases and calling it transformation.

• Atlassian Adds AI Enablement to Its People Strategy. Atlassian created a Chief People and AI Enablement Officer role, and put Avani Solanki Prabhakar in it. Unlike most announcements of this kind, the structural commitment here suggests someone might actually be doing this right.

• HR Tech Confidence Check, Spring 2026. Mercer’s spring check finds the same gap that has been there a while: shifting from simple investment to strategic alignment is still the move most HR teams have not made.

• Voice Is the New Interface. Greenhouse Just Made Its Move, Acquires Ezra AI Labs. George LaRocque talked to Greenhouse CEO Daniel Chait after the acquisition, and the bet is simple: voice is about to become the default hiring interface, and this is Greenhouse staking its claim early.

• Recruiting Brainfood, Issue 499. Hung Lee is one away from 500, and 499 does what you would expect from someone who has kept this going long enough to include a serious essay on organizational sense-making alongside the usual links.

• Somewhere Over the Atlantic, I Figured Out Why AI Adoption Is Broken. Always good to get a Jason Averbook update from 30,000 feet, and this one lands on something that isn’t just a runway: the technology is not broken, the system it was dropped into was never designed to be trusted in the first place.

• Workday and A16z. Thomas Otter offers some comments on the comments about Workday, and there is enough signal here that piling on with more observations would just get in the way. Just read it.

• Is the Workday Debate Really About Workday?. Steve Smith argues that anyone working in enterprise software should take this debate personally, because the real question it keeps circling is about the whole category, not the company.

• Ep 790: Rethinking Work in the Age of AI. Matt Alder and Stacey Harris talking is reason enough to listen, and the topic, what AI is actually doing to work and what the vendor landscape is supposed to do about it, gives the runtime something real to cover.

• Ethical HR Leadership. Laurie Ruettimann has a LinkedIn Learning course on ethical HR leadership, and the fact that she has to preempt the joke about whether that is an oxymoron tells you something about where the field is right now.

• Hurtful, Honest, or Helpful. Craig Hepburn gets closer than most to naming what the AI-and-jobs argument keeps skipping: the actual space between disruption and displacement, and what is happening there.

• A New Way of Entering the Job Market. John Sumser calls it a draft advice note, which is the honest label for a moment when the rules for entering the job market are still being written.

• 2026 RedThread Megatrends. Stacia Sherman Garr maps the five forces reshaping work, and the one that anchors the whole thing is this: they are bigger than either HR or the business, which means both sides need to stop acting like they control the outcome.

• I Just Launched the AI Pledge for Humanity. Here’s Why. AI leaders keep saying UBI is necessary, and Scott Santens puts out the call for them to actually prove it with real commitments, which is a reasonable test of whether the consensus position is a belief or a talking point.

• HR Snacks To Go: Kyle Forrest at Deloitte, Transform. Joel Stupka and Kyle Forrest run through the AI-plus-human equation in ten minutes, and the case they make for multiplication over addition is worth the quick listen.

• The Platform You Bought in 2021 Was Built for a World That No Longer Exists. Mike Wood’s counterpoint is worth the read: the TA software market has already had its Napster moment, not the slow-moving kind where incumbents get years to adapt, and the progress worth tracking is the kind that does not wait for them.

• 5 Lessons for Early-Stage B2B Brands. I got to talk to Bennett Sung about what he was building before he put it in writing, and what he is sharing here, category building, AI-augmented marketing, founder-led GTM, is the kind of playbook people usually keep to themselves.

• I-O Psychology and Predicting the Future. Gabby Burlacu comes out of SIOP with a concern worth talking about: what industrial-organizational psychology knows about where work is going and what organizations actually apply are two very different things, and the gap between them is addressable.

• Informed Does Not Mean Intelligent: Workforce Analytics and the Under-Appreciated Value of Context. Steve Hunt draws a hard line between informed and intelligent in workforce analytics, and the argument is that organizations calling data outputs intelligence are creating blind spots they do not know they have.

• Why Trust Is the Defining Asset of 2026. Three numbers from a Fast Company piece stopped Kristy McCann Flynn mid-read, and the case she builds around them, trust as the asset most companies are not measuring, is one worth thinking about.

Have a great rest of your week!

Welcome back to The Turn. Today, we’re talking about the exciting world of worker buyouts.

Microsoft is offering roughly 7% of its US workforce the option to retire early. The eligibility formula, age plus years of service totaling 70 or more, effectively targets its most tenured (and expensive) employees.

Buyouts aren’t exactly new. If they were a cure-all, every newspaper in the country would be thriving. I am told that is not the case, though.

While it is a novel solution in the tech industry, I’ve always had a problem with a voluntary buyout, even a targeted one.

The biggest issue: Voluntary programs don’t let companies choose who leaves. They let employees choose, and employees optimize for their own interests, which is reasonable but also entirely at odds with what the organization needs.

The employees most likely to accept the package are the ones with the strongest external options. They might have decades of enterprise relationships, networks, and a resume that does a lot of heavy lifting. Some will land at competitors. Some will start something.

Microsoft’s exit package becomes their runway.

The ones who decline are a more complicated group. Some are committed to seeing the transformation through. Some already tested the external market and didn’t like what they found. Some know they have topped out at Microsoft and want a few more years of their top earnings in their retirement accounts.

All of these are good reasons. For the employee.

Microsoft doesn’t get to distinguish between those outcomes. Layoffs aren’t inherently strategic, but they can certainly be that if done well. You make projected cuts based on the skills you need going forward, and you sell the people who you chose on why they are so needed.

Targeting their oldest and most experienced employees is also a gamble. These are the people who remember how the last several platform shifts actually played out inside a large enterprise. Not how they were announced, but how they actually went. They also have customer relationships that predate their current skip-level. They know which problems are structural and which are noise, which escalation paths work, which internal fights are worth having.

That knowledge isn’t in a knowledge base. It isn’t recoverable from a well-constructed prompt. It lives in specific people, built over years of being inside a specific organization.

Microsoft is betting AI absorbs what leaves or that what they actually need is a fresh start with fresh ideas.

That bet could very well pay off at the task level and maybe even a beyond. The judgment layer is a harder problem, and the people who carried it are now taking calls from recruiters.

What else is happening this week

• The AI Labor Debate: Three Views on the Future of Work. Carnegie lines up an optimist, a skeptic, and a muddier middle ground on what AI does to work, and the honest read is that all three might be right at the same time.

• Why Career Sites Are the Future of Recruitment. Matt Charney finds the gems in the thing recruiting teams love to complain about most. The case for owned channels over borrowed ones isn’t new, but the specifics here make it stick.

• Shaker RM Is a Stevie Award Winner. Congrats to Gina Alioto and the whole Shaker team on the Stevie win.

• The Talent Time Machine, Episode 16. Marissa Geist and Jason Scheckner dig into what it actually takes to break IT and HR out of their respective silos. Good conversation on the structural reasons this problem persists and what it costs when it does.

• MrBeast’s Company Sued for Alleged Sexual Harassment, Wrongful Termination. The excuses cycle through the same predictable rotation: startup energy, fast growth, isolated incidents. At some point the pattern is the story.

• The Market Isn’t Pricing Your Numbers, It’s Pricing Your Narrative. Steve Smith breaks down why ServiceNow and SAP command the multiples they do while Medallia doesn’t, even when the underlying numbers tell a messier story.

• Anthropic’s 81K Economics Research. Anthropic drops more research on AI’s economic footprint. How are CEOs so low on the displacement list, given that some of them are already running multiple companies at once?

• SkillCycle CEO & Founder Files Federal Lawsuit Alleging Predatory Takeover, Fraud, and Retaliation. Kristy McCann is fighting to take back the company she founded in an unusual way: in public. We usually only hear about this at networking happy hours at conferences.

• What’s Stalling AI Adoption in HR. Uncertainty about cost is doing more to slow AI adoption in HR than uncertainty about capability, says Stacey Harris.

• How Your Hierarchy Ensures Eventual Failure. Michael Carden taps into the structural reasons well-designed organizations eventually collapse under their own weight. Harder to dismiss than the usual org design takes.

