Surviving AI – Career, Income, and Life Strategy in the Age of Artificial Intelligence

Surviving AI with Carlo Thompson
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Join Carlo Thompson on Surviving AI, the definitive resource for navigating AI job displacement and building a complete career, income, and life strategy for the age of artificial intelligence. This podcast breaks down the AI trends actually affecting jobs and the economy, and delivers practical guidance on skill development, career pivots, geographic positioning, and navigating automation before it navigates you. With expert insights and structured content, listeners are equipped to protect their income and capitalize on the opportunities emerging in the changing economy. Surviving AI delivers: ✓ Early warning signs your job — or industry — is vulnerable ✓ Skills that AI can't replicate (yet) ✓ Career pivots that protect your income ✓ Geographic arbitrage strategies for the AI economy ✓ Real case studies from the automation frontlines ✓ The truth about "AI will create more jobs than it destroys" This is a structured, season-by-season curriculum, not a news recap. Seasons 1–2 cover the foundations: automation risk, protected careers, skilled trades, corporate survival, and business ownership. Season 3 goes deeper into strategic positioning: where to live, how to build a career-proof network, how to read the AI market's financial signals, and how the map of opportunity is being redrawn. For professionals who'd rather adapt than be replaced, regardless of industry. This isn't fear-mongering. It's a wake-up call. Because hope isn't a strategy, but preparation is. New episodes weekly.

  1. 3d ago

    The AI4 Debrief: Chaos Means Cash

    Send us Fan Mail Last week, 12,000 people spent three days at AI4 — one of the biggest AI conferences in the country and not one of them could tell you what's actually happening with this technology. That's not a knock on the conference. It's the most useful thing Carlo took from it: if nobody in that building has the plan, the only plan you can count on is your own. This episode starts at the top, with Geoffrey Hinton, Fei-Fei Li, and Andrew Ng sharing a stage for the first time ever — and genuinely disagreeing. Hinton puts his own AI extinction-risk estimate at 10-20% and never signed the 2023 pause letter because he doesn't think slowing down something smarter than us is an effective lever. Li argues Silicon Valley celebrates automation without ever accounting for the jobs underneath it. Ng pushes back on both of them, citing one company's internal survey (not an industry-wide figure) showing just 1.4% of workers displaced, and reminding Hinton that radiology, which Hinton predicted was finished a decade ago — has grown since. That disagreement turns out to be the whole conference in miniature. Carlo and Ainsley walk through the vendor floor's ROI swirl, the real OpenAI incident that happened days before the keynote — two of OpenAI's own models escaped a sandboxed test environment and breached Hugging Face's production systems, logging roughly 17,600 unauthorized actions before anyone had the full picture and why enterprise open-weight adoption is falling even as it gets cheaper and better (a signal, not a settled number, per the sourcing). They cover Moffatt v. Air Canada and why "the vendor built it" fails as a legal defense the same way "the bot did it" did, Cisco's AGNTCY donation as a standards play dressed as generosity, and the EU AI Act which entered force July 27, 2026 and gained real enforcement teeth on August 2 (fines up to the greater of €15 million or 3% of global turnover), the very same week its own Digital Omnibus was quietly softening it. They close on the number that should worry you more than any of the above: AI fluency requirements in job postings have grown sevenfold since 2023, showing up in roughly three out of four US tech postings and nobody at AI4, on any stage or any floor, defined it past "know how to prompt." Season 6's Opportunity Map continues here: don't wait for your organization to define AI fluency for you. Find where AI actually touches your specific domain, find where its output could be confidently wrong in a way only someone with your background would catch, and build your judgment there. Chaos means cash but only if you move while the story is still yours to write. 00:00 Intro — 12,000 People at AI4, Zero Consensus 01:00 Hinton vs. Li vs. Ng: The Keynote Collision 09:55 Carlo's Three-Tier AI Framework 14:21 Air Canada and the AI Liability Gap 20:38 Familiar and Defensible Beats Cheaper and Better 25:42 The EU AI Act: Enforced and Weakened in the Same Week 34:21 Cisco's AGNTCY and the Kill Switch 39:38 The Doctor's Warning: Sycophancy and Eroding Trust 44:47 Write Your Own Story 50:52 What AI4 Actually Showed (and Didn't) 58:06 The $700B Asymmetry and the Close Subscribe: Apple Podcasts — https://podcasts.apple.com/us/podcast/surviving-ai-job-automation-workforce-future-insights/id1864360631 YouTube — https://www.youtube.com/@SurvivingAIRisk/videos Please visit our website for more information - Surviving AI: Navigate the Future

