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AI & Tech

Gen Z turns on AI leaders

Wednesday, May 20, 2026 · from 4 podcasts
  • Recent grads boo AI commencement speakers, calling tech leaders' vision a betrayal of their futures.
  • OpenAI and Anthropic now take 89% of AI startup revenue, fueling duopoly fears.
  • Behind closed doors, AI executives admit workers are 'screwed,' while job data defies doomerism.

Graduation season turned sour this year. At multiple universities, students jeered speakers who praised AI’s promise. The protest wasn’t about automation replacing clerical work - it was about CEOs like Ken Griffin confirming AI now does PhD-level analysis in hours. Jason Calacanis called it a betrayal: a generation spent years earning degrees only to hear the architects of AI predict their obsolescence.

The anger isn’t abstract. A Stanford senior’s viral New York Times essay claimed AI has already hollowed out the value of liberal arts degrees. Students used ChatGPT to pass courses, then watched companies automate the very roles they trained for. Calacanis likened the mood to the 1960s anti-war movement - drafted into an AI revolution they never signed up for.

On the ground, the data cuts both ways. Software engineering job postings are up 18% year-over-year, and unemployment for college grads aged 20-24 dropped from nearly 9% to 5%. Anthony Pompliano notes companies are hiring more engineers than before, not fewer. Yet Jasmine Sun observes that AI leaders like Dario Amodei privately admit the median worker faces a bleak future - 'screwed' in their own words.

"Silicon Valley is bracing for a permanent underclass."

- Jasmine Sun, Bankless

That dissonance - between public optimism and private pessimism - fuels AI populism. Sun notes the issue has risen faster in polling than any other over the past year, even as it ranks below cost-of-living concerns. Politicians like Bernie Sanders are seizing it, framing AI as an elite project to dismantle the middle class. Unlike crypto, which few used, AI touches everyone: 70% of Americans say it’s moving too fast.

The economic model is shifting beneath their feet. Nathaniel Whittemore points to Anthropic’s ARR exploding from $9 billion to over $44 billion in months, doubling every six weeks. The 'token factory' model means one user can now generate thousands in monthly revenue - making OpenAI and Anthropic a duopoly capturing 89% of AI startup revenue.

"We’re moving into an era where every job becomes a potential startup."

- Nathaniel Whittemore, The AI Daily Brief

Still, the promise of 'working being optional' rings hollow to grads entering a job market defined by precarity. Calacanis argues the only escape is entrepreneurship - citing Stripe Atlas hitting 100,000 incorporations with Q1 filings up 130%. But for most, the message is clear: if you don’t own the model, you’re a cost center.

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5/19/26: Trump $1.8 Billion Slush Fund For Allies, Students Boo AI At Graduation, Kars4Kids Scandal EruptsMay 19

  • Donald Trump dropped a lawsuit against the IRS, initiating a settlement that created an "Anti-Weaponization Fund" of taxpayer dollars. The fund aims to compensate individuals politically targeted for prosecution.
  • Saagar highlights the unusual nature of the Anti-Weaponization Fund, noting that similar compensation funds, like the 9/11 Victims Compensation Fund, are typically created by Congress, not through an executive settlement.
  • Krystal and Saagar contend that the fund is intended to benefit Donald Trump's allies, including January 6th participants and individuals prosecuted during previous administrations, raising concerns about direct government payouts without a clear process.
  • Saagar reports that at least 33 pardoned January 6th individuals faced other criminal charges, including DUI, felonies for threats, and child sex crimes, with some allegedly reoffending after receiving pardons.
  • Saagar criticizes the administration for dropping fraud charges against Indian billionaire Gautam Adani, involving allegations of hundreds of millions in bribes to secure deals in India. US jurisdiction applied due to misleading US investors.
  • Krystal and Saagar argue that inconsistent application of fraud laws, pardoning wealthy individuals while prosecuting others, erodes public trust in the rule of law and the social safety net.
  • A federal court rejected Elon Musk's lawsuit against OpenAI on a technicality, stating the statute of limitations had run. Musk alleged OpenAI abandoned its original non-profit, open-source mission by becoming a for-profit entity.
  • Recent college graduates booed commencement speakers who discussed AI, reflecting widespread skepticism, especially among young people, about AI's impact on the job market and their future.
  • Polling shows 70% of Americans believe AI is developing too quickly, with over 50% holding negative views. Only 18% of young people express hope about AI, largely due to concerns about job displacement.
  • Ken Griffin, a top financier, noted that AI tools have profoundly increased productivity in the past nine months, automating work that previously took weeks or months for highly skilled professionals into hours or days.
  • A California court banned Cars for Kids advertisements in the state after finding the charity violated false advertising laws. The lawsuit, filed in 2021, revealed donations did not go to underprivileged children in California as implied.
  • A report from Haaretz claimed ICC prosecutors were seeking arrest warrants for Israeli officials Ben Gvir and Smotrich for alleged war crimes, though the ICC disputed this report. Warrants were previously issued for Netanyahu and Gallant.
Also from this episode: (2)

Corruption (1)

  • Testimony in the Cars for Kids case showed that out of $45 million raised annually, 60% went to Aura, a New Jersey-based Orthodox Jewish organization that funded adult matchmaking, teen trips to Israel, and summer camps, with 16.5 million used to buy a building in Israel.