• Intrateam IC Newsletter. If you’re doing digital transformation work inside a large organization and you’re not subscribed to Kurt Kragh Sørensen‘s Intrateam newsletter, fix that ASAP.

• Culture King at 30,000 Feet: Lessons from Shawn Achor at Total Rewards. Tom Short has a solid set of takeaways from Shawn Achor‘s session at WorldatWork in San Antonio. If you weren’t there, this is the next best thing.

• Your AI Prefers Itself. Steve Levy breaks down what happens when AI systems favor AI-generated content in recruiting, where the entire point is evaluating actual humans. Quiet problem, loud consequences.

• Your HR Tech Stack Is Being Rebuilt Around You. Do You Have a Voice in It?. George LaRocque brings the marketscape data into a conversation HR leaders need to be in. The stack is getting rebuilt with or without them, and that’s the problem.

• So Many Vegas Visits, Still So Few for Fun. Rob Pegoraro captures why Vegas is essentially a different city depending on why you’re there. It’s been a few years since a trip that wasn’t for an event, basketball included, and this one resonates.

• The Reinvention of Workday: From System of Record to Platform of Agents. Josh Bersin unpacks what Workday is actually building toward: less the place where HR data lives, more the foundation for AI agents working on top of it.

• More Output, Less Meaning: How AI Is Changing Day-to-Day Work. Interesting research on AI and workplace meaning, brought to you by the company that makes your business cards.

Have a great rest of your week!

Welcome back to The Turn. Today’s story is very, very dumb. But selfishly, I hope you read it anyway.

I wrote about Meta’s attempt to develop a photorealistic AI version of Mark Zuckerberg for Reworked. It’s kind of like the Tupac hologram that “performed” at Coachella a few years ago, but only if you like robotic technocracy instead of counter culture social commentary and sick rhymes.

Unfortunately, Zuck AI is built off of his human mannerisms and tone as well as public statements he’s made (including those made during earnings calls). Sounds captivating.

Of course, the company is investing in this initiative as they plan waves of layoffs starting in May (conveniently leaked out prior to its earnings call next week). Remember when layoffs indicated a company in trouble rather than one that investors flock to? Simpler times.

There are two issues here that are both simultaneously valid.

This is what Meta does

Meta sees a problem. Meta tries to solve it with technology first, seemingly unaware of the limits of how far a tech solution can take it. The Metaverse continues its slow collapse in spite of early promise. Workplace by Meta declined much more rapidly.

There’s not necessarily a flaw in the technology itself. Instead, what seems to happen is that Meta has a weird view on how people want to interact with and get from technology and spends ungodly amounts of money on the problem, only to eventually give up.

In that way, this approach isn’t unexpected. Meta has too many people to connect with their CEO in an authentic way. This weird stand in will certainly help, right?

It won’t. I don’t care how robotic and weird this dude is but he is who he is because of his humanity. This isn’t some Black Mirror episode where we can interact with someone’s essence. It won’t even be uncanny.

Let’s just hope they don’t spend another $70B+ on this one.

Connection is a legitimate challenge

And you know, I hate to give them credit, but the problem they’re trying to solve is a real one. Once you get beyond a certain size, connecting with employees as a CEO is just impossible. If Zuck spent every minute of a standard work week connecting with employees, they’d each get 90 seconds.

Think that’s bad? Walmart’s 2.1 million employees could bank on 3.5 seconds each. Hope you make a strong impression.

Which is why companies don’t try to do this at any sort of scale. They use sampling or focus groups and hopefully they don’t insulate a CEO too much from the real world problems. It’s why shows like Undercover Boss worked.

Most companies of that size have also figured out that the CEO isn’t even a great person to be connected to anyway. If you’re at Walmart, you’d probably rather be connected to your store manager or regional leader where decisions about your working life are more closely made. If you’re at Meta, you’d probably rather be connected to the senior leader of your department or your project team.

Please don’t do this

I don’t know why the folks at Meta think this is a good idea but it isn’t. I could make jokes for days about it, but at a time when thousands of people are being laid off by cold emails at 6 am, we need real human connection, not a synthesized version of it.

Trying to scale connection to the CEO will not work. It’s a dumb investment. I don’t want to ask an avatar for answers about my job or about the direction of the company I work for. I’ll talk to a human, any human, with some insight. And if it is just a video put together by humans whose job it is to communicate such matters, then that’s fine as well.

Did I say don’t do this already? Don’t do this.

Claude Design is live and it’s better and worse than I expected

Claude Design launched and I played with it (and completely exhausted my usage for an entire week).

The TL;DR version is like all things AI: Highly capable in plausible execution, less so with specifics and production-level quality. It takes some work to get it in good shape and there will be some very well executed slop.

Apologies to all my designer friends who will be feeling the annoyance that folks in the coding and writing trades have been dealing with.

What else is happening this week?

• Letting AI Do Your Work Erodes Your Confidence in Your Own Thinking. Passive acceptance is the key variable: the 1,923 adults who took AI answers without pushback reported weaker confidence and less ownership over their own ideas, while those who edited and pushed back came out fine.

• The Hidden Cost of Frictionless AI. reframes the cognitive dependency problem as “capability preservation,” which is more useful for organizations whose AI rollouts are producing faster but shallower work.

• 58% of Employees Plan to Search for New Jobs in the Next Year. Intent is cheap; the question nobody’s answering is what jobs these people are planning to land in, given how quickly the entry-level roles are being absorbed.

• If AI Were a Woman. builds a more interesting piece than the premise promises, including a first-person detour into Claude’s Design app that does real field reporting alongside the philosophy.

• How to Get Started with Claude Design. No mature design system, no clean results: that’s Brandon Giella‘s honest summary of a tool that works as a multiplier but not as a replacement for foundational design operations.

• Early Talent in Peril: Can Work-Based Learning Solve the Entry-Level Career Crisis? Six percent fewer early talent jobs since 2022, twice as many applicants per opening, and AI absorbing the work that used to be the training ground: Alexandra Levit makes the data hit harder than the talking points from Unleash.

• Writing from AI Defaults to the Mediocre Median. Jaclyn Schiff compares AI-generated LinkedIn content to Spotify’s recommendation bubble, and it’s a good one: algorithms optimizing for broad appeal produce content nobody asked for specifically.

• The Religious Right Is Being Recruited for the AI Crusade. The argument that Christians have a moral obligation to embrace AI, pushed by Peter Thiel, Katherine Boyle, and Trae Stephens, is a more substantive strategic play than the headline makes it look.

• HR Tech’s Moviephone Moment. Mike Wood launches a new site and opens with a Seinfeld reference, which is a strong editorial debut if you’re picking one cultural touchstone for where HR tech is headed.

• Purple Acorn Network Partners with PodStar to Scale Founder Voices Across the Future of Work. Congrats to Evan White: 30,000 monthly listeners and a partnership that gives real global distribution to a platform that has already outgrown its original lane.

• The Road to ERE: Part One. One of the better recruiting conferences on the calendar gets a preview, and Brian Fink‘s conversation with Ed Delgado on what sourcers actually need to do with AI is worth reading before Atlanta in May.

• The AI-and-Jobs Convo Gets Real: Talking Layoffs, Brain Fry and the SaaSpocalypse. Steve Smith argues the real displacement story isn’t just jobs. It’s also the software those workers depended on. What happens when the middleware layer collapses and the management layer built to oversee it goes with it?

• We Need to Do the Reps to Get Better as Talent Advisors. Working at something is still how you get better at it, and John Vlastelica‘s pushup analogy holds because talent advisor skills are built in actual conversations with actual hiring managers, not in training modules.

• The Payroll Problems That Never Change. More than a dozen years since I’ve done payroll and Stacey Harris and Sapient Insights are surfacing the same core failures: integration gaps, customization limits, and systems that don’t talk to each other, just with newer logos on the vendors.

• The Truth About California’s Fast Food $20 Per Hour Wage Law. Steve Boese reports that prices barely moved and job losses were modest, which dispenses with the main employer objections but leaves the more useful question open: when does this become a federal conversation?

