UNDER THE RADAR Friday, February 13, 2026
BOTTOM LINE UP FRONT
Thursday’s employment data confirms what workers already feel: Continuing claims hit 1,862K – people staying unemployed longer as reemployment gets harder. WARN Act notices show 852 job losses per day (up 51% from 2025), with companies explicitly citing “AI and automation” for cuts. Meanwhile, corporate lobbying setup is underway – OpenAI sending memos to Congress about “threats” while workers have no seat at the table.
This week’s Top 5 opportunities: Updated with honest timelines (3-10 years, not “safe forever”) and clear pivot paths. The reality: AI generations every 6-12 months, robotics generations shrinking to 12-24 months, career retraining takes 12-36 months. You literally cannot retrain faster than technology evolves. These five positions offer real demand NOW plus better adaptation options than alternatives.
The compression is real. The “stable 30-year career” is dead. Use these positions to build savings, develop adjacent skills, and plan your next move.
THE JOBS REALITY CHECK
Thursday’s Numbers (February 12, 2026):
- Continuing claims: 1,862K (up from 1,841K, expected 1,850K)
- Initial jobless claims: 227K (expected 222K) – worse than consensus
- 4-week average: 219.5K (up from 212.5K) – trending worse
Translation: More people losing jobs. Fewer jobs to land in. Staying unemployed longer.
This isn’t a temporary blip. Continuing claims track people who remain unemployed week after week. When this number rises, it means the labor market isn’t absorbing displaced workers. Harder reemployment validates what we’ve been documenting: automation displacement is accelerating while replacement opportunities shrink.
WARN ACT SIGNALS: LAYOFFS INCOMING
The 60-Day Warning System:
The Worker Adjustment and Retraining Notification (WARN) Act requires companies with 100+ employees to file notices 60 days before mass layoffs (50+ workers) or plant closures. These aren’t rumors – they’re legally required advance notice.
What We’re Seeing (As of February 13, 2026):
Year-to-Date 2026:
- 60 layoff events
- 37,478 workers impacted
- Averaging 852 job losses PER DAY
- Largest single layoff: Amazon – 16,000 employees
Compare to 2025:
- 338 layoff events
- 205,773 workers impacted
- 564 job losses per day
That’s a 51% increase in daily job losses.
Major February Announcements:
- Amazon: 16,000 latest round (following 14,000 in October 2025)
- Dow: 4,500 jobs – explicitly citing “AI and automation” (7% of workforce)
- Heineken: 6,000 jobs globally (7% of ~87,000 employees)
- Washington Post: 1/3 of newsroom staff
- Bay Area concentration: Amazon 769, Meta 102, Western Digital 47, Genentech 141
Who’s Getting Cut:
Per SkillSyncer’s analysis of WARN data: “Companies across every sector are experimenting with where AI fits into their workflows, often replacing roles in content creation, customer support, data entry, and basic coding tasks.“
Notice what’s NOT on that list: Healthcare patient care. Electricians. Physical infrastructure work. Edge computing engineering. The positions our Top 5 targets.
Actionable Intelligence:
If you work in content creation, customer support, data entry, or entry-level coding:
- Check your state’s WARN notices: WARNTracker.com tracks all public filings
- If your company filed: You have 60 days to act
- If they haven’t filed yet: Start positioning NOW
New CalWARN Requirements (Effective January 1, 2026):
California now requires employers to provide more detailed information in WARN notices and coordinate with local workforce boards and elected officials. Better transparency on what’s being cut and why.
What WARN Data + Jobs Data Together Tell You:
Continuing claims rising (1,862K) + WARN notices accelerating (852/day) = People aren’t just losing jobs, they’re staying unemployed longer because there are fewer positions to land in. The displacement-to-replacement ratio is getting worse.