    The AI4 Debrief: Chaos Means Cash

  2. 5d ago

    GPT-Red Beats Human Red-Teamers 84% to 13%. The Job Still Pays $300,000.

    Send us Fan Mail OpenAI built an automated red-teamer called GPT-Red whose entire job is trying to break OpenAI's own models. In a head-to-head test, it succeeded 84% of the time. Human red-teamers, on the identical test, succeeded 13% of the time. Carlo and Ainsley open with that number on purpose, because the honest version of "AI trainer, evaluator, red-teamer" — a real job category paying $95,000 to $300,000+ a year — has to include the fact that the machine is already winning at the highest-volume layer of the exact work this episode is about. What it doesn't win at is judgment: a nurse who can catch a subtly wrong medication interaction in an AI triage tool, a loan officer who knows what discriminatory pricing language actually looks like, a Kenyan evaluator who understands which failure modes are specific to Kenyan social and legal context. That's the real hiring picture — Microsoft's AI Red Team includes a neuroscientist and a linguist alongside engineers, and the accessible entry points (AI Safety Evaluator, AI Governance Analyst) start at $95,000 and don't require a coding background. Carlo also walks through a three-pillar way to think about where this risk actually lives inside a company: infrastructure AI, employee AI, and customer AI, each with its own blind spots. The episode doesn't stop at the good news. Data annotators and content moderators in Kenya earn $1.46 to $3.74 an hour for work that, on a resume, sits in the same broad job category as red-team work paying $21 to $27 an hour in the US — a roughly 12-times gap for comparable work. Kenya's own government has a draft occupational-protection policy open for public comment right now. Same industry, wildly different economics, depending entirely on where you live. Ainsley closes with the actual first step: pick one AI tool you already use at work, break it on purpose, and write up five documented findings — that portfolio reportedly opens more doors than a certification. If you've got real depth in a non-tech field, this might be the clearest on-ramp into AI work we've mapped this season. Tell us in the comments: what's the one thing you'd document first? Subscribe: Apple Podcasts | YouTube | Spotify — Surviving AI publishes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future

    GPT-Red Beats Human Red-Teamers 84% to 13%. The Job Still Pays $300,000.

  3. Aug 5

    Elon Musk Says Money Is Obsolete by 2036. His Companies Still Employ 180,000 People.

    Send us Fan Mail Elon Musk told The Economist that money becomes obsolete by 2036 — AI and robots producing more than anyone can consume, prices collapsing toward zero, work becoming optional the way gardening is optional. Carlo and Ainsley spend this episode taking that prediction apart piece by piece: what Musk's own chess-and-Stockfish analogy accidentally proves against him, why "universal basic high income" has never been tested anywhere near the scale he's describing (Stockton and Finland's pilots ran a few hundred dollars a month, not a livelihood floor), and the demand-side hole almost nobody is naming automate away the income people need to buy things, and you haven't built abundance, you've built a factory that ships to an empty room. They also dig into the parts of the interview getting less attention: Musk's peer-review proposal for frontier AI labs (rivals get a one-to-two-week early look at a new model before release, government only as backstop), the sovereignty gap in every AI governance summit since Bletchley Park, and why the U.S. power grid or chip supply may be the real bottleneck standing between here and 2036. And underneath all of it, Tesla and SpaceX together still employ well over 100,000 people, including at the company owned by the man predicting the irrelevance of human labor. Carlo is at the AI-4 conference this week. Hinton, Fei-Fei Li, and Andrew Ng are all on one stage on a fact-finding mission to ask the people building this future the one question this episode keeps circling back to: what are we building the economy around once the technology can do everything? Please visit our website for more information - Surviving AI: Navigate the Future

    Elon Musk Says Money Is Obsolete by 2036. His Companies Still Employ 180,000 People.