• How Webinar Transcripts Drive Search Visibility by Anchoring to 3 SEO Fundamentals. Bennett Sung makes the case that one webinar can become five focused search pages, and the core argument that raw transcripts are an underused asset holds even if you skip the SEO scaffolding.

• Why AI Improves Employee Engagement for Some Organizations and How to Make It Work for Yours. Almost half of surveyed leaders report AI improved engagement while fewer than one in ten say it hurt. Those numbers look very different sitting next to the burnout and cognitive offloading studies published recently.

Have a great rest of your week!

We’ve developed a bad habit of treating individual talent moves like market research.

Someone notable leaves one software company for another, and within hours, there’s a hot take about what it means for the incumbent’s competitive position, its AI credibility, and its long-term viability.

The more senior the person, the more definitive the conclusion for some reason.

It’s gotten to the point where every hire announcement from Anthropic or OpenAI comes pre-loaded with a narrative about who’s winning and whose goose is getting cooked.

This is not a useful way to read the industry.

People move for a lot of reasons. It can be a role that turned out to be the wrong fit, a challenge they wanted to explore, or a working environment that suited how they actually want to work. There can be personal reasons or preferences, even for big-time executives.

None of those reasons are completely invisible in a job announcement, but none of them are completely visible either. What you see is a name, a title, and a press release written by a comms team.

I wrote on Reworked this week about Peter Bailis leaving Workday for Anthropic, partly because the coverage got some things meaningfully wrong, and partly because it’s an example of this broader reflex. From misreading what the title actually means to stretching the competitive angle, too much got skipped.

None of that is surprising. Nuance doesn’t travel well in a news cycle. But the cumulative effect of treating every notable hire as a verdict is that we end up with a lot of confident conclusions built on thin evidence.

The talent patterns that actually tell you something are aggregate, not individual.

• Which kinds of people are choosing to build at the model layer versus the application layer?

• Is the flow directional and sustained or scattered?

• What do dozens of moves reveal about where the hard problems are perceived to be?

One person’s career decision, for any number of reasons you’ll never fully know, doesn’t get you there.

We’re going to keep seeing these hires, and they’re going to keep getting this treatment. Don’t read too much into it on an individual level. Look for larger trends. I know it’s less fun, though.

Use AI to research in a way that’s smart

I’ve been annoyed by bad research since before Wikipedia and “Source: Google” citations.

The most annoying part is that people today have much more powerful tools at their disposal, yet they use them to synthesize the most boring conclusions. “AI is disrupting recruiting,” or “Entry-level jobs are changing.”

Wow. I definitely needed a summary on that.

I recently shared how I structure my general research process using AI. It is NOT a pretty process, and it is expensive as far as usage is concerned. But instead of a Reader’s Digest version of the news, it gives you an organized reading list to get you an in-depth read on what has and is happening.

What else is happening this week?

• Meta AI Lets Zuckerberg’s Staff Talk to the Boss — Meta built an AI clone of Zuckerberg so all 79,000 employees can feel connected to a CEO who apparently couldn’t manage it himself. Nothing says “we value our people” like a chatbot wearing the boss’s face.

• Gallup: Rising AI Adoption Spurs Workforce Changes — Half of workers use AI at least sometimes, but only one in ten says it’s actually changed how work gets done. Companies that adopted it are somehow hiring more and cutting more simultaneously, in case you were wondering who’s pocketing the productivity gains.

• Is Joy at Work Possible? — talked to Yolanda Fraction, who argues joy is more achievable than happiness at work because it doesn't require things to be going well. A genuinely useful distinction most workplace wellness gurus never bother to make.

• Zoomers Are Sabotaging AI at Work — Nearly half of Gen Z workers are deliberately breaking their company’s AI rollouts by leaking data, using unapproved tools, and submitting garbage output. The researchers recommend better change management rather than stopping the automation victory laps while threatening people’s livelihoods.

• Minimum Wage Hikes Are Quietly Raising Injury Rates — When the minimum wage goes up 10%, companies respond by working people harder rather than trimming headcount, producing two to three additional injuries per 1,000 workers annually. You got a raise and a repetitive stress injury.

• Workplace Management Tech Is Everywhere, But Integration Challenges Limit Its Value — Workplace management tech is widely deployed and barely anyone can get it to talk to their other systems. This sentence has been true of enterprise software since 1998 and probably won’t change with AI.

• Bosses Are Getting Worse. AI Is Part of Why. — Managers are outsourcing their judgment to ChatGPT, and their employees are cleaning up after it. Groundbreaking findings from the year 2026.

• The New Architecture of Work — AI is collapsing the cost of expertise to near-zero and most enterprise software was built for organizational structures that no longer make sense. proposes replacing static job titles with dynamic task categories, which is the right idea and one nobody will actually implement.

• Should AI Agents Be Treated Like Colleagues? — A journalist staffed a startup entirely with AI agents and was stunned when they argued, disobeyed, and questioned his authority. The answer to the headline is no, and 82% of deploying companies are going to learn that firsthand.

• The Remote Work Fantasy Breaks in Real Life — A designer who moved through nine countries concludes that stability produces better work than novelty. The files always come with you.

• Could Microsoft Win the War for Enterprise AI? — While everyone obsesses over OpenAI and Anthropic, argues Microsoft is quietly positioned to capture the enterprise AI market through Office, Azure, and existing customer relationships. The companies that control distribution usually win. Or at least that’s what the guy who poured me my IPA last night said.

• The Future of Work Is Here, But Hiring Hasn’t Caught Up — AI and automation have reshaped what companies actually need from workers, but recruiting is still running the 2019 playbook. The gap between how work has changed and how companies hire for it is where a lot of current talent pain lives.

• Zoom CEO Says 3-Day Workweek Could Be the Future — Eric Yuan, whose company nearly collapsed when offices reopened, is very excited about AI making the five-day week obsolete. A real study backs him up on the time savings, but he’s a CEO, so the question of who actually keeps those hours went unaddressed.

• The Agent Illusion — Most things vendors are selling as AI agents are just workflows with a better interface. ’s test for a real agent: Does it adapt to new conditions or just follow a predetermined path, and does it remember anything? This also might work on me.

• The Missing Layer in AI Transformation — CHROs are deploying AI without first getting clear on what work they’re trying to change. This is also what happened with every ERP, HCM, and workforce planning platform before this one.

Have a great rest of your week!

Welcome back to The Turn. Today, we’re talking about everyone’s favorite work technology company, Microsoft.

I say that semi-jokingly and semi-lovingly. My provincialism for the PNW extends to the folks up in Redmond. Seattle’s journey as a major tech hub looks very different without them. Creating 12,000 (or more) millionaires concentrated in one place will do that.

There have been many phases of Microsoft but they may be entering their most interesting one. As I wrote in Reworked last week, CEO Satya Nadella inherited a company infamous for internal politicking and frequent re-orgs under different fiefdoms more than a decade ago.

Now, under new-ish CPO Amy Coleman, the tech behemoth’s HR function is going through a consequential re-org of its own. No more chief diversity officer. People analytics moves directly under the HR org. And a newly named Workforce Acceleration team tries to capture the momentum of a stampede of AI usage across its sprawling global workforce.

They are also losing multi-decade HR leaders in talent acquisition, total rewards, HR business partnerships, and diversity. A century and a half of combined leadership will be gone.

One of those changes is big enough on its own. All together? It’s a lot. Maybe too much. But as Coleman wrote in her internal memo:

Stability has been the name of the game for Nadella’s turn at CEO. That has resulted in generally warm reviews from the investor class. But since last summer, the stock has been in a relative free fall (though the stock is still 9x what it was since Nadella took over in 2014).

And with how reactive the market is and how quickly AI is impacting SaaS software, it really is a “what have you done for me lately?” sort of environment. Thanks for those long term gains and the dividends. Now, show us more growth, more innovation, and, yes, probably more AI.

Will it all work out? Microsoft can afford to take some swings and misses in the service of getting closer to the bleeding edge. The risk of looking complacent (regardless of reality) is a probably the bigger risk.

But I don’t think this playbook is for everyone. I explain why in my column.

HR tech providers: Are you doing agentic AI for real?