Politics (1)

  • Benjamin Netanyahu publicly stated that Israel controls "60% of the strip" in Gaza and implied further expansion, boasting about retrieving hostages without ceding territory and noting his corruption trial was again delayed for security reasons.

Why is Gen Z hates AI?May 18

  • Jason Calacanis argues college graduates fear AI not out of simple anxiety but from feeling betrayed by tech leaders like Eric Schmidt, who they believe have bad intent about job displacement.
  • Calacanis says this generation has used ChatGPT for two years to complete degrees and understands the technology well, which fuels their cynicism about future job prospects.
  • Hosts note a stark gap between business excitement about AI and average consumer sentiment, particularly among recent graduates entering the workforce during economic uncertainty.
  • A viral New York Times essay by Stanford senior Theo Baker claimed cheating with AI is omnipresent on campus, dissolving the foundations of liberal arts education faster than the workforce.
  • Calacanis believes the only way to escape a permanent underclass in the AI economy is to start a company, as being a worker for someone else makes you a cost center.
  • Jason Calacanis advocates for 'delightful scale' companies making $500k to $5M annually as a viable path, arguing necessity and modern tools like ChatGPT lower the barrier to entry.
  • The Information reports Anthropic and OpenAI generate 89% of all AI startup revenue, creating a duopoly that is consolidating power.
  • Hosts note that six months ago, Anthropic and OpenAI represented 4.5% less of total startup AI revenue, indicating they are rapidly gaining market share.
  • Calacanis suggests potential safeguards for surveillance tech like Flock include strict audit trails, biometric access logs, and enforced data retention policies of up to 36 months.
  • Jason Calacanis advises against using AI alone to file patents due to the high-stakes, specialized legal nature of IP, though it can be used with a human-in-the-loop for initial work.
  • Calacanis believes running AI models locally on hardware like Mac Studios is the future for privacy and cost reasons, not a fad, especially for sensitive corporate data.
Also from this episode: (5)

AI Infrastructure (3)

  • A University of Utah study projected US data center construction jobs will peak and then decline, with total direct operations jobs reaching only about 65,000 by 2030.
  • Calacanis highlights that tech companies cut 100,000 jobs in the first part of the year, a figure already surpassing the total data center jobs projected for 2030.
  • Calacanis argues AI model providers like OpenAI and Anthropic are likely selling tokens at a massive loss currently, similar to Uber and Lyft's early subsidized growth phases.

Startups (1)

  • Hosts discuss the risk for application-layer AI startups, as major labs gaining access to their usage data could quickly build competing features and erase their market.

Society (1)

  • The shooting incident in Austin highlighted the privacy-versus-safety debate around Flock Safety's license plate readers, which the city council had removed but a neighboring county used to capture suspects.

