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I've survived three tech recessions. Lost my job in one, held the axe in another. The AI boom changed the rules again. The updated playbook for 2026.
The view from my desk during the 2020 layoffs
March 2020. I'm on a Zoom call with 47 engineers. Half of them are about to lose their jobs. I know who. They don't.
That was my second recession as a staff engineer. The first one (2008) I got laid off. The third one (2023) I helped decide who stayed.
I originally wrote this in October 2023. The core is still true. But the AI boom between 2023 and now changed enough of the calculus that this needed a real update. What follows is the original playbook plus a new section on what's different now.
I'll get to the evergreen advice in a moment. But first: the 2023 version of this article missed something important, because it didn't exist yet.
The headcount math shifted. Engineers using AI tools effectively are doing more work per person than before. That's great until it isn't — it means companies can sustain the same output with fewer people. The question "is this engineer revenue-critical?" now has a second dimension: "is this engineer productively amplified by AI tools, or are they getting lapped by peers who are?"
AI skills are the new revenue proximity. The 2023 version of this article said to get close to revenue systems. That's still true. But there's a new category of protection: engineers who own the company's AI capabilities — the evals, the agent workflows, the prompt infrastructure — are increasingly hard to cut. That work is new enough that few people understand it deeply, and it touches everything.
Agency beats intelligence. This is the most underrated hiring and survival insight I've seen in the last two years. The engineers thriving in the AI era aren't necessarily the most technically brilliant ones. They're the ones who can direct AI systems toward useful outcomes — who set clear success criteria, catch when models are heading the wrong direction, and iterate deliberately. That's agency: the ability to pursue goals, act on feedback, and self-correct. It's more scarce and more valuable than raw technical knowledge, and it's observable in how someone works.
The side project signal changed. In 2023, "has a deployed side project" meant you were keeping your skills current. In 2026, the more specific signal is: have you shipped something using agents or AI workflows? The former shows you can build; the latter shows you understand the new paradigm. Both matter, but the second gets attention.
The time-vs-timing distinction. Some career investments compound over time regardless of when you start them: deep domain expertise, relationships, foundational skills. Others depend heavily on timing — catching a wave when it's peaking. AI skill-building right now is one of those rare things that is . The compounding value of becoming technically fluent with AI systems is high. And the window where this is differentiated rather than table stakes is closing.
In 2023 the first cuts were contractors, then the most recent hires, then anyone on experimental projects. Revenue-critical work goes last, and two mid-level engineers often survive over one senior.
Keep six months of expenses in cash, not stocks. If you need COBRA, budget about $2K a month for family healthcare. In 2008 Clint got two weeks of severance and took 14 months to match his old salary.
Show leadership exactly what breaks if someone leaves, such as a 3-month delay or a system only one person knows. Tie every argument to money. Clint saved three jobs this way.
Negotiate everything. Clint got 2 extra months by asking. File for unemployment the same day and update LinkedIn before the press release.
2008: I had the best performance reviews on my team. Still got cut. Why? I was expensive and working on a "non-essential" project.
2020: We kept the mediocre engineer who knew our billing system inside-out. Let go the brilliant engineer working on our future platform.
2023: The first cuts were contractors, then the most recent hires, then anyone on experimental projects.
The pattern is always the same:
I've seen staff engineers with 15 years at a company get cut while a junior who maintains the payment system survived three rounds.
Every quarter, map out where revenue comes from:
Product A: $40M (60% of revenue)
├── Payment processing (Team: 3 engineers)
├── User analytics (Team: 8 engineers) ← Overstaffed
└── Core features (Team: 5 engineers)
Product B: $10M (15% of revenue)
└── Entire team: 12 engineers ← Danger zone
If your team's revenue per engineer is below company average, start planning.
When I survived 2008, I started keeping what I call the "Go Bag":
The engineers who struggled most in layoffs? The ones who hadn't interviewed in 5 years and whose entire network was inside the company.
What gets hired in downturns:
What doesn't:
In 2020, I watched our "AI Innovation Lab" disappear overnight while the team keeping our 10-year-old Java monolith running got raises. In 2025, I watched the inverse: an AI team lose headcount while the engineer who owned their evals and monitoring infrastructure got a promotion. The pattern isn't about AI vs. legacy — it's always about mission-criticality.
This applies whether you're a staff engineer or aiming to become one.
The hardest career question to answer honestly: what work sits at the intersection of what you genuinely care about and what you're exceptional at? That narrow category is where you're hardest to replace. It grows deeper and narrower over the span of a career, but the people who find it early build compounding advantages.
The autonomy paradox is real: to reach staff or principal level, you become essential. To be effective at that level, you have to actively remove yourself from the critical path so the organization doesn't depend on you for execution. The leverage shifts from doing to enabling — connecting teams with problems to teams with solutions, mentoring engineers who can do 40 hours of work with 2 hours of your guidance, reshaping what the organization values through persistent documentation and advocacy.
During layoffs, this framing becomes survival advice. If you can answer "what would break, and how badly, if I left tomorrow?" with specificity, you can make the case for keeping you. If you can't answer it, neither can your manager.
First time managing through layoffs? Here's what HR won't tell you:
1. You'll know before your team Sometimes weeks before. You'll sit in 1:1s discussing career growth with someone you know is getting cut. It's soul-crushing.
2. The list changes 2023: My initial cut list had 5 names. Final list? Only 2 were the same. Politics, last-minute budget changes, and someone's golf buddy intervening. Plan for chaos.
3. Survivors guilt is real The team that remains? They're not relieved. They're angry, scared, and wondering why them and not their friend. Productivity crashes for months.
Document everything:
## Team Impact Assessment
- Project X: Losing Sarah means 3-month delay minimum
- System Y: Only Bob knows this, need knowledge transfer
- Customer Z: Their dedicated engineer is on the cut list
I saved three jobs by showing leadership exactly what would break.
Fight for your people (but pick your battles):
Prepare your survivors: Before layoffs hit, cross-train aggressively. In 2020, we did "bus factor reduction sprints" — saved us when cuts came.
If you survive:
If you're cut:
Survivors face:
This is when the second wave of departures hits — voluntary ones.
After three recessions and two years of watching the AI boom reshape what engineers are worth, here's what I know:
The next recession is coming. It always is.
The question isn't whether you'll face layoffs in your career — it's whether you'll be ready when you do.
I learned that the hard way in 2008. By 2023, I was the one holding the axe. The view isn't better from either side.
Prepare accordingly.