I am writing a report on it and would love to get stories of real life use cases and outcomes rather than AI washing. If you have 30 minutes this month to walk me through what you’re doing, fill out the short form here:

Brief me

What I’m reading

I haven’t done this for awhile but I am LONG overdue to recommend some folks to follow across LinkedIn and Substack because I do an absolutely awful job of crediting for keeping me informed and inspired. To write a lot, you have to read a lot. Who am I missing on my reading list?

• Laurie Ruettimann is an OG who has been telling HR the truth about itself since before the industry was ready to hear it. You can read Punk Rock HR on LinkedIn and her newsletter on Substack.

• Steve Smith monitors the workplace technology market so you can stay current without having to read every vendor press release and funding announcement yourself, which is either a service or a calling. You can read Work Tech Weekly on LinkedIn.

• John Vlastelica named his newsletter after the thing he’s most tired of hearing from leaders, which tells you everything about his relationship with corporate pep talks and nothing about why we keep giving them. You can read Try Harder Is Not A Strategy on LinkedIn.

• Jess Von Bank writes at the intersection of work, technology, and humanity, which is the intersection where most organizations install a stop sign and call it strategy. You can read her newsletter on Substack.

• Katrina Kibben has spent years trying to get companies to write job descriptions that don’t immediately disqualify the people who could actually do the job, which is both noble and the world’s most patient Sisyphean project depending on your employer. You can read Rewrite Recruiting on LinkedIn.

• Dan Schawbel has been tracking workplace trends so consistently for so long, I’m convinced that future historians will cite him when trying to understand what people work was like right now. You can read Workplace Intelligence Weekly on LinkedIn.

• Madison Butler is documenting the corporate experience with the honesty that most companies’ engagement surveys are specifically designed to suppress. You can read The Corporate Crash Out on LinkedIn.

• Brian Fink has appointed himself the chief advocate for an industry that doesn’t always advocate for itself, which either makes him noble or means he has a very specific kind of energy. You can read The Talent Architects on LinkedIn.

• David Manaster has been covering talent acquisition longer than most of today’s recruiting platforms have been in business, giving him the rare perspective of knowing what this industry looked like before it got a rebrand. You can read ERE Weekly on LinkedIn.

• Hung Lee manually curates recruiting content every week from sources most people aren’t reading, which in an era of AI-generated everything is a principled stance (and maybe some pure stubbornness). You can read Recruiting Brainfood on Substack.

• Mervyn Dinnen is still making the case that HR is actually a business function, which is apparently a necessary argument in any organization where the people team is still fighting for a seat at the table. You can read HR Means Business on LinkedIn.

• Mike Wood reads all the HR tech news every week so you don’t have to, and in an industry that produces this volume of announcements and rebrandings, that is genuinely a public service. You can read The Wrap on LinkedIn.

• Jennifer McClure is still using “disrupt” without apology, which is a statement of conviction and proof that she really is the founder of DisruptHR. You can read Designed to Disrupt on LinkedIn.

• Donald Thompson releases his leadership insights monthly, which is a sensible pace for ideas that take longer than a quarter to actually implement. You can read Leadership Edge on LinkedIn.

• Joel Stupka gives us snackable content that, even if you aren’t 100% sure you like it, only lasts a few minutes (but that has always worked out for me). You can read HR Snacks on LinkedIn.

• Kyle Forrest is Deloitte’s Human Capital CMO moonlighting as a newsletter editor, which means you get the enterprise view on what HR should be thinking about, curated by someone whose firm has thought about it for longer in private. You can read Human Capital Insider on LinkedIn.

• Thomas Otter has been tracking HR technology long enough to have watched multiple generations of “revolutionary” platforms become legacy systems, which gives his reflections on work tech a certain earned quality. You can read Work in Progress on Substack.

• Jason Averbook has spent decades at the intersection of HR and technology, which means he has had a front row seat to every overpromised implementation and every genuinely transformative shift (and can apparently still tell the difference). You can read Now to Next on Substack.

• Anita Lettink has made it her mission to decode the EU Pay Transparency Directive before it decodes your organization’s entire compensation structure first. You can read Equal Pay on LinkedIn.

• Steven Hunt started as a mathematician and became an organizational psychologist, which is the most logical career arc for someone who eventually concluded that people are the hardest variable. You can read Talent Tectonics on Substack.

• John Sumser has been the HR tech industry’s resident skeptic long enough to have earned the right to say “I told you so” about several things that are now considered conventional wisdom. Heather Bussing continues to play the role of counselor (in all ways) for the industry. You can read HRExaminer on Substack.

• Josh Bersin covers the entire HR technology and talent landscape with a research operation that makes you wonder if he sleeps, or if the real Josh Bersin is actually a very well-trained AI model by now. You can read Josh Bersin Unleashed on Substack.

• Kevin Wheeler has been writing about the future of talent since the future was still largely theoretical, with both incredible foresight and a field that is just catching up to things he was saying years ago. You can read Future of Talent.

• Meg Bear and Amy Wilson decided two newsletter authors are better than one newsletter author (or one podcast host), which is either a sign of shared passion or a mutual inability to commit to a solo project. I like both of those. You can read Insight Loop on LinkedIn.

I am sure I missed some folks (or maybe you don’t post enough!) but I’ll share more inspiration on the reg.

That’s it for this week!

He ended up at a Temple of the Dog rehearsal instead, more or less by accident. Somewhere in that session, Chris Cornell needed him on “Hunger Strike,” a song that became one of the defining tracks of a decade of Pacific Northwest grunge.

The rest is history.

Serendipity probably isn’t a good way to justify the mechanics behind a killer song or a user interface for SaaS. But it’s what kept going through my head when I saw the announcement from Workday about Sana’s “Superintelligence” offering, which is part connector, part agent orchestrator, and part deep AI chat capabilities for the enterprise.

The last part follows a trend which I’m not sure I like.

Visual interfaces have always been full of accidental on-ramps. You hover over something you didn’t mean to click and discover a feature you didn’t know existed. You scroll past a setting, you flip through a menu, you stumble, and you might find something interesting.

A visual interface has texture. It has information without asking. It has those moments of friction and serendipity that people have come to expect.

Chat has none of that. If you don’t know that you don’t know, well, then you don’t know. Even the stuff that it’s really good at, like pulling information from all over the place and making some semblance of sense, requires some level of knowledge to even ask.

It’s easy to make fun of a dashboard that looks like it was created when the Seattle Supersonics still existed. But those usually existed because someone was making a decision based on it.

I will say that for users with motor impairments or low vision, chat with voice enabled can be a genuine step forward. Have you ever had an accessibility feature read you a data chart? Don’t (unless you need it). A chat interface that can be descriptive instead of visual is a godsend.

For regular users of ChatGPT, there’s probably a level of comfort (especially at the beginner level). But for power users, for those who really need the full ugly functionality of these enterprise tools, it’s going to be a sidestep at best.

Natural language chat interfaces are built for ambiguity. That’s why they are so good for beginners. But strip all that away and the supposedly frictionless interface requires you interact with a different level of precision. You train yourself to issue commands so that you get expected results. So your brain and fingers become a different type of UI.

Obviously Workday isn’t shedding its whole UI but other startups in HR have sort of embraced this chat interface as the default or, in some cases, only option. The move to position Sana as chat first might embolden them to push further.

I don’t think that’s wise.

Vedder wasn’t supposed to be in that studio. But the scene worked the way it did because people were in the same room, stumbling into each other’s orbits, and discovering things sideways.

The best interface might not be one that simply goes from taps or clicks to chats because it feels easier for everyone. Sometimes it’s the one that puts something you didn’t explicitly ask for in your path.

What else is happening

• Workers Are Using AI to Sneak Out for Spin Classes and Skip Lunch Meetings. A Zoom-sponsored study conveniently finds that AI saves workers 30 minutes a day, which sounds pretty sweet. Bosses paying for AI productivity tools may be surprised to learn they’re also funding spin class memberships.

• 3 Charts on What CHROs Think About AI and the Future of Their Departments. Nice story from HR Dive showing that every CHRO says AI is their top priority, yet half haven’t figured out how to measure whether it’s actually doing anything. Apparently “AI strategy” for most organizations means “we’re aware AI exists and are very worried about it.”

