The Layoff Guide | Bloat + AI Efficiency = Perfect Storm
More layoffs are coming…and AI will be the excuse, whether it’s true or not.
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Layoffs Are Coming…
I hate to be a doomer, but tech layoffs are going to be brutal in 2026. Block’s massive 40% layoff announcement last week will trigger LOTS of conversations among execs and their boards. And there is a strong reason for layoffs at most tech companies: 1) inflated headcount relative to the recent massive deceleration in revenue growth and 2) huge efficiencies coming from AI.
To put Block’s 40% layoff number in perspective, below are the largest percentage layoffs by tech companies. Block stands out…
There are two camps of thought regarding Block’s layoffs:
This wasn’t really about AI efficiency. Block was extremely bloated and they over-hired during the ZIRP days. Remember that Jack Dorsey built an extremely bloated Twitter and Elon slashed headcount at Twitter by 80%+ when he took over. Don’t take Block’s layoff as a sign of large-scale layoffs because of efficiencies from AI.
Block just said the quiet part out loud…Lots of layoffs are coming due to AI. Jack was just early to do it and bold to fully right-size the company with a massive layoff.
#1 makes us white-collar workers feel better because maybe AI isn’t going to take our jobs this year. But just because #1 is partly true, doesn’t mean #2 isn’t also true…
Jack clearly described this layoff as being AI-related in his announcement. And that the business is not in trouble. He even responded to one user who claimed that Block was just bloated by saying that they did indeed over-hire during covid but their gross profit per employee and efficiency is better than most in their industry.
What’s true? What should we take away from the Block layoff?
Both of the following can be true: 1) Block was bloated AND 2) they had decent financial metrics. AI is just making that bloat even more extreme.
If Block was bloated and they had better financial metrics than many others….what does that say about other companies’ bloat?
“AI efficiency” is easy air cover for a layoff. “Our business is strong, but AI means we need fewer people” feels like a much better story than “growth has slowed, so we need fewer people”.
Tech companies love to copy other tech companies. Large layoffs by a few peers provide acceptance/pressure for many more to consider similar layoffs in 2026.
Investor/board pressure to do layoffs is going to increase. Block’s stock jumped 25% on the layoff news…
It doesn’t matter if Block’s layoffs are actually AI-related…It’s kicking off conversations across the tech ecosystem.
How To Do Layoffs
1. How much severance should we pay?
I have a few general beliefs here and then I will get to the specifics:
Good severance is just as much for those that stay as it is for those that leave. If you pay good severance then you should tell everyone about it. Why? Because you want the people that stay to know that you took good care of their former teammates and that they will be treated really well if there are future layoffs.
If you want to say that “business is good but AI efficiencies mean we need fewer people” then you have to pay great severance packages. There is a price to pay if you use “AI efficiency” as your layoff excuse (whether true or not).
Most private company employees don’t care that much about generous equity severance…they care about cash. It’s nice, but don’t overplay it. For public companies, it’s as good as cash so they do care.
Below are some interesting benchmarks of severance packages from recent layoffs:
Caveat to above data: Companies are only telling everyone what the severance packages are if they are good. If they are bad (below average), then most companies are silent on it so it won’t be on my list above. So the above data is going to lean generous. Smaller companies with less cash/runway will need to do less, but unless you will be going out of business soon then I’d generally recommend a minimum of 5 weeks of severance.
Some other severance package things to consider:
Paying for COBRA for some extended time period is fairly standard. Smaller private companies may do 1-2 months while larger companies may do 4-6 months.
Some equity stuff:
Accelerated vesting for public companies is great because it’s basically cash. Not so much for private companies…
For private companies, rather than acceleration of vesting (or in addition to), consider an extended post-termination exercise period.
Dropping the 1-year cliff for those impacted is pretty standard these days
Other common benefits: Laptops can be kept, career services, and immigration support
Some companies offer severance packages to folks not being laid off (usually must decide in <30 days). The idea is to not keep people who will just “quiet quit” while they look for something else.
2. How much do we cut?
If the layoff is related to financial trouble, then the CFO is backing into a total payroll dollars that need to be cut. If AI-related, then the question turns to “how much do we think we can cut?” and then the model is run to see how much more profitable you will become.
There are usually two options for layoffs:
Gradual over time - helps control cutting the wrong people or too much, but terrible for company morale, focus, and trust from customers and shareholders.
One big cut now - takes more time to plan to get right and higher risk, but better for those that stay so you can confidently tell them nothing else is planned.
I will choose the one big cut option 100% of the time if it’s possible.
Some questions to consider when sizing the layoff:
How will projected AI efficiencies impact headcount needs in 6-12 months?
How many people will voluntarily leave because of this layoff?
How will sales be impacted? Cut more people and sales forecasts will decline
What will break if we cut too many? You have to balance informing some leaders to get their feedback and the chance of it leaking.
Who are executive teams looking at to cut?
Poor performers are first on the list.
If execs are pushing more in-office work (many are), then remote folks will be in trouble
Expensive management layers. Everyone is talking about reducing layers. These folks are high on the list when there is financial trouble
Departments most impacted by AI. Such as support and engineering (definitely not CFOs…right? 😬)
A lot will depend on your circumstances, but I will refer to my favorite quote when doing any house projects: “Measure twice and cut once”. Or in this case, measure 10 times and cut once.
3. Layoff Communications
I am not a corporate messaging expert, but layoff communications must feel authentic and honest. If it sounds like AI or not authentic, then you will lose the trust of the employees that stay. The messaging is critical to helping the business move forward as best as possible.
Below are some recent well written layoff announcements that you can reference:
The AI Layoff Announcement: Block’s layoff provides the best example of this so far as he squarely blames AI. Some commented on his lack of capitalizing anything in the message, but one thing was clear from his message…it wasn’t written by AI. It felt very much directly from Jack. That matters.
Below are a few other good layoff templates:
Final Words
Layoffs suck. If you take away nothing else from this post…treat everyone like humans. Be authentic and honest. People will see through it if you don’t.
The tech job market is rough right now and it is going to get much worse before it potentially gets better.
Be generous, if you can, with your severance. It will also help those who stay to get back to full productivity faster.
Footnotes:
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