In this issue:

On LinkedIn the other day, I said it out loud: I’m cautiously optimistic about the job market. When the smoke thins and the sirens fade, AI leaves more seats than it takes. There’ll be bruises in between. Paychecks missed. Résumés in the wild. But the sun still clocks in—bet your bottom dollar. Not everyone bought it. One subscriber, in particular, pushed back like this:

No shade. I like contrarians. They make me dig, check receipts, and bring back something worth reading. This issue is proof. Welcome to Part 1 of a 5 part series on the job market. Love it or hate it, just don’t shrug. I hate indifference. Indifference kills the work. And so it begins.

…

The HR Blotter

Clock In, Bow Down: When Prayer Becomes a Job Requirement - A factory in North Carolina turned the assembly line into a pulpit. According to a federal lawsuit, bosses forced workers into prayer meetings, and those who refused were punished—demoted, written up, or tossed out the door. It’s a brutal case study of control at work, where management blurred the line between faith and employment until it became a weapon.

Resumes written by ChatGPT are favored by Applicant Tracking Systems that use ChatGPT (Go figure) - AI isn’t just scanning resumes anymore, it’s playing favorites. A new study shows that when both job seekers and employers use large language models, the machines lean heavily toward their own kind. Resumes polished by the same AI screening them are up to 60% more likely to be shortlisted, leaving human-written applications at a sharp disadvantage. In the battle for jobs, the bias isn’t just human anymore—the algorithm may be stacking the deck for itself.

Return-to-Office: The Layoff You Don’t Get Severance For - The job market’s bleeding, AI’s eating jobs like popcorn, and now the corporate giants want you back under their fluorescent glow. Microsoft, Paramount, Amazon, JPMorgan—lining up to preach “culture” while really trimming headcount without calling it layoffs. Small firms, meanwhile, are circling like sharks, scooping up talent with the promise of freedom. Translation: bend the knee at the office cubicle or get left out in the cold.

Scammers Hired Her, Fired Her, and Robbed Her Before Day One - A recent grad thought she’d landed her dream job through LinkedIn but what she got instead was a $2,400 scam. Posing as Bold Business recruiters, scammers ran her through a fake interview, sent her a bogus check, and convinced her to Zelle money for “work equipment.” When the check bounced, the cash came straight out of her pocket. Her tearful PSA has gone viral, warning job seekers that in today’s market the biggest trap isn’t rejection, it’s getting played before day one.

From PowerPoint to Power Sauna: Networking Gets Steamy - These glossy new bathhouses aren’t just about health, they’re moonlighting as networking hubs. Workers are swapping cocktails for cold plunges, trading résumés in the steam, and closing deals half-naked in a hotbox. It’s corporate bonding rebranded as “wellness,” where team offsites and client meetings now happen in swimsuits. The message? Work has officially invaded every corner of life, even the sauna.

…

The Jim Stroud Podcast

Not subscribed to The Jim Stroud Podcast? Then you’ve been flying blind. Here’s a taste of what they’ve been hearing—while you’ve been missing it.

…

…

The Great AI Employment Data Divide: When Research Meets Reality

The hottest fight in tech isn’t model versus model. It’s truth versus truth. Will AI create jobs or vaporize them? Depends who’s holding the mic, which dataset they’re waving, and what month you ask. In 2025, the labor market is a hall of mirrors: tidy charts, clashing conclusions, and a fog machine set to high. Everyone’s right. Everyone’s wrong. Sometimes in the same paragraph.

The Optimists: Big Numbers, Bigger Promises

Start with the sunshine. The World Economic Forum projects 170 million new jobs created and 92 million displaced for a net +78 million by 2030. That’s not a forecast; that’s a pep rally).

Even the U.S. Bureau of Labor Statistics—not exactly cheerleaders—expects software developers to grow 17.9% (2023–2033), roughly 4.5× the average occupation, smack in the domain where Copilot supposedly eats junior code for breakfast.

Then there’s PwC’s AI Jobs Barometer: workers with AI skills command a 56% wage premium. AI‑exposed industries see 3× revenue per worker growth, with wages rising 2× as fast as the laggards.

Most telling, Brookings found firms investing more in AI aren’t trimming headcount; they’re adding it. A one standard deviation lift in AI investment lined up with ~20% higher sales growth over a decade—and employment grew with it.

The Pessimists: When the Floor Drops Out

Pop the confetti later. Stanford’s Digital Economy Lab sliced ADP payrolls and saw a 13% employment drop for 22–25‑year‑olds in AI‑exposed roles since late 2022—exactly when GenAI went mainstream. Older workers in those same lanes? +6–9%. Translation: entry‑level rungs are snapping while higher rungs hold.

LinkedIn piles on: AI technical hiring quadrupled over eight years and grew 30% faster than overall hiring in 2024. Great if you’re specialized; brutal if you’re the role being replaced, not the role doing the replacing.

And the hype hangover? MIT reports 95% of GenAI pilots are face‑planting on revenue impact—big talk, thin P&L.