• HR’s Imperative: Invest in the Skills AI Can’t Touch. HR thought leaders are urging companies to finally invest in “human skills” like emotional intelligence and critical thinking, the same skills we’ve been systematically devaluing in favor of quantifiable metrics for the past two decades. Better late than never?

• JPMorgan’s Jamie Dimon Says Remote Work Breeds ‘Rope-a-Dope Politics’ and Stunts Young Workers’ Growth A billionaire CEO insists young workers can only learn by watching him make mistakes in person, despite research showing remote workers are more productive and more engaged. The 1,200 JPMorgan employees who petitioned against the five-day mandate still seem unconvinced.

• Report Reveals Widening AI Guidance Gap. Thomson Reuters finds that companies are enthusiastically pushing employees to adopt AI while having no coherent strategy for what that’s supposed to achieve. That’s fine, because only 22% of companies have any AI strategy at all. The bar for “ahead of the curve” remains comfortably low.

• Major League Baseball’s Robot Umpires Are Here—and They Tell Us Something Uncomfortable About AI and Work. MLB introduced an AI challenge system for ball/strike calls, framed as a thoughtful human-AI collaboration. Given that nearly two-thirds of player ejections were over ball/strike disputes last year, human umpires weren’t exactly making a compelling case for their own indispensability.

• Welcome to the Weird World of AI Agent Teams. Researchers discover that when you put a bunch of AI agents together without organizational structure, they spiral into chaos, a finding that will not surprise anyone who has never attended a corporate meeting. Coordination problems, it turns out, are not a uniquely human flaw.

• Who Owns AI Agent Access? At Most Companies, Nobody Knows. 85% of companies have AI agents running in production, but nobody has agreed on who’s responsible for securing them. That seems like detail worth sorting out before something goes catastrophically wrong. With agents routinely over-privileged and borrowing human credentials, the next major breach has essentially been pre-scheduled.

• Why AI Is a Massive Job-Creation Technology, Despite What You Think Josh Bersin argues AI creates more jobs than it destroys, pointing to rising software engineering salaries as proof. The “don’t worry, new jobs will appear… eventually” argument has a long and storied history of being technically correct and creatign short-term pain.

I just launched Beacon Turn

A little promotional news: I just officially launched Beacon Turn. If you’re reading this on my Substack, you know this.

You can read the full announcement on my LinkedIn and if you have any research, media, or advisory work, I’d love to chat about it.

Thanks and have a great rest of your week!

One of my favorite places in my town is the Vancouver Community Library. It’s located about 10 blocks south of my house and I walk past old homes, apartments, and businesses along a tree-lined street to get there.

The funny part about most of my library trips is very few of them involve me reading a physical book. Instead, I’m often doing work, writing, or research there when I am tired of my office and house.

I see all kinds of folks there too. I might see a parent and child exploring the children’s book section. I see a senior volunteering to help people prepare taxes. I see folks without housing getting a break from the elements. People of all types, really.

Sometimes I work better with murmured chatter. Other times, I want to be interrupted. While I love working out of my home office, it’s nice to have places you can opt into some level of social gather.

Plus, the view from the top deck where you can get some sunshine and views of the river, Portland, and the West Hills is nice.

(Oh, and hi old ZoomInfo HQ.)

I bring this up because I enjoy the sense of community I get from the library the same way I get from my favorite coffee shop, gym, or brewery. I see some of the same people consistently but also many different people. I’ve helped people find specific books or where to grab a decent sandwich (Tap Union if you’re okay with a little walk, btw).

But unlike a coffee shop, brewery, or gym, there’s no purchase pressure or access issues at the library. Besides the used book sale, there’s nothing really to purchase. It is open to all, where a person with a bike trailer full of their possessions has the same ability to access it as the high-paid lawyer who works across the street.

It’s a true third place. Not home or work but a third place where community can be built. In The Great Good Place, Ray Oldenburg says that third places are not just good for us but good for the world.

And I wonder if we need that for HR.

Creating a place that’s inviting by design

I tried to count the number of HR conferences or events that I’ve been to and I lost track. Hundreds, maybe? And while I like these spaces, they are limited by design. They charge money. They are in far flung locations. They are often built around an agenda with specific things that the organizers think you will like. The networking events are contrived and often revolve around alcohol or loud spaces (usually both).

And this is fine btw. Conferences in particular are big deals for people. They might be spending some of their own money or their employer’s money. They get to go to a nice place, learn something, and maybe even have a little fun. When I get cynical about all these events, I have conversations with folks who might only do this once a year and remind myself that they are important.

These events also have many of the same subjects, speakers, and sponsors. Some pay to get your eyeballs and earholes on them. That means there is stratification. Someone gets a VIP ticket to a vendor party with Third Eye Blind playing while someone else is scarfing down In-N-Out with a view of the High Roller (most of the time, I’d prefer the latter).

But if a conference isn’t a good third space, then what is?

I think social media used to be that place. But algorithms, advertising, and the eventual closed loop nature of them gets us the same problem we deal with in other access restricted areas.

Game social interaction or build early enough and you can stay ahead. But the average person probably isn’t doing this and they don’t have time for it anyway. There are few HR practitioners that really have the social following that matters. You can’t work your day job and produce the level and bulk of content you need to stand out now. Even with help from marketing and ghostwriting like some people use, it can be tough.

Places that are less algorithmic? Sure, but why would I look at those when I could read a LinkedIn update from two weeks ago?

What a third place solves for

The reason why I continue to wonder about this is that I think we get stuck in an echo chamber. A small group of people determine the experience, content, and more in HR.

As a former event organizer, I always tried to get perspectives from people outside of my world but let’s be honest, it isn’t easy. Plus, the format of events in general is hierarchical by design (and by necessity, probably).

With the online environment, I wonder if anything can really cut through in a way that connects people. There are probably pockets of it, especially in niche areas.

There are likely some local organizations as well but those come with membership fees or event fees because, well, space costs money. Someone has to foot the bill at some point.

When I look at all the handwringing and confusion in HR today about the future of the profession or how it will change, the leaders I know have to be intentional about creating their own little packs of colleagues and advisors. But, those things take time and time feels like the thing that escapes us.

But we also have to have a place where we can come as ourselves instead of peacocking around and pretending we have all the answers. Authenticity is thrown around a lot but in reality, it’s about creating a space where we feel comfortable with reality. Nobody has all the answers.

And while hierarchies feel comfortable, I can tell you that in private conversations, the biggest names that get in front HR audiences are questioning what’s going on just as much. They just have the ability to come up with better sounding answers.

Do we need this?

I don’t know. Maybe people feel like they have a sense of community already. But I think a space that operates as a community with fewer boundaries is a good thing.

I don’t have answers beyond that, though. I am interested in your honest take. Do we need something like this or do you get your fill elsewhere?

What else is happening

• U.S. Department of Labor Launches ‘Make America AI-Ready’ Initiative. The government’s latest workforce strategy is a seven-day AI course delivered entirely by text message. It’s designed to be accessible, quick and simple, which is another way of saying your AI education now competes with spam texts and verification codes. The future of work, apparently, fits in your notifications.

• HR Leaders Say They’re Optimistic Despite Anticipating More Change in 2026. Nearly three-quarters of HR leaders say they feel optimistic, but two-thirds also expect even more disruption this year. Culture, engagement and constant change are still major problems, and employees don’t actually share leadership’s confidence. So it’s optimism… with a heavy dose of denial.

• Report: CHROs Now Among Highest-Paid Execs at Public Companies.

  While workers watch their pay shrink, chief human resources officers are suddenly joining CEOs and CFOs in the boardroom penthouse. A Conference Board study shows CHROs appearing as named executive officers jumped 55% between 2021 and 2025, with AI hype and talent wars turning “HR” into code for high compensation.

• Half of Companies Are Cutting Compensation To Fund AI Investments. In the race to feed the algorithm, 54% of surveyed companies admit they’re raiding employee pay to bankroll AI projects. Bonuses, equity and even base salaries are all on the chopping block, and many bosses plan to smear tiny “peanut butter raises” evenly across staff. Cutting compensation to pay for robots. What could go wrong?