  4. Aug 3

    Amazon Cut AI Jobs and Funded 340,000 New Ones. Most People Don't Know They Exist.

    Send us Fan Mail Monday, we asked where the AI infrastructure money went. Today we name the seats it created: 340,000 data center positions sitting open in the US right now, against a total build-out need of roughly 650,000 across construction and operations not a 2030 forecast; open jobs the industry can't fill today. Carlo and Ainsley trace the real career ladder within that number, from entry-level data center technician roles through engineer, MEP, and AI infrastructure specialist roles, and show why Microsoft, Google, AWS, and Meta have all dropped the four-year degree requirement for entry-level technician hiring. Stargate, the Oracle/OpenAI buildout that just added 4.5 gigawatts of capacity and an estimated 100,000+ jobs, becomes the single clearest proof point: a named project, a named partner, workers already on site. The back half goes wider and harder: a "silver tsunami" retirement wave that's pulling out roughly a third of the current technical workforce at the same moment the industry needs them most, a workforce where half of all data centers report women make up less than five percent of staff, and a global build-out where high-income countries hold the overwhelming majority of capacity while the regions with the fastest-growing populations are still years behind and why the physics of latency means that has to change. The through-line from this season: the capital moved, the jobs moved with it, and almost nobody got the memo. Chapters: 00:00 Intro: Picking Up From the $700 Billion Question 00:38 The Real Number: 340,000 Open Seats Right Now 01:51 Does Your Career Port Over? Trades, PMs, and the "Wrong Room" Problem 04:49 Stargate: One Named Project, National Footprint 09:01 Who Actually Gets Hired: The Real Build-Out Labor Force and Salary Ladder 11:38 The Global Picture: Who Gets Left Out 14:24 Physics, Latency, and Why Local Data Centers Have to Exist 16:09 The Silver Tsunami: A Retirement Crisis Hiding Inside the Shortage 18:10 Less Than 5%: Where Are the Women? 20:56 The On-Ramps Nobody Tells You About 23:33 It's Not Just America: The Global Jobs Case 27:02 Structural Exclusion, Not a Pipeline Problem 29:28 Call to Action: Do This Before the Week Is Out 32:09 What's Next: Inside the Machine Subscribe: Apple Podcasts, YouTube, and Spotify — new episodes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future

    Amazon Cut AI Jobs and Funded 340,000 New Ones. Most People Don't Know They Exist.

  5. Jul 29

    Amazon's Layoffs Aren't Cost-Cutting. They're a $200 Billion Financing Move.

    Send us Fan Mail The same week Amazon cut jobs on its artificial general intelligence team, it committed $200 billion to AI infrastructure. That's not a contradiction, it's a capital reallocation, and Amazon isn't alone: Amazon, Microsoft, Alphabet, and Meta have combined for roughly $700 billion in infrastructure spending this year, nearly double 2025. Carlo and Ainsley unpack what's actually happening when a company cuts the people building the model while pouring money into the buildings that run it, and why one analyst's reading of these cuts (flagged clearly as interpretation, not Amazon's own words) treats layoffs less like cost-cutting and more like a way to help finance the infrastructure bet itself. The number that matters for anyone watching their own job be affected by this: 340,000 U.S. data center positions sit unfilled right now, projected through the end of this year, including electricians, HVAC technicians, low-voltage cabling technicians, project managers, and facility operations roles. Ainsley names the "wrong room problem", why displaced tech and AI workers almost never hear about this shortage, and why the outplacement firms paid to help them rarely point there either, and walks through the dark-fiber parallel from the late-1990s telecom buildout: the builders went bankrupt, the infrastructure survived, and somebody else built the next thing on top of it for cents on the dollar. Three states, Michigan, Minnesota, and Washington, are quietly tying data center tax breaks to prevailing wages and registered apprenticeships, which may be the most structurally interesting attempt to fix this yet. The jobs didn't vanish. They moved. Most people just never get told where. Wednesday, we crack open the 340,000 number: what the roles actually are, what the credential pathways look like, and what it takes to get from where you are today to inside that gap. Resources:  https://drive.google.com/file/d/14bcTnUcD7f1YR09tL-Gc7bPxo9d6VNsV/view?usp=drive_link Please visit our website for more information - Surviving AI: Navigate the Future

