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Monday's episode told you WHERE to live in the AI economy. Today's episode tells you HOW.

Carlo Thompson breaks down the step-by-step relocation playbook: the job-vs-move-first question answered with actual data, the financial runway you need, the housing strategy that protects your capital, and how to build a professional network in a city where you know nobody.

📋 What you'll get today:
→ Move First vs. Job First — the real answer based on your situation
→ The true cost of relocation (most people underestimate by 40%)
→ The 6-month financial runway formula
→ Rent-first vs. buy — the 2026 math
→ The 90-Day Network Blueprint for a city starting from zero
→ How to negotiate relocation packages most people leave on the table

This is the advanced companion episode to Episode 22 (The Geographic Deep Dive). Monday gave you the city rankings. Wednesday gives you the execution plan.

📌 Key Stats Covered:
- Referrals fill 70–80% of professional jobs — the only strategy that scales in a new city
- Referred candidates are hired 30% faster and 4–5x more likely to land the role
- Average relocation packages: $15K–$75K — and most people never ask
- Full financial runway target: $15K–$30K before you move

🔔 Subscribe — new episodes every Monday and Wednesday on Surviving AI.

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Your zip code might be the most important career decision you make in the AI era — and most people aren't paying attention to it.

In this episode, Carlo Thompson breaks down the 2026 city tiers for AI economy survivability: which cities are winning the infrastructure buildout, which are quietly hollowing out, and exactly how to decide whether you should move.

What you'll get today:

• The 5-factor city scoring framework

• The full Tier 1–4 city rankings with 2026 updated data

• The Data Center Belt breakdown — and why it's creating $120K+ trades jobs

• The remote work paradox no one is talking about

• A concrete move decision matrix with 3 strategic options

Updated Stats Covered:

• 40,000 construction jobs from TSMC Arizona alone

• 340,000 data center positions could go unfilled by end of 2026

• Electricians on data center projects earning $240K–$280K in Texas

• Healthcare postings 22.6% above pre-pandemic levels

• Intel New Albany: 3,000 Intel jobs + 7,000 construction jobs (2030 timeline)

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The college decision in 2026 is not the same as it was in 2006. With AI compressing entry-level white-collar jobs and 25% of bachelor's degree programs delivering a negative ROI, families need a new analytical framework — not social inertia.

In this bonus episode of Surviving AI, Carlo Thompson runs the full math on the college vs. trades vs. apprenticeship decision in the AI economy.

**What you'll learn:**
- Why workers aged 22–25 in AI-exposed roles have already seen a 16% employment drop — and what that means for new graduates
- The 25% of degree programs with negative ROI — and how to know if you're about to enroll in one
- The trades and apprenticeship math nobody shares: $80K starting salary, 90% employment, $3K–$15K cost
- The "sheltering in higher education" trap — why grad school as AI anxiety relief is usually the wrong call
- The 5-question decision framework for making this call analytically

📊 **Key data this episode:**
- 25% of bachelor's degree programs: negative ROI (Fed Reserve Bank of NY)
- 51% of Gen Z regret going to college
- Workers with AI skills earn 56% more than peers in identical roles
- Apprenticeship completers: ~$80K year one, 90%+ employed
- Trade vs. college net position by age 22: $80K–$150K ahead for the trade path

🎙️ Surviving AI Bonus Episode | Companion to Episode 21: The Family Strategy

📌 **SUBSCRIBE:** Apple Podcasts | YouTube | Spotify