THE CORPORATE LOBBYING SETUP
Yesterday’s Timeline (February 12, 2026):
1:02 PM: OpenAI/Cerebras announce first AI model using Cerebras chips instead of Nvidia (hardware diversification signal)
4:42-5:37 PM: Corporate lobbying narrative building begins:
- OpenAI memo to Congress: “DeepSeek is distilling US models to gain an edge, free riding on US”
- Nvidia infrastructure: Data center lease financed by $3.8B junk bonds
- Nvidia/Brazil partnership: “Sovereign AI” expansion
- OpenAI follow-up memo: “Review indicates DeepSeek continued activities consistent with distillation targeting OpenAI and other US frontier labs”
What You’re Watching:
This is Stage 2: Direct lawmaker contact – the pre-formal lobbying setup. The pattern:
- Crisis narrative (“They’re stealing our AI”)
- Memos to lawmakers (what happened yesterday)
- Media amplification (coming next)
- Registered lobbyists (formal lobbying campaign)
- Legislation (final stage)
Historical Pattern:
Same playbook as 2000s outsourcing debates. Companies built narrative about “job theft,” lobbied for protective legislation, and workers paid the cost through reduced bargaining power and stagnant wages.
For Workers:
When corporations lobby about “threats,” always ask: Who pays the cost of their proposed solutions?
Usually workers – through reduced protections, accelerated automation to “compete,” or policies that prioritize corporate interests over employment stability.
Current Reality:
Workers have no seat at the table in these discussions. Six companies (Anthropic, Amazon, Google, Meta, Microsoft, OpenAI) coordinate AI governance standards. Federal deployment accelerates (AWS $50B contract). And worker compensation growth slows (0.8% vs 0.9% prior) while AI infrastructure investment hits $1+ trillion.
TOP 5 CAREER OPPORTUNITIES – FEBRUARY 13, 2026
CRITICAL CONTEXT:
No career is automation-proof forever. AI generations: 6-12 months. Robotics generations: 12-24 months (shrinking). Career retraining: 12-36 months.
You literally cannot retrain faster than technology evolves.
What matters: How well can you pivot when change comes? These five offer the best combination of current demand + future adaptability + honest timelines.
Scoring Criteria:
- Market Demand (30%)
- Entry Speed (25%)
- Income Potential (25%)
- Future Viability (15%)
- Scam/Risk Factor (5%)
Threshold: 70/100 minimum to make Top 5
#1. Healthcare Direct Patient Care (RN, Medical Assistant, Physical Therapy)
Score: 87/100 | Viability: 7-10 years ✅
Current Reality:
- 189,100 openings/year (BLS projection)
- RN #1 in hiring volume (Monster 2025 Report)
- 95,948 travel nursing jobs active as of Feb 6
- $93,600 median for RN, travel positions up to $130/hour
- Advanced Practice: 45% growth projected through 2034
- Home health, LPN, CNA all in top-10 demand
Why Protected (For Now):
- Physical presence legally required (HIPAA, licensing, liability)
- Human touch + clinical judgment irreplaceable
- Aging demographics = structural demand growth (not cyclical)
- Protected by regulation + malpractice liability
- AI assists but can’t replace hands-on care
When Change Comes:
Administrative parts automate first (scheduling, billing, documentation already happening). Direct patient care shifts to higher acuity work – sicker patients, more complex cases, shorter interactions.
Pivot Paths:
- Clinical + Tech Hybrid: Telehealth coordination, remote patient monitoring specialist ($75K-$95K)
- Healthcare Informatics: Bridge clinical knowledge + data systems ($85K-$110K)
- Medical Device Training: Train others on new AI-augmented tools ($70K-$90K)
- Patient Advocacy/Navigation: Help patients navigate increasingly complex AI-driven systems ($60K-$85K)
- Specialized Care: Geriatrics, palliative care (human touch irreplaceable) ($80K-$120K)
Why This Pivots Well:
Healthcare credentials transfer across settings. Clinical judgment remains valuable even as tools change. Aging demographics = structural demand that isn’t going away. You’re not betting on one technology stack – you’re betting on humans continuing to get sick and need care.