The Fed’s Curveball: “We’re Using AI… But Not Firing Much (Yet)”

The New York Fed steps in with a cooler take: AI usage is up sharply, layoffs tied to AI are still rare. Services firms using AI jumped to 40% from 25% (that’s a 60% relative increase). Manufacturers: 26% from 16%. Today’s story is retraining over job loss. Tomorrow’s? Those same firms expect more layoffs as integration deepens.

Why the Data Seems to Contradict Itself

Short version: the studies aren’t measuring the same thing.

• Future intent (boardroom promises). The WEF asks executives what they plan to do in the next few years. It’s a forecast of intentions, not a headcount ledger. That’s why it reads upbeat.

• Right‑now reality (who got paid). The Stanford work looks at payroll data. No vibes, no promises, just “did a human get a paycheck this month?” That’s why it can show junior roles shrinking even while leaders talk growth.

• Operator pulse (what firms did and expect next). The NY Fed surveys businesses on actual usage and near‑term plans. Today: more AI adoption, limited layoffs. Tomorrow: more changes likely as AI gets embedded. It’s the bridge between forecasts and payrolls.

• Adoption vs. ROI (the sober hangover). The Stanford AI Index says adoption is high—78% of orgs used AI in 2024, up from 55%—but 95% of pilots aren’t moving the bottom line yet. Lots of testing, little profit. Measuring a marathon at mile two.

Bottom line: Different lenses, different time horizons, different questions.

• WEF = where leaders want to go.

• Stanford payroll = what’s happening right now.

• NY Fed = what operators did and what they’ll try next.

• AI Index = adoption is real, returns are lagging.

Put all these perspectives together and all the contradictions on job market reporting makes sense. But I digress.

The Age Problem: No Rungs, No Ladder

The ugliest finding in all this is the age split. Juniors do the routine, codified work; exactly what AI automates first. Veterans bring context, client equity, and messy problem‑solving; exactly what AI augments. If entry‑level roles evaporate, how does anyone climb? That’s not a skills gap. That’s a pipeline collapse.

Geography: Zip Code Arbitrage

AI’s upside is uneven. The NY Fed survey reflects a region dense with finance and services, where AI adoption is already normal. The PwC wage premium shows up strongest in big metros with capital, buyers, and talent networks. Smaller markets feel the automation pressure without the same volume of AI hiring. Remote options help, but labor demand is still clustered around those hubs.

## Timing: Calm Before, Storm After

Today’s blend—rising adoption, limited layoffs, heavy retraining—smells like transition. WEF’s long arc captures eventual job creation. Stanford captures now. The Fed captures now with a side of what’s next. The mismatch isn’t contradiction. It’s a timeline problem.

The Skills Premium (and Its Half‑Life)

Yes, there’s money on the table: workers who can actually apply AI are earning ~56% more today. But the easy stuff commoditizes fast. To stay ahead, lean into work that ties AI to real business outcomes: workflow design, human‑in‑the‑loop ops, data quality and governance, risk/ethics, and change management. Those capabilities decay slower than prompt tricks—and they travel across tools.

## Corporate Double‑Speak

Press releases say “transformation.” Earnings calls whisper “efficiency.” In 2025, ~800,000 workers were laid off, but only ~20,000 were labeled “AI‑related.” Is AI the reason, or the fig leaf? Firms that invest to augment people grow revenue and headcount. Firms that drape AI over a cost‑cutting plan shrink and blame the robot.

The Measurement Trap

Our instruments aren’t built for hybrid work. When a support rep offloads routine tickets to a bot, are they displaced or upskilled? When a developer lets Copilot chew boilerplate, is that automation or leverage? Forecasts capture intent, payrolls capture outcomes, and operator surveys capture practice. Until metrics evolve to track task‑level shifts, expect noisy, partial truths. For now, the NY Fed business surveys are the closest operator pulse, while payroll data shows who actually got paid.

## What to Do While the Clock’s Ticking

Workers: stop spectating. Build AI‑complementary skills—workflow design, prompt‑to‑procedure, oversight, exception handling, stakeholder comms. The wage premium won’t last forever. Your relevance will.

Companies: pick a lane. Augmentation beats churn. Follow the Brookings arc—invest in tools and people—and you’ll keep both customers and headcount.

Policymakers: use the retraining window. Build reskilling rails now so when the Fed’s “later” arrives, you’re not drafting policy on a wildfire.

Bottom Line: Embrace the Mess

Use the timeline to read the conflict, not to pick a side. WEF points to long‑run job creation. Stanford shows a near‑term squeeze on juniors. The NY Fed logs adoption now and warns of more changes later. Strategy that wins: augment people, don’t just replace them; rebuild entry‑level ladders so newcomers can learn; fund AI projects with clear owners, KPIs, and P&L. Today’s scoreboard reads: juniors squeezed, specialists rewarded, lots of experiments, thin ROI so far and C‑suites rehearsing for layoffs they say aren’t about AI. The paradox isn’t a glitch; it’s a design choice. Choose models that spread gains, not just cut costs.

…

…

One more thing before I go…

In part 2 of the series, I share a dirty little secret that corporate America doesn't want you to know: AI isn't taking your job—but your CEO is happy to let you think it is. Wow! That’s a wild claim. Check back next week to see if I can back it up.

And as always, hit reply and let me know how I’m doing. Or slide into my DMs as the kids say. All good.

…