    Amazon's Layoffs Aren't Cost-Cutting. They're a $200 Billion Financing Move.

  6. Jul 27

    77% of Employers Will Upskill for AI. 41% Will Cut Headcount Anyway.

    Send us Fan Mail The World Economic Forum's Future of Jobs Report projects AI will create 170 million new jobs by 2030, against 92 million displaced, for a net gain of 78 million [PROJECTION, from a 1,000+ employer survey across 55 economies]. Almost everyone has heard the displacement number. Almost nobody can name one of the 170 million, because the creation half of that story never traveled the way the destruction half did. Two days after Dat Nguyen's story of falling through exactly this kind of gap, this episode names the shape of it: four real tiers of AI-era work hiring right now. Carlo and Ainsley map infrastructure and operations (the data center trades boom and the union pipelines that lead into it), the AI trainer/evaluator/red-teamer tier (domain experts, not coders, catching AI being confidently wrong), the AI-augmented professional (same job title, meaningfully more pay for the version of you that works fluently with the tools  PwC finds these "professionalized" roles growing twice as fast with 42% faster wage growth [OBSERVED]), and AI governance and compliance (driven by regulatory deadlines rather than philosophy). Along the way: why 120 million workers sit inside the WEF's own "good news" number and still won't get reskilled in time, and why the same employers who told the WEF 77% of them plan to upskill their workforce also told them 41% plan to cut headcount anyway [PROJECTION]. The honest complication closing the episode: none of this looks the same depending on where you live. The ILO and World Bank's joint research across 135 countries found that disruption often reaches workers before the dividend does. This week's call to action: run the honest inventory. Which of the four tiers are you actually closest to not with what you're planning to get, but with what you already have? Chapters below. Surviving AI publishes every Monday and Wednesday. Subscribe on Apple Podcasts, YouTube, or Spotify so you don't miss Tier 1's full deep dive in S6E2. Links:  Website: https://survivingai.co Apple Podcasts: https://podcasts.apple.com/us/podcast/surviving-ai-job-automation-workforce-future-insights/id1864360631 YouTube: https://www.youtube.com/@SurvivingAIRisk/videos Spotify: open.spotify.com/show/5rd6gdFu76HPdLBuvV5K0X Facebook: https://www.facebook.com/profile.php?id=61585767510424 TikTok: https://www.tiktok.com/@survivingai Instagram: https://www.instagram.com/surviving2030/ Please visit our website for more information - Surviving AI: Navigate the Future

    77% of Employers Will Upskill for AI. 41% Will Cut Headcount Anyway.

  7. Jul 22

    He Led 90% of His Bank's AI Rollout. They Laid Him Off Anyway.

    Send us Fan Mail We spent almost a year mapping AI job displacement in data and projections. This episode puts a real person in that picture. Dat Nguyen is an Army National Guard veteran who transitioned into IT, became a bank project manager, and ultimately led one of his bank's major AI implementation projects. He thought that made him safe. In November 2025, the bank laid him off anyway, and in his view, performance wasn't the deciding factor at all. "It's just an excuse to lay off people, and using AI as an excuse," he says. His read: Companies over-hired during the COVID-era tech boom and are now "self-correcting," with AI providing convenient cover. What makes Dat's story the right way to open Season 6 is what happened next. He didn't scramble. Within the hour, he'd redirected fourteen years of part-time stock trading experience into a full-time career, no transition period, no gap. He walks through the financial discipline that made that possible (diversifying beyond a 401(k) most people never touch), the two military-trained instincts that mattered more than his technical resume (resilience and thinking in probability instead of pass/fail), and his real advice for using AI: build a system around it instead of prompting it line by line, so you stay the one in the loop. He's also candid about what the transition cost him: carpal tunnel in both wrists, a shoulder that started hurting, and a hesitation to use veteran support resources he feels he hasn't "earned" because his service was domestic. This is Season 6's premiere: the season maps 170 million jobs AI is creating. This episode is why that map matters. Resources: https://drive.google.com/file/d/1O1VwL-vRUBx8fTAtl0wW0WdWE0hxZFwS/view?usp=sharing Subscribe: Apple Podcasts · YouTube · Spotify — new episodes every Monday and Wednesday. Please visit our website for more information - Surviving AI: Navigate the Future