Honest Warning:
Administrative healthcare roles (medical secretaries, billing specialists, basic coordinators) are automating now. Healthcare Data/Care Coordinators dropped from our Top 5 this week (Zippia projects 4% decline). The protection is in direct patient care – hands-on work that requires physical presence and clinical judgment.
Entry Paths:
- Medical Assistant: Certification in months, $38K-$48K entry
- LPN: 12-18 months, immediate employment, $48K-$58K
- RN (ADN): 2 years, $65K-$95K starting
- Physical Therapy Assistant: 2 years, $75K+ starting
#2. Skilled Trades with Clean Energy (Electricians, HVAC, Solar)
Score: 85/100 | Viability: 7-10 years ⚠️
Current Reality:
- 80,000+ new positions nationally through 2026
- Near-zero unemployment for electricians
- $18.50-$26/hour apprentice (paid while learning)
- $61,590 median journey-level (BLS), top 10% over $104K
- Apprenticeships: 4 years, earn while learning, no student debt
- Data centers + EV charging + clean energy mandates = sustained demand
Why Protected (For Now):
- Physical work in unstructured environments (every job site different)
- Problem-solving required (can’t be templated or automated easily)
- Safety-critical work (liability requires human oversight)
- Union protections in many markets
- Clean energy expansion legislated (policy support creates structural demand)
When Change Comes:
Diagnostic AI gets smarter. Robotics advancing faster than expected – bricklaying robots (3,000 bricks/day vs 500 for humans), 3D-printed structures, automated framing already deployed. Humanoid robots (Figure, Tesla Bot, Boston Dynamics) reaching human-level dexterity.
The timeline compression: What took 5 years between robotics generations now takes 18 months.
Pivot Paths:
- Renewable Energy Specialist: Wind turbine tech, solar installation – BEST BET ($55K-$85K, structural policy-driven demand)
- EV Charging Infrastructure: Growing market, electrical skills transfer directly ($60K-$90K)
- Building Automation Specialist: Smart building systems, IoT integration ($70K-$95K, but watch for automation)
- Industrial Maintenance: Complex equipment repair in manufacturing ($65K-$95K, problem-solving focus)
- Emergency/Service Calls: Unpredictable problems, customer-facing ($55K-$85K, harder to template)
- Energy Management Systems: Optimize building/facility energy use ($75K-$105K)
Why This Pivots Well:
Core skills (electrical, mechanical systems, HVAC) apply across multiple industries. Physical work + problem-solving in variable environments = harder to automate than office work. Multiple exit strategies (renewable energy, industrial, building automation, EV infrastructure).
Honest Warning:
- Construction robotics accelerating – routine work (framing, bricklaying) being automated
- Humanoid robots closing dexterity gap – what seemed impossible 5 years ago is happening now
- Your timeline: 7-10 years, NOT 10+ as previously estimated
- After that: Only most complex/unpredictable work remains human
- Data center jobs = myth – billions in investment ≠ meaningful employment (Meta: $50B = 500 jobs by 2034)
Strategy:
- Learn the trade NOW (4-year apprenticeship = 2030 completion, right before compression hits hard)
- Focus on service/repair over new construction (more variable, harder to automate)
- Specialize in renewable energy (policy mandates = structural demand)
- Avoid routine repetitive work (that’s what robots do best)
Entry Paths:
- Electrician apprenticeships: IBEW, IEC, ABC (apply in Feb, May, Oct enrollment periods)
- HVAC programs: Community colleges, 6-18 months
- Solar certifications: NABCEP, add to electrical skills
#3. Edge Computing / Local AI Infrastructure (LASP)
Score: 81/100 | Viability: 5-7 years ⚠️
Current Reality:
- 8,000+ active jobs (LinkedIn US)
- +39% YoY growth (UK Lightcast Q1 2025, US similar)
- $95K-$170K mid-level, $180K-$220K senior
- Entry positions starting: ByteDance, NVIDIA, Google hiring for 2026 starts
- Distributed AI alternative to hyperscale monopoly (AWS/Azure/Google)
The Concept:
LASP = Local Area Service Provider for AI – distributed micro-facilities (10-50MW) providing AI compute closer to end users, analogous to how ISPs distributed internet access vs. mainframe computing.