• U.S. Companies Plan to Accelerate Global Hiring Despite Major Workforce Headaches. Companies are expanding globally and hiring more—but also admitting they can’t find or keep talent. Nearly half say attracting international workers is “very or extremely challenging,” while burnout, turnover and “quiet quitting” are still wrecking engagement. So yes, hiring is up, but so is the chaos that comes with it.

• Why AI Job Cuts Are Turning Brutal. The era of cushy exits is over. Now people just lose Slack access and find out they’re fired. HR leaders say layoffs have become “sterile and surgical,” with less human interaction and more speed as AI reshapes companies. Turns out when efficiency is the goal, dignity is optional.

Have a great rest of your week!

Welcome back to another issue of The Turn.

I was able to get back to an Unleash conference, the first for me in more than a decade. I came in the day before and was able to plow through meetings, sessions, and some talking with vendors.

But, what got me was the keynote. Not on AI (as one would expect) but on failure.

Failure, by the way, isn’t a popular conference topic. Shocking, I know. Vendors don’t build booths around it. Nobody wants to tell stories about failures.

Amy Edmondson is different, though. She’s spent 30 years studying failure, and her argument cuts against the dominant mood of every AI conversation happening in organizations right now. “Our intuition about failure fails us,” she said. We learned failure was bad before we could reason about it.

Her framework separates failures into three types. Basic failures are preventable. They are often single cause in familiar territory and better systems can drive them toward zero. Complex failures are the perfect storms where multiple factors converge into a disaster that hinged on no single point.

Intelligent failures, on the other hand, are what you get when you run a real experiment in new territory: the outcome wasn’t what you wanted, but the information was exactly what you needed.

Intelligent failure has specific requirements. A credible hypothesis, a goal the organization actually cares about, and a scope sized to generate knowledge rather than to generate a report. Those exist because it’s supposed to teach you something. “An intelligent failure in your organization happening a second time,” she said, “is no longer intelligent.”

Edmondson described a conversation with senior executives at a financial services company who told her that failure might be acceptable in good times, but right now, facing uncertainty, “it’s important that everything go well.” Her response? “When you implicitly or explicitly declare failure off limits, you should expect to be kept in the dark.”

An AI story without the AI mention

That’s the AI implementation story playing out right now across most large organizations.

The pilots are staffed with enthusiastic early adopters with the conditions controlled. The goal, even when nobody says it out loud, is to produce a result that justifies the next stage of investment. Yet, the next stage inevitably fails to deliver value (like most AI initiatives to date). As she says, “the pilot didn’t prevent the fiasco, because the pilot was a success.”

A real pilot looks different. It runs under representative operating conditions. Its explicit goal is to learn, not to demonstrate.

What makes that hard isn’t process design, though. It’s what Edmondson describes as the anxiety zone: the environment where someone on the ground thinks “I’m afraid I need help. I can’t ask for it. I will look foolish.”

Organizations willing to say publicly where AI is working and where it isn’t, to treat the honest account as more valuable than the polished one, are going to learn faster than everyone performing confidence. The ones that can’t will find out what they missed when it’s expensive.

Education, early career professionals, and HR’s role

I was also invited to a discussion about how education is struggling to keep up with the changing needs of industries. It was a diverse group across workforce leaders, researchers, consultants, and folks like me who really wanted to hear what people saw as an opportunity.

Alexandra Levit led the discussion and it was enlightening. She’s the author of many books, including Make School Work, a focused look at work-based learning.

Reducing stigma about trades, better AI training earlier, and how we can create a national policy when so much of what we’re doing is run on a state-by-state or even down to an individual school level.

I came away with two takeaways.

Many trades have already figured out the high school-to-career pipeline. It’s one of the meaningful ways that districts have kept graduation rates steady while providing students with the opportunity to jump start their careers. White collar work could (and should) spend time learning from them.

The second takeaway is a little more troubling. As we are diving in head first into AI in education, I continue to wonder how we build up skills like judgement. One of the things I heard from Alexandra is that she can’t use anything out of Claude as is. How does she know it’s not ready for prime time? Years of experience doing work by hand. Seeing how words and numbers come together not only give you judgement, they give you taste.

Building taste and judgement has always just been a repetition game. Do things enough times and you figure out what good should look like and what it takes to get there. But if AI is doing the heavy lifting, how can you judge something as good or complete?

AI boosts developer performance (with a catch)

I’ve strung together a number of posts recently critical of AI, so much so that I got asked if I was anti AI at Unleash. My latest on Reworked talks about AI actually coming through on its promises: Freeing people up to do work. And, while AI has been lauded as an accelerant for mid- to senior-level developers, it’s actually doing numbers with junior developers.

Of course, that comes with a catch.

AI has killed a lot of the collaboration between development teams. Instead of asking a coworker how to solve a problem, they are solving it with AI.

Which, is good and bad. Good in that those senior devs can focus instead of fielding questions. But knowledge transfer? Judgement? The why behind why you do certain things? Those things are missing.

That’s what I worry about. We don’t understand the long term consequences of this, either. Maybe things will turn out fine. But instead of wishing and hoping, I wonder what we do to intentionally build skills necessary to be a good partner with AI if and when we use it. How do I know what to look for? What are my own tendencies as a human being with this very agreeable technology?

In the waning days of World War II, a Manhattan Project scientist named Vannevar Bush wrote an essay in The Atlantic that described a problem that feels as fresh today as it did more than 80 years ago.

The world was producing knowledge faster than anyone could absorb it. Every field was generating groundbreaking discoveries. Every discipline was advancing at breakneck speed.

The tools available to make sense of it all were filing cabinets, index cards, and more books and papers than a person could ever hope to read.

Bush called it a problem of connection.

We had learned to grow information of incredible volume. We hadn’t learned to connect it.

His proposed solution, the memex, was a desk-sized machine that could store libraries of material on microfilm and, more importantly, let users link items to each other. Rather than organize by category like a filing cabinet or keywords like an index at the end of a book, it would work the way a curious mind creates sense from noise. The way the electrical impulses that drive a human heartbeat can feel like the beat of a Green Day song.

The technology to build the memex didn’t exist, but the core principle of this idea would shape eight decades of grappling with a now evergreen challenge: Too much information, too little wisdom.

Technology catches up with the vision

Twenty-three years later, Douglas Engelbart demonstrated the mouse, the graphical interface, and live hyperlinks to a room full of people who had never seen any of it. It became known as the Mother of All Demos. Alan Kay took those ideas further at Xerox PARC, building systems that treated the computer as a dynamic medium for thinking, not just data processing.

Then Bill Atkinson, a programming genius working on the original Macintosh team, had a psychedelic-driven vision on a park bench in Los Gatos. Human knowledge was siloed. Physicists knew things. Poets knew things. Musicians knew things. None of them were talking to each other, though.

His answer was HyperCard, released in 1987. It was my first experience with what would become the building blocks of the modern internet.

It was a virtual stack of cards that lived on your computer that could be linked to one another dynamically. Ordinary people with no formal computer training could build their own associative webs of knowledge. Teachers built learning tools, businesses built interactive knowledge bases, and I used it to build a choose-your-own-adventure style game that was about as sophisticated as you could imagine for an elementary school kid.

I believe poop was involved somewhere in the storyline.

Two brothers also used it to build a strange, contemplative game called Myst that became the best-selling PC game for nearly a decade.

HyperCard was, as Alan Kay later described it, symmetric. The person consuming information and the person creating it were on the same continuum. You could open any button and see how it worked. Like a jazz musician, you could use that knowledge play the same notes or you could iterate and expand.

Then Tim Berners-Lee, working at CERN on a NeXT workstation, built the first web browser. Inspired by HyperCard, the web as we know it today arrived. HyperCard faded as the web of information expanded beyond what we could store in a single computer.

But something important got lost in the transition.

We are building more file cabinets again

The web that actually emerged, the one we live in, is still mostly organized by taxonomy. Search by keyword, find your answer, and go on your way. The associative layer, the one where connections between unlike things produce genuine insight, mostly didn’t get built. Websites became self-referencing silos. Social media favored algorithms that give you more of what you already have.

