Pope Leo's AI manifesto, Uber questions its AI spend, and the quiet crisis in entry-level jobs

Something quietly shifted this week - and it didn't come from Silicon Valley.

The most consequential statement on AI this month came from the Vatican. Then, within 24 hours, Uber's president told the world its AI spending is getting "harder to justify." And MIT Technology Review published a piece that cuts right to the bone on who's actually being hurt by all of this. Today's newsletter threads all three together - because they're telling the same story from very different angles.

Pope Leo XIV's encyclical on AI is named 'Magnifica Humanitas' - but what does that Latin phrase translate to in English?

The answer is hiding near the bottom of today's newsletter... keep scrolling. 👇

Pope Leo XIV released his first major papal document on Monday - and it's entirely focused on artificial intelligence. 'Magnifica Humanitas' is the Church's formal statement on "safeguarding the human person in the time of artificial intelligence," and it doesn't pull punches.

The Pope called for the "disarming" of AI, specifically targeting its use in autonomous warfare. He denounced what he called the "culture of power" driving the rapid rise of the technology, warning that AI must be subject to the "most rigorous" ethical constraints as it infiltrates everything from work to war. The encyclical draws a direct parallel to Leo XIII's 1891 document on labor rights during the Industrial Revolution - the message being that unchecked technological power always concentrates in the wrong hands.

TechCrunch makes an interesting observation: the encyclical isn't really just about AI. It's using AI as a lens to diagnose older problems - concentrated power, eroding democracy, and a tech elite reshaping the world on its own terms. Whether you're religious or not, that framing is hard to dismiss. The document lands at a moment when questions about AI regulation and technology ethics are dominating policy conversations worldwide.

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This one is worth paying attention to if you work inside a company that's been told to "go all-in on AI." Uber president Andrew Macdonald confirmed this week that the company reportedly exhausted its entire annual AI budget by April 2026 - just four months into the year. And his assessment of what they got for it is remarkably candid.

Macdonald told Rapid Response that it's "hard to draw a line" between AI spending and deliverable features. That's a striking admission from a company of Uber's scale - and it's probably the most honest thing a tech executive has said about enterprise AI investment this year. Uber isn't alone. Across the industry, companies are pouring enormous sums into AI tools and infrastructure while struggling to quantify returns in any concrete way.

The pattern matters because Uber is a data-driven company with the resources to measure almost anything. If they can't draw the line between spend and output, smaller companies trying to do the same calculation probably can't either. It's a useful gut-check at a moment when AI investment is being treated as a default competitive necessity rather than a deliberate strategic choice.

Speaking of building with AI - if you're spinning up a project and need a website fast, 60sec.site lets you build one with AI in under a minute. Worth bookmarking.

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Everyone's arguing about whether AI is killing jobs. MIT Technology Review says the debate is missing the point entirely. The headline unemployment numbers look fine - but something structural is breaking underneath them, quietly and quickly.

MIT's analysis identifies a specific and serious problem: the "quiet weakening of the first rung of the career ladder." Entry-level white-collar positions - the jobs that used to train the next generation of analysts, lawyers, coders, and researchers - are the ones most exposed to AI automation right now. And they're shrinking faster than the aggregate data can capture.

This connects directly to what we're hearing from recent graduates. The Guardian spoke with students who booed pro-AI commencement speakers at their graduations this spring - not because they're anti-technology, but because they're watching the entry points into their chosen fields close off in real time. Jacob Pagel, graduating from Middle Tennessee State University, put it simply: he was already questioning the value of his degree before the speaker even started talking about AI's "transformative power."

The future of work conversation has been dominated by fears about mid-career disruption. MIT's argument is that we should be just as worried about what happens when people can't get their careers started in the first place. No junior roles means no pipeline - and no pipeline means the expertise gap widens over time, not shrinks.

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Wired published what they're calling the definitive account of how Claude Code, OpenClaw, and a wave of AI agents kicked off what may be computing's biggest transformation in decades. The headline framing - "plunged the tech world into chaos" - isn't hyperbole. It's a description of what happens when tools that can autonomously write, run, and debug code get put in the hands of millions of developers simultaneously.

The shift from "AI that helps you code" to "AI that codes while you watch" happened faster than most companies could prepare for. Wired traces how coding agents went from novelty to standard practice inside engineering teams, and what got broken in the process - version control assumptions, security models, review workflows, and the basic mental model of what a "developer" actually does.

This pairs interestingly with the entry-level jobs story above. If agents are handling the work that junior engineers used to do, the MIT concern becomes even sharper - not just fewer entry-level jobs, but potentially fewer humans who ever develop the deep skills those agents are currently drawing on. Worth sitting with that one for a moment.

For more on how AI is reshaping the job market, we've been covering this closely at Daily Inference.

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Documents obtained by Wired show that US law enforcement is actively tracking a new category of threat: organized hostility toward AI infrastructure, data centers, and technology companies. The FBI and DHS have reportedly begun flagging what they're calling "anti-tech extremism" as public anxiety over job displacement and surveillance grows.

The concern isn't just online rhetoric. Authorities are watching for potential physical threats against data centers - the very facilities powering AI systems that millions of Americans associate with economic disruption. It's a sobering reminder that the debate about AI's social costs isn't purely abstract. Real frustration, building over years of job market anxiety and eroded trust, is starting to find physical expression.

This is a story worth watching for AI infrastructure and public policy implications. The tension between rapid AI deployment and the communities bearing the costs is not going away.

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The answer is 'Magnificent Humanity'! 'Magnifica Humanitas' translates directly as 'Magnificent Humanity' - which is a pretty clear statement of intent from a document arguing that human dignity must remain central even as AI systems become more capable and pervasive.

The entry-level jobs story from MIT really stuck with me today. So here's my question for you: if you're early in your career (or managing people who are), have you noticed AI closing off the "training ground" roles that used to be the starting point? Hit reply and tell me what you're seeing - I genuinely read every response, and this one feels important to understand from the ground level.

That's all for today. A lot to sit with - from the Vatican to Silicon Valley to your graduation ceremony. See you tomorrow with more. And if you want to catch up on anything we've covered recently, the full archive is at dailyinference.com.