Yesterday’s Signal: Rivian announced in-house AI chip (4x Nvidia performance). Following Tesla and Apple’s vertical integration strategy – bringing AI compute to the edge (vehicles, devices) rather than relying on centralized cloud.
Why This Opportunity Exists:
Technical Drivers:
- Low-latency requirements: Autonomous vehicles, healthcare, manufacturing can’t wait for cloud
- 5G deployment enabling edge infrastructure
- AI at the edge: Processing data locally vs. sending to distant data centers
- Data sovereignty: Regulations requiring local processing (EU, China, others)
Counter to Hyperscale:
- Automotive (Rivian, Tesla, Apple) building in-house edge AI
- Industrial IoT needs local processing
- Smart cities require distributed compute
- Healthcare edge devices (remote monitoring, diagnostic tools)
The Acceleration Problem:
AI model generations: Every 6-12 months. Edge computing architecture could fundamentally change 5-10 times before 2030. What you learn in 2026 may be obsolete by 2028.
When Change Comes:
Either:
- Hyperscale wins → Edge consolidates into AWS/Azure/Google services
- Edge wins → Hyperscale shrinks (your bet pays off)
- Hybrid persists but platforms consolidate (most likely) → AWS IoT Edge, Azure IoT Edge absorb independents
Pivot Paths:
- Automotive AI Systems: Vehicle-based compute (Rivian/Tesla model) – BEST BET ($110K-$180K, structural need)
- 5G Infrastructure Specialist: Telecom engineering ($95K-$150K, structural deployment)
- IoT Solutions Architect: Industrial IoT, smart cities ($105K-$165K, if distributed model wins)
- Cloud Infrastructure Engineer: If centralization wins, skills transfer ($100K-$160K)
- Platform Engineering: Kubernetes, distributed systems ($115K-$175K, transfers across architectures)
- DevOps/SRE: Operating distributed systems ($110K-$170K, architecture-agnostic)
Why This Pivots Well:
Distributed systems knowledge valuable regardless of who wins. Automotive/IoT need engineers EITHER WAY (edge vs. cloud question doesn’t eliminate need). Multiple competing models = opportunity in transition. Skills transfer better than platform-specific knowledge.
Honest Warning:
- Technology stack changes faster than you can retrain
- Platform consolidation likely (AWS/Azure/Google absorbing independent edge providers)
- Your timeline: 5-7 years MAX before major consolidation
- Entry-level positions may saturate quickly as bootcamps flood market
- Still hybrid with hyperscale (edge handles inference, hyperscale handles training)
Strategy:
- Specialize in automotive edge AI (Rivian signal = real trend, structural demand)
- Focus on distributed systems fundamentals (transfers better than specific platforms)
- Stay platform-agnostic (don’t lock into one vendor’s tools)
- Plan your exit by 2030 (before consolidation complete)
Entry Paths:
- Distributed systems fundamentals: Cloud platforms (AWS IoT, Azure IoT Edge)
- Container technologies: Docker, Kubernetes certifications
- IoT protocols: MQTT, CoAP practical experience
- Programming: Python, Go, Rust for system-level work
Skills Required:
- Distributed systems architecture
- Container orchestration (Kubernetes)
- IoT device management
- Network engineering (5G, edge networking)
- Real-time data processing
#4. AI/Cybersecurity Specialists (Cloud Security, IAM, AI Governance)
Score: 76/100 | Viability: 5-7 years ⚠️⚠️
Current Reality:
- 0% unemployment for cybersecurity roles
- 514,000+ job openings (CyberSeek)
- 29-33% growth projected through 2034 (BLS)
- $75K-$124K median (Information Security Analysts)
- 53% of employers increasing starting pay for cyber talent
- SOC Analyst, IAM Analyst, Cloud Security hiring actively
Why Demand Exists:
AI creates NEW attack vectors:
- Model poisoning/theft
- Prompt injection attacks
- Data poisoning in training
- Adversarial attacks on AI systems
- Every new AI deployment = new security surface
The Acceleration Problem:
ServiceNow + OpenAI partnership (announced Dec 2025) already targeting IT support. Cybersecurity is adjacent. SOC analyst work partially automated NOW, not “someday.”
