TL;DR
The first four months of 2026 saw approximately 119,721 tech workers laid off — averaging ~958 people per day. Major contributors include Meta (10,400+ across rounds, 8,000 of those on May 20), Microsoft (~8,750 buyout-eligible), Amazon (16,000 in Q1), Oracle (10,000+ already, up to 30,000 reportedly), Nike (1,400 mostly tech), and dozens more. The drivers: AI-driven efficiency gains, capex pivot toward AI infrastructure, and softer revenue forecasts. For job seekers, this market demands organized documentation. Use ScrapeMaster to build a structured tracker of open roles. Use Convert: Web to PDF to save job postings before they expire. Use Convert: Anything to PDF for severance docs and offer letters.
The Q1 2026 Layoff Numbers
According to public layoff trackers and company announcements:
- ~119,721 tech workers laid off in the first 4 months of 2026
- 265 distinct layoff events at tech companies
- ~958 people per day average pace
By company (selected major events):
| Company | Q1 2026 Cuts | Pattern |
|---|---|---|
| Amazon | ~16,000 | Manager-driven corporate cuts |
| Oracle | ~10,000+ (up to 30,000 reported for the year) | Voluntary + involuntary |
| Microsoft | ~8,750 buyout-eligible | Voluntary departure programs |
| Meta | 10,400+ across rounds (8,000 on May 20) | Performance-based framing |
| Nike | ~1,400 mostly tech | Tech department reorganization |
| Various smaller cuts | Tens of thousands combined | Across hundreds of companies |
These are concentrated; smaller companies make up the long tail.
What's Driving the 2026 Wave
Multiple drivers are converging:
AI-driven efficiency gains. 55% of US hiring managers surveyed expect layoffs in 2026, with 44% citing AI as a top driver. Companies are using AI to automate roles in customer support, content moderation, recruiting, and increasingly, software engineering.
Capex pivot to AI infrastructure. Big tech is investing hundreds of billions in AI infrastructure ($725B+ aggregate AI splurge across major players). That investment is partly funded by labor cost reductions.
Softening revenue forecasts. Several major tech companies face revenue growth deceleration as advertising, cloud, and consumer markets mature.
"Performance-based" layoff framing. Several companies have moved to performance-based cuts rather than mass restructuring announcements — affecting smaller percentages but sustained over time.
Hiring freezes amplifying the effect. When laid-off workers can't find replacement roles quickly, the effective unemployment in the tech labor market grows beyond the layoff count.
What This Means for Job Seekers
The 2026 market is challenging but not uniformly so. Some segments are flooded; others are still hiring aggressively.
Crowded Segments
- Generalist software engineering at large companies
- Recruiting and HR
- Sales operations
- Marketing and comms (especially content)
- Customer support
- Mid-tier product management
- Project management (where AI tooling competes)
Still-Hiring Segments
- AI / ML research roles
- AI infrastructure engineering
- Specialized cybersecurity (threat intel, AI security)
- Compliance and privacy (state law and EU AI Act create demand)
- Sales for AI products
- Specific ERP and database expertise (Oracle migrations, Workday, etc.)
Targeting your search at the still-hiring segments helps the math.
A Layoff-Aware Job Search Playbook
Week 1: Document and Decompress
- Save severance documents, offer letters, equity records as PDF
- Save important Slack/email threads (only your personal records)
- Save references' contact info before access ends
- Update LinkedIn while still employed (carries different weight)
- Connect with everyone you've worked with
Week 2: Target List
- Build list of 30-50 target companies
- Prioritize: still-hiring segments, warm intro available, geography fit, role match
- For each: career page URL, list of currently-open relevant roles, estimated salary range, person to ask for warm intro
ScrapeMaster helps build this systematically. As you browse Anthropic's, OpenAI's, Apple's, etc. career pages, it captures structured data for your tracker.