We got abundance. We still didn’t get wisdom.

Information is cheap and plentiful. Wisdom is what you develop after you’ve seen enough information in enough contexts to recognize a pattern that isn’t obvious. It requires connection, not just retrieval. It requires someone or something that can look across the silos and say: These things are related, and here’s why it matters.

AI is arriving in organizations right now with a promise that sounds familiar. More information, faster. Cheap wisdom and abilities without all that thinking work. The implementations being built and deployed are largely retrieval and regurgitation tools.

Bigger, faster, and, sometimes, hallucinating filing cabinets.

AI is genuinely useful and it’s hard to describe how powerful it can be. We can’t build wisdom without knowledge. When I describe to my daughter how we researched before the internet, I might as well be talking about the Library of Alexandria.

But the way we use these tools is not solving the fundamental question that Bush was grappling with in 1945.

The tools that actually move people from information to wisdom are the ones that surface connections people wouldn’t have made on their own. They tell you not just what is true but what relates to what else, and why the relationship matters in your specific context.

When I see the information bloat, lack of vision or purpose, and thousands of copy and pasted AI posts that have the same beats, the same messages, and the same conclusion, I know we haven’t answered the fundamental question because we don’t even know what the question really is.

Connection, not collection

Every generation since (at least) 1945 has continued to make access to vast stores of information easier and declared victory. Certainly this will be the invention that solves our problems. Yet, information multiplies and we still feel like we don’t understand our world.

The hard problem is connection, not collection.

The tools we use to solve this problem reflect the assumptions of their builders. HyperCard was built by someone who wanted ordinary people to be authors to share their sense with the world, not just readers. AI is being shaped right now by the assumptions of the people deploying it.

Those assumptions are worth considering.

For example, when Anthropic publishes a study that reduces an occupation to collections of tasks and skills rather the connection of them, it feels like the record is skipping again. The theoretical AI coverage proposed is the type of fever dream that we’ve seen before.

There is genuine novelty with AI innovation (and, sure, a little bit of terror). That’s why it is so frustrating to see these abilities reduced to “answer engines” or debating which (contextually devoid, individual) tasks that AI can or cannot do.

Can AI help you connect with the world better? Can it create understanding where discernment is difficult? Can it help you make better decisions than you would’ve made on your own? Can it make you a better person or give you abilities beyond multiplying my own foolishness at unbelievable scale? Can it make something better that people actually want?

I think so because I’m a silly optimist, but it’s not how we’re using it.

I don’t want a faster, scaled up version of my thinking or abilities when it can’t crib the connections I’m making in my head. I don’t want a machine that can take the collection of tasks that makes me good at what I do without the ability to ask, “Wait, why are we even doing this?”

Someone still has to ask the right question. Someone still has to decide what the pattern means for this organization, this moment, these people, and find the right medium to tell that story so that someone who gives a damn will understand.

If all we are doing is just reinventing a faster file cabinet (again), then what the hell are we doing? Creating a brainless, context-less collection of information, tasks, and skills that can scale stupid work 10x?

I believe Vannevar Bush’s vision is still out of reach, at least in practice. It’s worth asking if we as people want to use the very capable technologies we already have to build wisdom or connection or if we are always going to try to settle for shortcuts and speed?

I think there is still a market for people who care about making sense out of noise rather than noise out of sense. Let’s hope so, at least.

A long, long time ago when I was still in HR, I watched two managers face the same crisis in different ways. Business was down, we had to shift people, and employees in the organization were frustrated and scared.

One gathered his team in a conference room the morning the news was going to be announced. He didn’t have all the answers, but he told them what he knew, admitted what he didn’t, and promised to keep them updated.

The other manager waited for the official talking points. When they came, he sent them via e-mail. By the time they got the sterile news, the team had already heard from their colleagues that change was coming.

A month later, both teams had the same leaders and a similar group of employees as they had before but very different levels of trust and performance.

Back then, all I had was vibes for what I saw. Clearly, the first manager was operationally better and a more empathetic leader. You could see signs of it in his employees too. But why did it seem like his team also buckled down more and were more willing to put in the unpleasant work to turn our fortunes around?

If the story is familiar, it’s because this pattern plays out everywhere. And now, SparkEffect (formerly Waldron and Torchiana)’s 2025 Trust in Turbulence report puts numbers to what many of us have seen up close: Trust is an operational variable that can predict whether teams hold together or fall apart when things get messy.

The numbers tell a simple story

When employees trust their leaders, everything works better. The key findings from the report shows that in high-trust organizations, 97% of people say their organization has strong financial performance. In low-trust environments, it’s less than half. Retention jumps from 52% to 93%. Even basic clarity about the company’s direction doubles.

Trust comes from how leaders show up every day. It manifests in how they explain decisions, handle uncertainty, and follow through when it matters. During disruption, those daily actions decide whether a team holds together or falls apart.

Where trust actually lives

The data also answers a harder question: who holds that trust?

It might surprise you that it isn’t the CEO or the executive team. Having worked with executives, I know big decisions that rock companies feel like a pressure cooker for them personally. They feel like everything they do is under a microscope.

But trust is really owned by the managers who talk to employees every day. People place far more confidence in their direct leaders than in “the organization.” But that confidence is brittle. When disruption hits, trust in their direct managers is what drops sharply. Their trust in the broad organization? It barely moves.

That should make every executive pause and consider where the pressure truly resides. The moment turbulence hits, the leaders closest to the work absorb the shock first. They become translators and stabilizers, all while trying to keep the work moving as if nothing was happening. If those leaders don’t have clear direction or support, the trust gap starts there and spreads fast.

The research makes a point that’s easy to overlook: leadership across the entire organization is strategic infrastructure. It’s as essential as having an office roof that doesn’t leak or a warehouse that has been upgraded to modern safety standards. You can’t build trust through slogans or one-off initiatives. You build it from the ground up by equipping managers to lead with clarity, fairness, and empathy. That’s especially true when they don’t have all the answers.

And when disruption happens, scaling your leadership capability is the only way to keep the value of trust intact.

When the waves hit

Every leader hits a moment when the room goes quiet. A tough call, a bad quarter, a change that lands wrong...

Values set the next move. They shape the words you choose, the tradeoffs you accept, and the people you protect. They decide who hears first, who gets context, and who gets your time.

Comfort tempts shortcuts. Values hold the line. They ask for plain talk when news stings. They demand fair process when speed feels easier. They keep promises in view when pressure shows up.

People watch the choices that their direct managers make. They see who they stand with, how they explain it, and whether they stay present when the room gets heavy. Those signals become the story employees tell about working there.

The teams that came out stronger shared four habits, and none of them are complicated:

• They communicate early and plainly, even when the news is rough

• They explain the “why,” not just the “what”

• They treat people with fairness and empathy in the moment

• They invite questions, even when they can’t answer all of them

Those actions sound basic, but they’re show up rarely under pressure. The report found that when disruptions were handled well, employee trust actually rose above baseline. When they were handled poorly, trust dropped by nearly 30%.

The elasticity of trust

SparkEffect uses the term “elasticity” to describe how well trust stretches under pressure and snaps back afterward. I love it. The idea is simple: some organizations absorb the hit, learn from it, and emerge steadier. Others crack.

In high-elasticity environments, employees say their companies retained key people, sustained reputation, and had a clear plan for the next challenge. In low-elasticity ones, those same scores collapse. Strategy clarity, arguably the foundation of leadership,bottoms out almost completely.

That’s what happens when trust runs out.

Most crisis plans focus on risk management: minimize damage, restore order, move on. The better leaders treat disruption as an accountability moment. They use it to show who they are when things aren’t easy. When handled with transparency and care, those moments turn into proof points of integrity.

Building trust on purpose

Trust can’t be built with values statements or an executive leadership retreat on purpose. It’s much more pragmatic than that. The research suggests four practical moves every organization can make to meaningfully support trust:

1. Support your frontline managers. They hold the most trust and the most risk when things go wrong. Equip them. Have them build a bank of trust when those hard moments hit.

2. Rehearse crisis leadership before you need it. Practice clarity and fairness in small moments so they’re automatic in big ones. These moment count and become evidence for or against your leaders.