When Change Comes (Already Starting):
- Alert triage automated: AI handles false positives, basic threat detection
- Routine compliance checks automated: Scanning, reporting, basic audits
- Pattern recognition: AI identifies known attack signatures
- What remains: Governance, architecture, incident response leadership, strategic planning
Entry-level SOC analyst jobs shrinking NOW. The protection is moving up the stack to governance/architecture/strategic roles.
Pivot Paths:
- AI Security Specialist: Secure AI systems, prevent model theft/poisoning – BEST BET ($95K-$145K, growing field)
- Compliance/Governance: Regulatory oversight (EU AI Act, sector-specific rules) ($85K-$130K, regulatory moat)
- Security Architecture: Design secure systems (higher-level strategic work) ($110K-$165K)
- Policy Consulting: Navigate regulation for enterprises ($95K-$150K, judgment-heavy)
- Incident Response Leadership: Crisis management, coordination ($100K-$155K, can’t template)
- Privacy Engineering: GDPR/CCPA compliance ($90K-$140K, regulatory requirement)
Why This Pivots Well:
Security expertise applies across industries. Compliance/governance harder to automate than technical monitoring. Regulation driving demand for human oversight. Can shift from technical → managerial → policy as automation advances.
Honest Warning:
- SOC analyst jobs shrinking NOW (entry-level positions vanishing)
- AI handling 60%+ of security operations work already
- Your timeline: 5-7 years before senior roles feel pressure
- Must shift from technical → governance/strategic FAST
- ServiceNow/OpenAI targeting IT operations = warning signal for adjacent security roles
Strategy:
- Don’t enter as SOC analyst (that’s the automated role – start higher)
- Go straight for governance/architecture if you can
- Specialize in AI security (new field, growing need)
- Build compliance expertise (regulatory moat provides protection)
- Plan transition to management/strategy by 2028
Entry Paths:
- Certifications: CompTIA Security+, CISSP, CISM (6-18 months)
- Cloud security: AWS Security, Azure Security certifications
- AI governance: Emerging field, no standard certification yet (build expertise through projects)
- Career changers from IT: Faster path than starting from scratch
#5. Construction Technology / BIM Specialists
Score: 73/100 | Viability: 3-5 years ⚠️⚠️⚠️ (MOST VULNERABLE)
Current Reality:
- Active hiring NOW (199 NYC, 271 LA, 510 remote positions)
- $24-$37/hour entry-level
- $31-$76/hour BIM modelers
- $70K-$210K BIM Directors/senior roles
- CHIPS Act + data center boom = infrastructure spending
- Digital transformation of construction sector
Why Demand Exists Now:
CHIPS Act manufacturing facilities, data center construction, infrastructure modernization all require BIM (Building Information Modeling) specialists who understand both construction AND technology.
