Don’t Cut Talent. Remix It.

The tech layoffs of 2023–2024 were supposed to be “strategic.” Instead, they often turned out to be guesswork.

When AI hit with full force, companies scrambled to downsize. Entry-level devs were the first to go. Then QA. Then, in some cases, entire functions, axed based on the promise of automation. 

But the bloodletting often went too far.

According to a recent CIO.com survey of 1,000 senior leaders, 55% admit they made mistakes in letting employees go during AI adoption. The reasons are telling: confusion over which jobs would benefit from AI, which were redundant, and which simply hadn’t evolved yet. In other words, the map didn’t match the terrain.

Now comes the walk-back. About 80% of those same organizations are reversing course, investing in reskilling programs to help existing employees work more effectively with AI. 41% are increasing their learning and development budgets.

Why? 

Because they realized what many engineering leaders already know: AI isn’t replacing people. It’s replacing tasks. And if you cut the people who understood the business, the codebase, the legacy systems...you’re not left with a lean machine. You’re left with brittle knowledge gaps and a hiring crisis.

IBM offers a revealing case study. The company made headlines when it announced thousands of HR jobs would be automated by AI. But what got less attention was the follow-up: they also began hiring software engineers and data analysts to fill the gap. Not a net loss. Just a talent remix.

This is where forward-looking engineering managers are now focused. Not on replacement. On redeployment.

Think about it: which is more valuable? A brand-new hire who’s fluent in LangChain… or an existing engineer who already knows your systems and just needs six weeks of training to become AI-competent?

We’re already seeing the shift on the ground. Teams are organizing AI workshops, hosting internal hackathons, and sending their senior engineers to prompt engineering bootcamps. Managers themselves are getting trained, not just to lead the tech, but to mentor their teams through it.

This isn’t a trend. It’s a reset.

Upskilling isn’t a luxury anymore. It’s table stakes.

Hiring great developers used to be the bottleneck. Now it's about finding people who can move fast, collaborate across tools, and co-build with AI.

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The companies that handle AI adoption best aren’t treating it like a cost-cutting spree. They’re treating it like a transformation. That means retaining domain expertise, retraining for the new tools, and redesigning workflows so that AI augments the human, rather than making a human-shaped hole and expecting magic.

Cut too deep, and you’ll spend the next year rehiring what you just lost. Train smart, and you’ll unlock 10x leverage from the team you already have.

The choice isn’t between laying off and doing nothing. The choice is between panic cuts and strategic evolution.

More to come…

✔️ Oops, We Did It Again: Companies Regret AI-Driven Layoffs (OpenTools)

✔️ AI & the Workforce: The Illusion of Reskilling & The Coming Crisis (Sumir Nagar)

✔️ Intel exec on bringing artificial intelligence into the workplace (AP News)