New Tech Layoff Data
Mostly just a response to layoffs.fyi and a TechCrunch article published in mid-august
On August 15, 2024, TechCrunch posted the following:
- January 2024: 19,350 employees laid off — see all January 2024 Tech Layoffs
- February 2024: 15,589 employees laid off — see all February 2024 Tech Layoffs
- March 2024: 7,403 employees laid off — see all March 2024 Tech Layoffs
- April 2024: 22,153 employees laid off — see all April 2024 Tech Layoffs
- May 2024: 9,882 employees laid off — see all May 2024 Tech Layoffs
- June 2024: 10,083 employees laid off — see all June 2024 Tech Layoffs
- July 2024: 8,851 employees laid off — see all July 2024 Tech Layoffs
The TechCrunch data above is independent of the chart on layoffs.fyi
The natural question that follows: “What constitutes a tech company?”
Well, Slate addresses that here in its interview with the founder of layoffs.fyi. layoffs.fyi relies on self-reported data, and it does not have a strict definition.
While Lee’s tracker is more transparent than BLS data — he names companies and links to his sources — it is as not methodologically rigorous, particularly when it comes to defining tech companies. “There’s no strict definition,” Lee told me. “If they sell software, that’s obviously a tech company. If they’ve raised venture capital funding, then usually I’ll count them as a tech company as well.” He included Capital One, a bank, because it laid off roles exclusively in its technology department. (In turn, I included Capital One on a ranking of recent tech layoffs.) But, Lee said, “I might change my mind.”
— Source
Natural Questions And Responses
Why are these layoffs occurring?
I don’t know.
Every time I see anyone post about tech layoffs, I always see variations of the same four comments:
- Tech layoffs are occurring because of AI
- Tech layoffs are NOT occurring because of AI, and anyone who thinks they are is ill-informed
- Tech layoffs occurred due to over-hiring
- Tech layoffs occurred due to the rise in interest rates
Are interest rates a major factor in tech layoffs?
Well…sure. That and the comment about over-hiring are the easiest to address. This blog post trended on HackerNews and said the following:
Basically, all the “free money” went away when the gubbment mandated interest rates go from years of declining-or-near-zero percent to now over 5% (curiously, a 5% increase in the fed rate also caused all credit cards rates to go from 9% to 30% over the same timeframe. what world).
Why would interest rates cause jobs to go away? Remember an interest rate is essentially “the price of money” — a higher interest rate means money is more expensive itself. Also with higher interest rates, organizations with millions and billions of cash sitting idle can park their money in safe government-backed interest accounts2 to grow their balances risk-free instead of taking on risk assets seeking outsized returns.
What counts as risk assets avoided during high interest rate periods? Well, funding companies with uncertain futures is a pretty risky asset. So, at times of high interest rates, the weaker companies collapse, strong companies use high interest rates as an excuse to “clean house” every 10 years, then a couple hundred thousand previously high compensation workers discover there are no jobs for anybody anymore over the next 2–4 years.
— Source
…but this probably doesn’t even have to be cited, I just liked the description of an interest rate as the price of money. Interest rates rose to combat inflation. When they rose, it became more risky to fund tech companies.
This is a chart depicting the decline in software development job openings on indeed.com. Unfortunately I am not allowed to include a screenshot of it (the copyright on it was rather explicit), so if you do not click the link, please use your imagination to picture an upside-down parabola that starts to go way up in mid-2020, peaks in early 2022, and then starts to rapidly decline in early 2023. From early 2023 to the present, imagine it continuing to decline, but flatten out.
Wow, I can imagine my 7th grade math teacher retroactively flunking me for the paragraph above.
Is AI the reason for tech layoffs?
I can’t find any solid proof that they are, so I find it strange that some news outlets claim that they are.
For example, this February 2024 CNBC article explicitly stated:
The number of tech sector layoffs in 2024 has been outpacing the number of terminations in 2023. So far, about 42,324 tech employees were let go in 2024, according to Layoffs.fyi, which tracks layoffs in the tech industry. That averages out to more than 780 layoffs each day in 2024. In 2023, nearly 263,000 tech employees got laid off, averaging to about 720 layoffs each day that year.
There are several factors behind the churn. AI is at the forefront. Companies need to free up cash to invest in the chips and servers that power the AI models behind these new technologies. There’s also the stock market effect. Companies that conducted layoffs haven’t been punished, either by investors or on their bottom lines. In fact, they’ve been rewarded with rising stock prices.
— Source
AI is at the forefront, because companies need to free up cash to invest in the chips and servers? What is their source? That exact same week, BusinessInsider posted this article claiming that AI was NOT driving layoffs:
Fabian Stephany, who lectures about AI at the Oxford Internet Institute, said: “Fighting against robots is a nice cover story,” he said. “But if you have a closer look, it’s often old school, simple economic dynamics like outsourcing or lead management cutting costs to increase salaries in other places.”
…
Despite noise about replacing employees with robots, though, there’s been little clear evidence this is taking place.
AI is still playing an “ambiguous” role in the labor market, Stephany said. “It’s not that on a mass scale jobs are being automated away. It just comes down to augmenting and automating certain things.”
— Source
Regardless of who is correct, how would you definitively prove that AI is or is not driving tech layoffs? You would need interviews with ex-employees from companies that actually proved you could use something like generative AI to replace some (perhaps junior) developers.
Without such evidence, why are blog posts like “The Death Of The Junior Developer” still trending? They mostly rely on incomplete, poorly-backed anecdotes.
Closing Thoughts
I posted this in February last year.
The comments were so good that I could probably write an updated response to them as my next blog post (I can call it “Responding To Readers — Making Sense of Tech Layoffs”), but one of them was highly critical. It told me to be more concise and “consolidate that shit.” Fine, I thought, and wrote this comment:
Thank you for your comment. That is a valid criticism. To anyone who decided to look at the comments section first:
*Interviewing.io collected 2022 data from layoffs.fyi. They determined that only 5% of tech workers laid off were engineers, with the caveat that layoffs.fyi data is provided voluntarily. If you look at the interviewing.io article, they also explore further by adjusting for department size
*365DataScience sampled 1157 LinkedIn profiles from November 2022 to January 2023 and found that 22.1% of those laid off were software engineers
Quite a disparity, so call that 5–22% of “tech workers” laid off at the time.
Other comments discussed opportunities at non-tech companies, followed by a lengthy comment about someone’s personal experience.
So what does this all mean?
I don’t know.
This is the part where I usually just link a dog video and call it a day.