The Double Acceleration:
- Infrastructure boom peaks 2028-2030 (CHIPS Act timeline, data center deployment cycle)
- Construction robotics generations shrinking: Bricklaying robots, 3D-printed structures, automated framing advancing FAST
When Change Comes (Soon):
- Infrastructure boom ends ~2030 (cyclical, not structural)
- Robotics handle routine construction (repetitive tasks automated)
- BIM becomes standard (not specialized) – commoditized skill
- Remote operations reduce on-site needs
- Demand crashes after boom cycle completes
Pivot Paths:
- Digital Twin Specialist: Ongoing facility management, building operations – BEST BET ($75K-$115K, long-term need)
- Smart City Infrastructure: Urban planning, IoT integration ($80K-$125K, emerging field)
- Facilities Management Technology: Building operations systems ($70K-$105K)
- Project Management (general): Skills transfer out of construction entirely ($85K-$130K)
- Real Estate Technology: PropTech, building analytics ($75K-$120K)
- Pivot OUT of construction by 2028: Use BIM/tech skills to exit before boom ends
Why This Barely Makes Top 5:
- Current demand is REAL (verified jobs, good pay, active hiring)
- But timeline is SHORT (3-5 years maximum)
- Window closing FAST (enter NOW or don’t enter at all)
- Only makes the list because it offers immediate income + clear pivot path to digital twins
Honest Warning:
- This is a TIMING PLAY, not a career
- Infrastructure boom = temporary (not structural demand like healthcare or aging population)
- After 2030: Demand crashes (cyclical construction pattern)
- Robotics eating construction faster than other sectors
- Most vulnerable position in our Top 5
- Data centers ≠ jobs (Meta: $50B investment = 500 permanent jobs by 2034)
Strategy:
- Enter ONLY if you can complete training by 2027
- Plan exit to digital twin/facilities management by 2029
- Save aggressively (this is a high-pay window to build financial runway, not a long-term career)
- Don’t depend on this past 2030
- Use it to fund training for your next position
Entry Paths:
- BIM certifications: Autodesk Revit, Navisworks (3-6 months)
- Construction background + tech training: 6-12 months
- Associate degree programs: Civil engineering technology, construction management (2 years)
NOT MAKING TOP 5 THIS WEEK:
Healthcare Data/Care Coordinators (was 78/100):
- Zippia: 4% decline projected
- Administrative coordination automating faster than expected
- Role consolidation with AI-augmented care managers
- Salary confusion ($34K vs $57K conflicting data)
- If you’re in this role: Pivot toward clinical positions (LPN, RN) or specialized health informatics
WHAT WE REVISED THIS WEEK:
Removed from pivot paths:
- ❌ Data Center Technician – Billions in investment ≠ meaningful employment
- ❌ Long-term construction careers – Robotics + boom cycle = short window
- ❌ Entry-level cybersecurity (SOC analyst) – Already automating
Compressed timelines:
- Healthcare: 10+ years → 7-10 years (administrative automation accelerating)
- Skilled Trades: 10+ years → 7-10 years (robotics closing dexterity gap faster)
- Edge Computing: 7-10 years → 5-7 years (platform consolidation coming)
- Cybersecurity: 7-10 years → 5-7 years (SOC work already automating)
- Construction Tech: 5-7 years → 3-5 years (infrastructure boom cycle + robotics)
The Honest Assessment:
NO position is truly “10+ years safe” anymore. The compression is REAL:
- AI generations: 6-12 months
- Robotics generations: 12-24 months (shrinking)
- Career retraining: 12-36 months
You literally cannot retrain faster than technology evolves.
HARDWARE SIGNAL: CEREBRAS
OpenAI/Cerebras Announcement (February 12, 1:02 PM):
OpenAI debuted its first AI model using Cerebras chips instead of Nvidia. Wafer-scale engine architecture vs. traditional GPU clusters. Different infrastructure requirements.
Why This Matters:
Hardware diversification happening. Nvidia dominance not guaranteed. Multiple chip architectures competing (Nvidia GPUs, Cerebras wafers, custom chips like Rivian’s).
But let’s be clear: This doesn’t create jobs for workers. It just changes which company profits from AI infrastructure. Whether you’re training models on Nvidia or Cerebras chips, the automation impact on workers remains the same.
The pattern: Companies compete on chip efficiency to reduce compute costs. Lower costs = faster AI deployment = more automation = fewer workers needed.
NVIDIA CEO: “7-8 YEARS OF BUILDOUT”
Jensen Huang to CNBC (February 12):
Nvidia CEO stated that demand is “sky high,” “massive AI CapEx is appropriate and necessary,” and “the AI build-out will take 7-8 years.”
Context: This is the company selling the GPUs. Profiting directly from every data center deal. Telling communities to commit to nearly a decade of infrastructure spending.
What He’s Asking:
7-8 years of buildout for technology that evolves every 6-12 months. By the time these facilities are complete, AI will have evolved through 8-16 generations.