3. Design fairness into decisions. Ask early: Is this clear? Is this fair? If I described what I did to an outsider, would they get it? If there’s hesitation, there’s work to be done.

4. Measure trust like you measure performance. What gets measured changes behavior.

Trust shapes the outcome of every disruption, from how people talk about leadership to whether they stay to help fix what broke.

What endures

Trust grows in the moments that test conviction. It takes shape through clarity, fairness, and steadiness when conditions shift. Each disruption becomes a record of what leaders chose to stand for.

Leaders who ground every decision in those values leave something lasting: a pattern people can rely on when change comes again. That consistency is the foundation of endurance, the quiet strength that carries a company forward.

That’s it for this week!

I’ve lost count of the number of HR Tech Conferences I’ve attended since my first one in 2009. In the dingy basement at the back corner of McCormick Place, the show was much smaller. You could walk every aisle in the expo hall in a brisk 5-10 minute walk. You could fit all the attendees in one of the breakout rooms used in 2025.

Maybe that’s an exaggeration, but you probably weren’t there.

The spectacle that exists today makes it impossible to get a feel for the room the same way you could 16 years ago. That makes me more convinced than ever that HR Tech is a reflection of our own experiences as much as it is a bellwether for what’s going on in the industry.

Feeling cynical about the crest of the AI hype cycle? You’ll find plenty of reasons to embrace the cynicism. A booth proudly proclaiming to be “like ChatGPT but for hiring” is both unintentionally hilarious and an indicator of how much AI has latched onto every last function of HR, whether buyers actually want it or not.

Feeling like innovation is starting to ramp up? Even beyond the ruckus of AI and agents, there are some interesting things happening that work leaders have needed for far too many years.

Feeling hopeful for a soft economic landing and continued investment in the industry? The show size (as big as ever), increased buying behaviors, and a Fed interest rate cut made those proverbial wallets feel a little looser.

Feeling like we’ll go back to reinvesting in employee experience like we did in 2022? Well, even a Rorschach test can do only so much projection.

So what am I seeing?

Show me, don’t tell me

AI was ubiquitous. There were a scant few booths that didn’t have a mention of AI and disappointingly, no strong counter to the AI-fication of everything. HR Tech can be a miserable place in the throes of a hype cycle. The eyes glaze over like looking at the menu at Border Grill for the seventh time.

What would’ve been nice to see is a strong, clear AI story. Instead, there was a lot of bark and little bite.

Vendors had issues answering questions like:

• How does your AI work in plain language?

• Who is using your AI solution?

• How is it improving outcomes?

• How is it improving the experience, especially for employees?

Of course, I wasn’t talking to the product leaders (I didn’t think I’d even be coming to the event until a few weeks ago). But very few people generally do. If your whole team can’t answer these questions credibly, it’s bad.

Ultimately, buyers aren’t looking for AI in and of itself. They are looking for answers to problems their organization is facing. A lot of them are distrustful of big promises because HR technology providers often struggle with basic automation and janky integrations already. Anyone who is in the CHRO seat has had a major technology failure in the last five years. Even if intrigue is high, they are probably going to focus first on getting the basics right.

Skills no longer pay the bills

In the paraphrased words of Supertramp, goodbye skills, it’s been nice. Hope you find your paradise.

What was once the hot trend for a few years was much less prominent this year. I’m not surprised, though. Skills are hard to quantify and capture in the same way that credentials or years of experience are. A credential is binary. You either have it or you don’t. Skills have a whole range of possibilities. And even people at the same skill level will vary.

Not only that, there’s a whole philosophy around taxonomy and organization that carries some very strong feelings. That makes the match, even for true believers, about as easy as finding the owner a glass slipper after that late night party in Eye Candy.

Pragmatically, we need some sort of answer for skills. Buyers seem to be struggling here but they also seem happy to ride it out with existing tools.

Does anyone care about the employee experience anymore?

I get that the pendulum has swung power back to employers but wow. No wonder employees are slow walking AI adoption. Even the hint that AI could do some work that humans are doing has led people to talk about EX as an afterthought. Or worse, that AI will make the employee experience better (which just isn’t showing up in any data).

This is real short-term thinking. There aren’t too many companies out there with sustainable success that also don’t at least try to create a great employee experience. And I believe EX is innate in an organization, through good times and bad (or whether the power dynamic is in their favor or not).

The thing is, being a good workplace also stands out more when you have the option to act like a jerk and still get people to work for you. Maybe vendors feel like EX is implied but buyers do not.

Cheers and jeers

What was good and what was bad?

Cheers: New team

It was great getting together with some of my new (Mary Ellen Slayter and Alec Cherrin) and not-so-new (Steve Smith and Anthony Spangler, APR) colleagues at Rep Cap and having some great meetings at HR Tech. Everyone was excited!

Jeers: Vegas

I got sick, my feet still kinda hurt, and the dry air never goes away. I get why HR Tech is in Vegas, probably for the long haul, but I don’t have to like it. I want to go back to a real city, maybe one with some humidity and things besides Vegas-priced and styled bars and restaurants.

Cheers: Old and new connections

It was great seeing so many people (too many to count, I’m sorry, I can’t tag you all). As a guy who’s always happy to stay in my cave of an office away from socialization, the sprint of talking with this many people all at once is a lot. My heart is happy and I was glad to see y’all but I’m also happy for some quiet again.

Jeers: Badge scanning

I don’t know what happened but a bunch of companies decided to get really aggressive with the badge scanning this year. I had multiple people scan my badge without even asking and it seemed like everyone was looking for those sweet leads. My month-old email inbox is suffering already.

News from the show

• SAP confirms completion of the SmartRecruiters acquisition - link

• Visier Inc. launches Manager Agent - link

• Darwinbox launches Super Agent - link

• Employ (Jobvite/Lever/JazzHR) showcases AI Screening Companion - link

• Perceptyx debuts AI Agent Suite and reimagined platform - link

• Cornerstone OnDemand presents next evolution of the Cornerstone Galaxy platform - link

• RADICL launches AI-native platform to reimagine how people and teams organize around work - link

• Beekeeper introduces Manager Hub and My Portal for frontline EX - link

• beqom introduces Pay Equity & Transparency solution - link

• PageUp launches AI Skills Matching and “Paige” virtual assistant - link

• Remote expands global HR & Payroll with Remote Surveys and enhanced HRIS - link

• Salary.com introduces CompAnalyst AI Suite - link

• Skillsoft unveils next‑gen Percipio learning platform - link

• Proctorio announces Secure Interviews (anti‑fraud for interviews) - link

• RChilli Inc. introduces AI agent capabilities for autonomous recruitment data ops - link

• Nayya unveils year‑round, AI‑driven benefits actions and guidance - link

• Chime Workplace integrates financial wellness with Workday - link

• Guardian Life expands Guardian Access APIs for real‑time benefits data exchange - link

• EMPTrust Employee Onboarding Modules debuts EVA Section 2 Employment Verification Agent for I‑9 - link

• TraineryHCM launches AI in ReviewCloud + new JobArchitect module - link

• iCIMS releases the 2025 State of Frontline Hiring report - link

• ADP announces Lyric HCM named a Top HR Product of 2025 - link

• Workday announces Workday Wellness named a Top HR Product of the Year - link

• Paradox, A Workday Company announces Immersive Job Preview named a Top HR Product of the Year - link

• Eightfold AI announces recognition as one of HR Executive’s 2025 Products of the Year - link

• RedThread Research announces Ingentis has joined its Tech Consortium and previews member showcases at HR Tech - link

• The Josh Bersin Company announces 30 AI HR Tech Trailblazer vendors to be unveiled in the HR Tech 2025 keynote - link

• HR Executive & HR Tech announce the 2025 Top HR Products of the Year - link

A note on this newsletter going forward

I am still working on getting up to speed in my new role, so things might be touch-and-go for a bit as I get into a new rhythm. Stay tuned for updates on the evolution, and maybe eventually some new brand and name. If you’re subscribed, you won’t miss it. If you’re not? Well, I pray to the LinkedIn algorithm that you’ll find me sooner than two weeks later.

That’s it for this week!