Week 3: Active Outreach
- Message warm intros first
- Apply to specific roles (not generic blasts)
- Save each application as PDF
- Track in a spreadsheet/CRM
- Note response rates and adjust approach
Week 4+: Iterate
- Refine messaging based on what gets responses
- Expand targets if needed
- Negotiate warm-up calls into actual interviews
- Watch for layoff list communities (specific to your former employer) — many have job-share threads and warm intro coordination
Building a Personal Layoff Tracker
Beyond your own search, tracking the broader market helps you understand timing and target companies. Useful inputs:
Layoff Intelligence Sites
- Layoffs.fyi
- TrueUp
- BreachSense (security context)
- Industry-specific (TechCrunch, Information, etc.)
Hiring Intelligence
- Company career pages
- AngelList / Wellfound for startups
- LinkedIn Job postings
- Levels.fyi for compensation benchmarks
- Glassdoor / Pave for salary data
Industry News
- Major outlet AI/tech sections
- CNBC, WSJ, NYT for big-picture trends
- Industry-specific newsletters
ScrapeMaster lets you systematically capture data from these sites as you browse. The output is a structured CSV/JSON of dates, companies, layoff sizes, hiring announcements — useful for spotting patterns and timing.
Documentation You Need to Save
From Your Former Employer
- Offer letter and amendments
- Most recent compensation summary
- Equity vesting schedule
- Severance offer document(s)
- Final pay stub
- Year-to-date financial documents (W-2 prep)
- Healthcare COBRA paperwork
- 401(k) statement at departure
From Your Job Search
- Each job description you apply to (capture before postings change/expire)
- Recruiter messages and emails
- Interview confirmations and feedback
- Take-home assignment instructions and your submission
- Each offer received
- Counter-offer history
For Your References
- Contact info for managers and peer references
- Agreed reference talking points
- Backup references if primary becomes unreachable
For Your Records
- Performance reviews
- Project documentation showing impact (your contributions)
- Recognition and awards
- Internal certifications
- Training completed
Convert: Anything to PDF handles the mixed-format work. Convert: Web to PDF handles online portal pages.
Severance Comparison: 2026 Norms
For context on what's typical in current market:
| Element | Common 2026 Norms | Range |
|---|---|---|
| Base severance | 8-16 weeks | 4-26 weeks |
| Tenure additive | 1-2 weeks per year | 0-4 weeks per year |
| Healthcare | COBRA + sometimes subsidy | None to fully subsidized 6 months |
| Equity acceleration | Rare | Sometimes for senior or special cases |
| PTO payout | Usually full | Per state law |
| Outplacement | Sometimes | Varies |
| Non-compete | Often included | Enforceability varies by state |
Better packages tend to come from:
- Higher-tenured employees
- Senior individual contributors
- Voluntary departure programs (vs. forced)
- Senior management
- Specialized technical roles
Worse packages tend to come from:
- Performance-based framings
- Recent hires
- Junior roles
- Late-stage cuts (after company financial pressure)
Your specific package may vary. Save your specific offer.
Tax Considerations Across the Year
If you're laid off in the first half of the year, you have specific tax planning opportunities:
Severance lump sum. Severance is taxed as wages, often at higher withholding rates due to lump sum treatment.
Reduced annual income. A mid-year layoff likely means lower annual wages — potentially shifting you into lower tax brackets.
ACA subsidies. Reduced annual income may qualify you for ACA marketplace subsidies once COBRA ends or becomes unaffordable.
Retirement contribution decisions. Decide carefully about 401(k) contributions for the partial year and whether to convert to Roth in a low-income year.
Equity timing. If you have stock with deferred vesting, the year-of-vesting tax can shift if you change companies.
A CPA familiar with tech equity is worth consulting once you have severance terms.
Mental Health and Pacing
Layoffs are stressful. Some practical observations:
- Take 1-2 weeks before serious job searching if your finances allow
- The first 30 days of search productivity matter; pace accordingly
- Job search benefits from social structure — accountability partners help
- Layoff alumni groups (often active on LinkedIn or Slack) are useful for warm intros
- Severance buys time; use it intentionally
- Many ex-tech workers consider non-traditional paths (consulting, founding, sabbatical) before returning to FTE
The job market will eventually clear, but the cycle's path is uncertain. Don't anchor on "by October" or "by January" — focus on what you control week to week.