Communities will be locked into 25-30 year tax commitments for infrastructure that’s obsolete before completion.
For Workers:
- Louisiana gives Meta $3.3B in tax subsidies for equipment? Nvidia profits.
- Oracle cuts 20,000-30,000 jobs to fund AI expansion? Nvidia profits.
- Legal sector loses $285B in market value from automation? Nvidia profits from the tools.
Meanwhile, Federal Reserve Vice Chair Philip Jefferson said the same day: “Job creation has been weaker than we’d like” and “I don’t want to see any further weakening in the labor market.”
The Disconnect:
The CEO selling infrastructure wants 7-8 year commitments. The Fed admits jobs are weakening NOW. Workers are being displaced today. And communities are signing 25-30 year tax deals for technology that will obsolete itself multiple times before contracts expire.
This is the acceleration gap made explicit.
BOTTOM LINE
The Data Doesn’t Lie:
- Jobs: Continuing claims 1,862K (people staying unemployed longer)
- WARN notices: 852 job losses/day (up 51% from 2025)
- Roles being cut: Content creation, customer support, data entry, basic coding
- Corporate response: Lobbying setup while workers have no seat at the table
The Compression Is Real:
AI generations: 6-12 months. Robotics: 12-24 months. Career retraining: 12-36 months. You cannot retrain faster than technology evolves.
The Top 5 We’re Providing:
These are real opportunities with verified demand, honest timelines (3-10 years), and clear pivot paths. They’re not “safe forever” – nothing is. But they offer:
- Current demand (actual job postings, competitive salaries)
- Better runway (3-10 years vs. immediate automation)
- Pivot options (transferable skills, adjacent roles)
- Resistance factors (physical presence, human judgment, regulatory protection, or distributed systems knowledge)
What These Positions Are NOT:
- Lifetime careers
- Automation-proof
- Guaranteed for 30 years
What These Positions ARE:
- Transition opportunities to build savings and skills
- Better options than positions already automating (retail, customer service, data entry, basic IT)
- Platforms for adaptation when the next wave hits
Your Responsibility:
- Don’t coast – even in these roles, stay current, build adjacent skills
- Watch signals – WARN notices, industry announcements, automation patterns
- Build runway – Emergency fund because timing your exit matters
- Plan pivots NOW – Don’t wait until layoff announcement
Check WARN Notices: WARNTracker.com provides 60-day advance notice of mass layoffs. If your company filed, you have 60 days to act. If they haven’t, start positioning anyway.
The Pattern: Companies file WARN notices → 60 days later → layoffs happen. The signal exists. Use it.
The “stable 30-year career” is dead. The question isn’t whether change is coming – it’s whether you’ll be ready when it does.
Use these five positions to build savings, develop adjacent skills, and plan your next move. Adaptation is the way.
SOURCES:
- Bureau of Labor Statistics: Initial/Continuing Jobless Claims (Feb 12, 2026)
- WARNTracker.com: Layoff data compilation (Feb 13, 2026)
- SkillSyncer: Tech Layoffs Tracker (Feb 13, 2026)
- SF Bay Area Times: Bay Area Tech Layoffs Feb 2026
- The Information: OpenAI memos to Congress (Feb 12, 2026)
- CNBC: Jensen Huang interview (Feb 12, 2026)
- LinkedIn: Job posting data for Edge Computing (Feb 2026)
- Glassdoor: Job posting data, salary ranges (Feb 2026)
- Indeed: Job posting data (Feb 2026)
- BLS Occupational Outlook Handbook: Healthcare, Trades, Cybersecurity projections
- Monster 2026 Healthcare Market Report
- CyberSeek: Cybersecurity job market data
- Robert Half 2026 Salary Guide
- Refonte Learning: Edge Computing careers analysis
- SecondTalent: Edge Computing Engineer skills/roles
- Multiple WARN Act state databases
Under the Radar publishes every Friday. Career intelligence for workers navigating AI transformation.
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