Beating the AI Doom CycleMay 18

  • Nathaniel Whittemore identifies an emerging "AI vibe shift," characterized by a growing discourse that moves beyond doomerism, appearing in both job market discussions and financial markets. This dual emergence suggests a potential narrative shift rather than a temporary blip.
  • Jasmine Sun's New York Times essay, "Silicon Valley is bracing for a permanent underclass," reflects a prevalent doomer narrative among AI builders in Silicon Valley who believe AI will eliminate jobs. Whittemore questions over-reliance on builders' perspectives due to potential biases and their limited understanding of broader economic impacts.
  • Ezra Klein argues that the AI job apocalypse is unlikely, highlighting AI labs' role in creating negative narratives to excite investors or unwind post-COVID hiring. Economists, he notes, are generally skeptical of mass joblessness.
  • Klein cites ASU professor Eldar Maximov's research, indicating that employment grew faster in occupations heavily adopting computers than in those that did not. Cost reductions from task automation led to new demand, expanding overall occupations.
  • Klein also uses a personal example, noting his podcast team grew significantly after starting with one researcher, leading to more extensive and challenging episodes. He observes that enthusiastic AI adopters are working harder than ever due to increased possibilities.
  • Klein suggests AI is more likely to displace a limited number of workers rather than cause mass unemployment. He argues this localized displacement, similar to the 2 million jobs lost to Chinese competition, might be harder to manage than a mass event.
  • Macroeconomic data does not support the doomer narrative, with the unemployment rate at 4.3% in March 2026 and 4.4% in March 2020, and stable average hourly earnings. Demand for software engineers, despite AI exposure, continues to accelerate, up 18% since May last year.
  • Anthony Pompliano notes a shift in his view, now observing increasing hires for software engineers and growing open roles. He states that new college grad hires rose 5.6% over the past 12 months, and unemployment for 20-24 year-olds with college degrees dropped from nearly 9% to almost 5%.
  • A Wall Street Journal and LinkedIn analysis reports AI created 640,000 jobs in the US between 2023 and 2025, including new white-collar positions like Head of AI. Pompliano suggests companies are aggressively hiring, leveraging AI to boost employee productivity.
  • Merzmik Ahmed argues that AI increasing demand for software engineers is now a tech consensus. He applies Jevons' paradox, explaining that cheaper "digital bricks" (code) make previously expensive projects feasible, thus expanding demand for builders.
  • Greg Eisenberg predicts an unprecedented explosion of entrepreneurship as intelligence becomes cheaper and displaced workers create new businesses out of necessity and opportunity. Stripe Atlas data supports this, with 100,000 incorporations and Q1 up 130% year-over-year.
  • Roger Karma in The Atlantic notes a market shift: from concerns over AI infrastructure lacking profitability six months ago, to fears of insufficient data centers today. This change is driven by revenue catching up to hype, particularly with the rise of "Claude code."
  • The market narrative has shifted from "seats" to "tokens," as AI agents consume vastly more resources, making a single user generate hundreds or thousands of dollars monthly in token sales. This redefines the economic model for AI companies.
  • Anthropic's run rate revenue surpassed $30 billion by early April. SemiAnalysis reports its ARR surged from $9 billion to over $44 billion today, doubling every six weeks, with inference margins reportedly at 70%, up from 38% last year.
  • Ming Li highlights Anthropic's rapid growth, noting it's adding $96 million in ARR per day. He contrasts this with AWS taking 13 years to reach $35 billion and Salesforce over 20 years to pass $20 billion, indicating that old software valuation frameworks are obsolete.
  • Atlassian's stock surged almost 30% after its earnings report, with revenue growth accelerating to 32% (from 23% last quarter). Customers using their new AI search tool, Rovo, increased their own ARR at twice the rate of non-users.
  • The Associated Press reports that construction unions are collaborating with tech companies to overcome community opposition to data centers. Rob Bear of the Pennsylvania Building and Construction Trades Council emphasizes data centers create significant construction jobs.
  • Sam Altman, OpenAI CEO, stated on May 1st that the goal is to augment and elevate people, not replace them, and believes jobs doomerism is likely wrong long-term. He also noted that even with powerful AI, he has "never been busier."
  • Economic commentator Noah Smith views Altman's statements as a "huge messaging pivot" for OpenAI and the AI industry, which previously explicitly stated goals of replacing humanity. This shift suggests a more constructive dialogue about AI's impact.
Also from this episode: (3)

Big Tech (2)

  • Morgan Stanley raised CapEx forecasts for five hyperscalers to $805 billion this year (from $765 billion) and $1.1 trillion next year (from $951 billion). Andreas Steno Larsen notes that the backlog of demand for additional capacity is rising even faster than CapEx spend.
  • Mag Seven companies spent over $400 billion in CapEx in Q1 this year, but their reported and projected backlog stands around $1.3 trillion, indicating significant unmet demand. David Sacks argues AI CapEx will contribute a 2% tailwind to GDP growth this year, potentially 2.5% this year and over 3% next year per Morgan Stanley.

Enterprise (1)

  • Atlassian's Rovo leverages existing knowledge graphs in Jira and Confluence for context, significantly reducing token usage compared to token-hungry RAG search. This token efficiency, crucial in an agent intelligence era, helps maintain seat-based pricing models.

Will AI Populism Decide the 2028 Election? | Jasmine SunMay 13

  • Jasmine Sun says AI populism ranks 29th in salience among voter issues but has risen faster than any other issue over the last year according to Blue Rose Research polling.
  • Sun notes politicians like Bernie Sanders tie AI to core economic issues voters care about, framing it as an elite project to be resisted.
  • Sun argues AI populism differs from anti-crypto sentiment because AI drives a larger share of GDP and has higher consumer adoption.
  • Sun cites Anthropic hitting a $30 billion annual run rate and notes AI leaders like Dario Amodei predicting mass job loss lend credibility to populist fears.
  • Sun points to violent attacks on Sam Altman and the healthcare CEO murder as examples of extreme online nihilism, not a unified movement.
  • Sun explains AI industry executives often express bleak private views on job displacement but avoid saying them publicly.
  • Sun steelmans Dario Amodei's job loss argument by saying AI could break the link between human labor and productivity, unlike past automation.
  • Sun's own view expects near-term disruption for easily automated jobs like software engineering, but not an apocalypse, with significant political resentment.
  • Sun observes AI populism coalitions are bipartisan, uniting environmentalists, family-first conservatives, and creatives against tech elites.
  • Sun warns AI super PAC endorsements can become a political liability due to populist sentiment, unlike crypto's Fairshake PAC.
  • Sun proposes shortening the work week as a preferable alternative to mass unemployment if AI automation accelerates.
Also from this episode: (2)

Politics (1)

  • Sun suggests policy responses should include longer unemployment insurance, universal healthcare for freelancers, and rethinking education.

Labor (1)

  • Sun advocates for a grand bargain where productivity gains are shared, citing historical union bargaining as a model to avoid backlash.