Comparison: 2026 vs. Prior Layoff Cycles
| Metric | 2022-2023 Wave | 2024 Wave | 2026 Wave |
|---|---|---|---|
| Pace | Heavy 2023 Q1 | Reduced | High and sustained |
| Drivers | Post-COVID rightsizing | Rate environment | AI efficiency + capex |
| Severance generosity | Higher | Mixed | Generally less |
| Time-to-rehire | Faster | Mixed | Slower in many segments |
| AI roles | Hiring | Hiring | Still hiring strongly |
| Geographic concentration | US-heavy | Mixed | Global |
The 2026 wave's distinguishing feature is AI as a stated driver. That changes the expected return-to-hiring path — companies aren't reducing now to re-hire later; they're betting AI tools enable smaller teams permanently.
Frequently asked questions
How many tech workers were laid off in Q1 2026?
Approximately 119,721 in the first four months of 2026 — averaging about 958 people per day across 265 distinct layoff events.
Which companies had the largest Q1 2026 layoffs?
Amazon (~16,000 in Q1), Oracle (~10,000+ already, up to 30,000 reportedly for the year), Microsoft (~8,750 buyout-eligible), Meta (10,400+ across rounds with 8,000 on May 20), Nike (~1,400 mostly tech), plus many smaller cuts across hundreds of companies.
What's driving the 2026 layoff wave?
Three main drivers: AI-driven efficiency gains (44% of hiring managers cite AI as a top layoff driver), capex pivot toward AI infrastructure (over $725B aggregate planned), and softening revenue forecasts at major tech companies.
Is the job market actually bad, or just for some roles?
It varies by segment. Generalist software engineering, recruiting, content marketing, customer support, and mid-tier PM roles are crowded. AI/ML research, AI infrastructure, specialized security, compliance/privacy, and ERP migrations are still hiring. Target your search at hiring segments.
How do I track open roles across many companies?
Use ScrapeMaster — it captures structured data from career pages as you browse, building a CSV of role/company/level/location/salary/posted-date. Much faster than manually copying details into a spreadsheet.
What severance is typical in 2026?
Common: 8-16 weeks base + tenure-based additive, COBRA support, sometimes outplacement. Better packages: senior IC roles, voluntary departures, longer-tenure employees. Worse packages: performance-framed layoffs, recent hires, late-cycle cuts.
Should I save job descriptions before applying?
Yes. Job postings change and disappear. Save each posting as PDF using Convert: Web to PDF — preserves the visual layout, salary range (where shown), and posting date.
How long does the typical layoff-to-rehire cycle take in 2026?
Varies widely. Senior specialized roles in still-hiring segments: 2-4 months commonly. Generalist roles in crowded segments: 4-8+ months reported. AI/ML research roles: weeks if competitive. Plan for 3-6 months as a default and adjust.
What if I'm visa-dependent and laid off?
H-1B, L-1, and similar visa holders typically have 60 days from last day of employment to find new employment or change status. Consult an immigration attorney immediately. Some employers extend termination dates — sometimes negotiable.
Is it worth consulting a CPA on severance?
For severance over ~$50K or for anyone with significant equity components, yes. The interaction of severance, equity vesting, healthcare costs, and reduced annual income creates planning opportunities a CPA familiar with tech compensation can address.
Bottom Line
The Q1 2026 layoff wave — 119,721 tech workers in four months — is among the largest sustained periods in tech employment history. The drivers (AI efficiency, capex pivot, revenue softening) suggest the pattern continues through 2026.
For affected workers, organized documentation and tracking change outcomes. Save your severance docs and references with Convert: Anything to PDF. Save job postings before they expire with Convert: Web to PDF. Build a structured tracker of open roles and target companies with ScrapeMaster.
For absorbing the volume of tech employment analysis being published — the AI-driven labor crisis pieces, the company-specific reorganization stories, the macro analyses — CineMan AI summarizes long pieces in your browser so your time goes to action rather than reading volume.