What I Built While They Were Waiting

November 2025, I was part of a reduction in force. Eleven years. Then the call.

HBR documented the pattern in January 2026: companies were cutting because of what AI was expected to do, not what it was actually doing. The bets were made on anticipated performance. Not current performance.

Now the receipts are in. 32% of companies that cut for AI are rehiring those same roles. 55% say the initial decisions were wrong. 29% are bringing people back at 20-35% higher pay than when they cut them.

Ford brought back 350 veteran engineers to fix quality problems their AI systems couldn’t catch. IBM’s HR AI handled 94% of requests; the 6% it couldn’t were ethical judgment calls that needed people. The reversals are becoming public.

Forbes asked the question directly on July 26: should you go back?

I’ve been thinking about it.

What I did with the window

The average job search in 2026 runs 139 days, 80-150 applications, 2-3% interview rate on generic submissions. That’s what the window looked like for most people who were cut.

I didn’t do that search. I built instead.

J Hammon Consulting went live. I work with growth-stage SaaS teams on GTM operations: surfacing what their data is already trying to tell them, building the plan of action around it. Coaching clients came next, people in career transitions applying the same systems thinking to their own navigation. And I built RoleNavigator: an AI-powered job search tool that scans job sites, scores listings against your actual resume, generates documents, and tracks your whole application pipeline. It’s live. People are using it. I’m still learning what breaks.

Eleven years inside one structure is a long time before you find out what you build when the structure falls away.

The market that opened while they were figuring it out

PwC ran the 2026 Global AI Jobs Barometer across a billion-plus job postings in 27 countries, and the finding is specific. Roles where AI amplifies expert judgment rather than replacing it are growing at twice the rate of other roles, with 42% faster salary increases. AI-skilled workers command a 62% wage premium on average. Jobs requiring AI skills are growing 8x faster than the overall market. The market didn’t just move. It bifurcated.

The U.S. numbers confirm it. Tech listings sit 36% below their February 2020 baseline. Machine learning engineer openings are up 59% over the same period. General software engineering is down 49%.

New tasks added to AI-exposed roles are 2.5x more likely to require empathy, judgment, and creativity than a year ago. The job you return to isn’t the job you left.

My actual answer

I’m not going back. That’s not a rebuke. It’s just where I am.

The ten months since the cut weren’t a holding pattern. What got built is real: a consulting practice, a coaching client base, a product with actual users. None of it existed in November 2025.

But my answer isn’t the right one for everyone. If you were cut in the same wave and spent the window in a job search, the reversal might be exactly what you needed. The people coming back at 20-35% higher pay are getting something real.

The honest question isn’t whether to go back. It’s what you built during the window, and whether going back fits where that puts you.

For some people, the 139-day search was itself the build: patience, targeting, learning how to run a search they’d never had to run before. That counts.

For others, the window opened something that wouldn’t have existed inside the structure. If that’s you, the call asking you to come back is worth taking seriously. And worth declining just as seriously.

The window closed. The decisions made in it are still compounding.