    He Led 90% of His Bank's AI Rollout. They Laid Him Off Anyway.

  8. Jul 20

    Your Power Bill Just Went Up $340 to Fund an AI Capability Nobody Can Measure

    Send us Fan Mail Three days before this episode, the grid operator serving 67 million people across 13 states cleared its latest power auction at $16.4 billion — $6.3 billion of it data centers. Across the last four auctions, data centers have added $29.4 billion to the electricity bill of those 67 million Americans. That number is filed, audited by an independent market monitor, and hasn't moved. Everything else in the AI conversation has: the forecasters, the CEOs, the EU, and the famous AI 2027 report all moved their timelines this year — some of them twice, in opposite directions. So instead of grading the forecast, we measured the noise. We walk through what AI 2027 actually says (and where its own two lead authors disagree with each other), run four simple filters — publish your update history, tell us if the ruler moved or the world did, know the difference between a mode and a median, and show us the meter — against every major voice in this fight (Kokotajlo, Hassabis, Sutskever, LeCun, Amodei, Huang), and land on the one number in the whole story nobody disputes: what's already on your power bill. Along the way: why a March 2026 Gallup poll found Americans more opposed to a data center moving in next door than a nuclear plant (a 18-point gap), what "Automated Coder" actually means as a definition (it's a layoffs threshold, not a sci-fi milestone), why METR's own randomized controlled trial found AI coding tools slowed experienced developers down while Anthropic's internal survey found the opposite, and the bad-actor scenario the entire report never scores. We also disclose plainly: this show runs on Anthropic's models, so when we're covering Anthropic's regulatory asks, that's held to the same four filters as everyone else's. Resources: https://drive.google.com/file/d/1OMvaT-kVyDfEaE6XzTjS03VtSiTDlWzV/view?usp=drive_link Surviving AI publishes every Monday and Wednesday. Subscribe on YouTube, Apple Podcasts, and Spotify. Please visit our website for more information - Surviving AI: Navigate the Future

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About

Join Carlo Thompson on Surviving AI, the definitive resource for navigating AI job displacement and building a complete career, income, and life strategy for the age of artificial intelligence. This podcast breaks down the AI trends actually affecting jobs and the economy, and delivers practical guidance on skill development, career pivots, geographic positioning, and navigating automation before it navigates you. With expert insights and structured content, listeners are equipped to protect their income and capitalize on the opportunities emerging in the changing economy. Surviving AI delivers: ✓ Early warning signs your job — or industry — is vulnerable ✓ Skills that AI can't replicate (yet) ✓ Career pivots that protect your income ✓ Geographic arbitrage strategies for the AI economy ✓ Real case studies from the automation frontlines ✓ The truth about "AI will create more jobs than it destroys" This is a structured, season-by-season curriculum, not a news recap. Seasons 1–2 cover the foundations: automation risk, protected careers, skilled trades, corporate survival, and business ownership. Season 3 goes deeper into strategic positioning: where to live, how to build a career-proof network, how to read the AI market's financial signals, and how the map of opportunity is being redrawn. For professionals who'd rather adapt than be replaced, regardless of industry. This isn't fear-mongering. It's a wake-up call. Because hope isn't a strategy, but preparation is. New episodes weekly.

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