I’ve been putting off writing this post because the topic is genuinely painful. People I know and respect lost their jobs over the past two years. Friends. Former colleagues. Engineers, PMs, designers who did nothing wrong except work at companies that hired too many people too fast.

But the framing I keep seeing — that tech is “in crisis,” that the layoffs represent some fundamental collapse — doesn’t match the data. And bad framing leads to bad decisions, for companies and for the people navigating this market.

So let me try a different frame.

The hiring binge nobody talks about #

Between 2019 and 2022, the biggest tech companies went on a hiring spree that was, in retrospect, completely unsustainable.

Meta went from roughly 45,000 employees to over 87,000. Amazon’s workforce ballooned past 1.5 million. Google grew from about 119,000 to over 186,000. Microsoft added tens of thousands. These weren’t gradual growth curves; they were near-doublings in three years.

The reasoning at the time made sense. COVID drove a massive shift to digital. E-commerce surged. Cloud spending accelerated. Remote work tools exploded. Every engagement metric was up and to the right. The companies with the cash hired aggressively to capture what looked like permanent demand acceleration.

It wasn’t permanent. It was a pull-forward; years of digital adoption compressed into months. When the world reopened and growth normalized, these companies found themselves massively overstaffed for the actual demand curve.

The correction by the numbers #

Over 200,000 US tech workers were laid off in 2023 alone. That followed roughly 93,000 in 2022. The numbers are staggering, and they represent real human suffering — upended lives, lost health insurance, visa complications for immigrant workers.

But context matters. The US tech sector employed around 5.8 million people going into 2022. The layoffs, while devastating to the individuals affected, represented a single-digit percentage correction to a workforce that had grown by double-digit percentages during the pandemic years.

This isn’t a minimization. Every person laid off has a story that matters. But at the macro level, what happened was a workforce bubble deflating — not an industry collapsing.

Harvard Business School looked at this #

Sandra Sucher and colleagues at HBS studied the 2022-2023 tech layoffs and found something that should make every executive uncomfortable: overhiring was cited as an unusually prominent reason for layoffs across the sector. Not recession. Not product failure. Not competitive pressure. Just… hiring too many people.

Their research also highlights what companies consistently underestimate about layoffs: the hidden costs. Institutional knowledge walks out the door. Remaining employees disengage (survivor guilt is real and measurable). Voluntary attrition accelerates because top performers — the ones with options — start looking when they see colleagues cut. The organizational damage compounds long after the layoff announcement fades from the news cycle.

Sucher’s point, which I think is right, is that companies treat layoffs as a clean subtraction. Remove X headcount, save Y dollars. But the actual equation includes degraded team cohesion, slower execution, weakened employer brand, and higher future recruiting costs. Most companies don’t model those second-order effects.

The compounding factors #

Overhiring was the primary driver, but it wasn’t the only one. Several forces converged to make the correction sharper than it needed to be:

Interest rates. The Fed raised rates aggressively through 2022 and 2023. Cheap capital disappeared. The cost of carrying large teams with long payback periods suddenly mattered in a way it hadn’t when rates were near zero. Companies that had optimized for growth-at-all-costs pivoted to profitability almost overnight.

Venture funding declined. After peaking in 2021, venture capital deployment dropped significantly. Startups that had raised at inflated valuations found themselves needing to extend runway. Headcount reduction was the fastest lever available.

Enterprise spending tightened. As CFOs scrutinized budgets, enterprise software renewals got harder. Companies that had signed multi-year deals during the pandemic weren’t renewing at the same rates. This rippled through the SaaS ecosystem.

The combination — overstaffed companies, expensive capital, declining revenue growth — made some level of correction inevitable. The only real question was how fast and how deep.

What bothers me about the narrative #

Two things.

First, the “mass layoffs” framing treats all layoffs as equal. A company that hired 40,000 people in two years and then laid off 10,000 had a hiring problem, not a layoffs problem. That’s different from a startup that ran out of runway, which is different from a company that got disrupted. Lumping them all under the same narrative obscures the actual causes and therefore the actual lessons.

Second, the doom narrative benefits nobody. It doesn’t help job seekers (who need clear-eyed market assessment, not panic). It doesn’t help companies (who need to make rational staffing decisions, not react to headlines). And it definitely doesn’t help investors or policymakers trying to understand what’s actually happening in the tech economy.

The tech industry isn’t collapsing. It overbuilt during an unprecedented demand shock and is now right-sizing. That’s painful. It’s also normal, by the standards of any industry that’s gone through a bubble-and-correction cycle.

What I’d tell leaders #

Having managed teams through economic turbulence (at TaskRabbit during the pre-pandemic period, and now at DreamFlare during the post-pandemic correction), here’s what I believe:

Hire for sustained need, not projected peaks. The biggest mistake of 2020-2021 was hiring for demand curves that assumed permanent acceleration. Contractors and project-based work are the right tool for demand spikes; full-time headcount should match your baseline.

Model the real cost of layoffs. If you’re in a position where layoffs seem likely, actually calculate the cost of knowledge loss, voluntary attrition from survivors, and future recruiting spend. I’ve seen cases where the math doesn’t actually favor the layoff when you account for these factors.

Be honest with your teams. The companies that handled this worst were the ones that talked about “family” and “growth mode” right up until the layoff announcement. The ones that handled it best were transparent about financial realities months in advance, giving people time to prepare.

Don’t confuse efficiency with austerity. The pendulum swings. Two years ago, nobody questioned headcount. Now everyone’s cutting to the bone. Neither extreme produces good outcomes. The right answer is building teams sized for your actual trajectory, with enough slack to handle variability.

Looking forward #

We’re not done. January 2024 has already seen significant layoff announcements. But the pace is slowing, and the character of the layoffs is shifting — from “we overhired” to “we’re restructuring for AI” and “we’re consolidating after acquisitions.” The correction phase is winding down; the restructuring phase is ramping up.

For people in the job market: the worst is likely behind us. Hiring has picked up in Q4 2023 and early signals for 2024 are better. The market isn’t what it was in 2021 (it never will be again; that was an anomaly), but it’s stabilizing.

For leaders: learn the lesson. Sustainable growth beats hypergrowth followed by correction. Every single time.

I don’t enjoy writing about this. But pretending it’s either “everything is fine” or “tech is dying” does a disservice to the real people trying to navigate a genuinely difficult market. The truth — that this was a predictable correction after an unprecedented binge — is less dramatic but more useful.