Good morning, {{ first_name | AI enthusiasts }}. Religious institutions don’t usually weigh in on AI. But the world’s largest just did — in nearly 42,000 words.
Pope Leo XIV just published his first encyclical, one of the highest forms of papal teaching, drawing a direct line between today’s AI revolution and the Industrial Revolution, and making clear the Catholic Church intends to be a moral voice in how the tech develops.
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The Pope’s 42,000-word verdict on AI
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Meta and Google AI ‘decensored’ in minutes
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Turn any case study into a client-ready video
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Uber’s COO says AI cost is ‘hard to justify’
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4 new AI tools, community workflows, and more
POPE ON AI
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The Rundown: Pope Leo XIV just released Magnifica Humanitas, his first encyclical, to the Church’s 1.4B members, warning that a moral AI means nothing “if that morality is determined by a few” and calling to “disarm” the tech before it dominates humanity.
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Leo warned that AI’s drivers are private, transnational companies that already surpass the capacity of many governments, and that the tech is never neutral.
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He called for making AI “human-friendly” and freeing it from monopolistic control, warning it risks reducing people to cogs in an efficiency machine.
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Leo called for “robust legal frameworks, independent oversight, informed users, and a political system that does not abdicate its responsibility.”
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On warfare, he said lethal decisions must never be delegated to AI and that “no algorithm can make war morally acceptable.”
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Anthropic’s Christopher Olah also joined the Pope, saying “every frontier AI lab operates inside incentives that can conflict with doing the right thing.”
Why it matters: The Pope issues only a handful of encyclicals, and dedicating one to AI signals how seriously the Catholic Church is taking what’s coming. Leo sees AI as the Industrial Revolution of our time, and he’s chosen a partner that has been the most vocal about AI safety and most willing to say no to unrestricted AI use by the military.
TOGETHER WITH YOU.COM
The Rundown: LLMs hallucinate. Grounding gives them a factual anchor — and the accuracy gains are significant. In this guide, You.com breaks down what AI grounding actually is and how teams can implement it to get outputs they can trust.
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A three-part approach that outperforms RAG alone
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Why grounding isn’t set-and-forget, and how to build audit trails
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The open vs. closed platform trade-off (and what it means for your next model switch)
AI SAFETY
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The Rundown: FT just revealed that tools capable of removing guardrails from open-source AI are generating thousands of “decensored” models, with modified Meta and Google models found answering questions on bioweapons and child exploitation.
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FT removed guardrails from Llama 3.3 in 10 minutes, using a tool called Heretic (available on GitHub), four lines of code, and no specialist hardware.
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The model provided answers to harmful questions, including those about ricin dosage. A modified Gemma 3 also answered dangerous questions.
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Heretic’s creator said the tool has produced 3.5K+ decensored models, downloaded 13M times, and he stripped Gemma 4 within 90 minutes of release.
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Google called it “a known technical challenge facing all open models.” Meta, meanwhile, declined to comment.
Why it matters: While the technique only works on open-source models exposing their code, and proprietary systems remain safe, the bigger question remains: for how long? Open models have been closing the gap with closed systems, and it’s just months before they’re at this level — at which point, a decensored version could be a major risk.
AI TRAINING
The Rundown: In this guide, you will learn how to turn a written case study into a two-minute video for your team, complete with an AI narrator, B-roll, and animations.
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Prepare a case study as a text/PDF file, go to Synthesia in Chrome, click Start with Assistant, choose a 1- or 2-minute video, and attach the case study file
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Prompt: “Turn this case study into a 1–2 minute video for [AUDIENCE]. The topic is [TOPIC]. The objective is [OBJECTIVE]. Preserve the facts, metrics, and quote exactly”
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Select a visual style, then click Create Video. You will get back an outline with several 10- to 20-second scenes and their accompanying scripts
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Proofread scenes or tweak music, background visuals, and AI avatar, and then click Generate. Export as .mp4 when the video is ready (usually 10–15 minutes)
Pro tip: To make the video specific to a prospect, write a quick client background or project proposal and upload it with the case study.
PRESENTED BY FIDDLER
The Rundown: External LLM evaluation charges you per API call and increases as you scale. If you try to control spend with reduced sampling, you risk incidents slipping through undetected. Fiddler Centor Models run evals in your own infrastructure with no per-call costs, reducing your evaluation Total Cost of Ownership as you scale.
Put in your numbers to see:
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Your annual eval cost across GPT, Claude, and Gemini models at your trace volume
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How each evaluator you add increases your per-trace spend
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How your evaluation costs curves shift as agent traffic grows
UBER
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The Rundown: Uber’s COO Andrew Macdonald said in an interview with Rapid Response that it’s getting harder to justify the company’s AI spending as higher AI activity isn’t necessarily translating into proportional gains.
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Macdonald said it’s very hard to draw a direct link between higher token usage, often touted as “tokenmaxxing,” and shipping more useful consumer features.
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Without that connection, Macdonald said the costs are becoming hard to justify, especially as Uber has been slowing hiring to fund AI investments.
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The issue came to light after Uber’s CTO commented on burning Claude Code budget, sparking an internal debate about token usage and trade-offs.
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Macdonald also touched on autonomy, calling it “existential” for Uber — predicting it won’t take decades, but also won’t happen in a couple of years.
Why it matters: Big Tech is pushing tokenmaxxing and tying AI usage to performance reviews. But Macdonald’s comments signal that some are starting to ask whether AI spend is actually moving the needle everywhere. Duolingo also stopped evaluating performance based on AI usage, signaling a more balanced approach to work.
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🤖 Codex – OpenAI’s agentic coding assistant with a new Locked Use mode
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🧠 Manus – Meta’s agentic AI assistant, now with Projects on mobile
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💻 Supercomputer – Higgsfield’s agentic AI for video, with social connectors
Microsoft Azure’s Copilot Migration Agent turns complex migration data into clear answers using natural language prompts. Read the whitepaper.*
Anthropic’s Chris Olah said at the Vatican that researchers are seeing mysterious things in AI, including “introspection” and states resembling joy, fear, grief, and unease.
xAI launched Grok Build, its rival to Codex and Claude Code, in beta, making it available to all SuperGrok and X Premium+ users.
Elon Musk confirmed on X that Grok V9-Medium (1.5T) foundation model has finished training, with evals looking good and a public release likely in two to three weeks.
Anthropic’s Mythos model was briefly spotted inside Claude tools as “Mythos 1” and “claude-mythos-1-preview,” fueling speculation that a public release may be nearing.
Goldman Sachs CEO David Solomon argued in a New York Times op-ed that AI will create more opportunities than it destroys, dismissing fears of mass unemployment.
Every newsletter, we showcase how a reader is using AI to work smarter, save time, or make life easier.
Today’s workflow comes from reader Patrick in Yuma, AZ:
“As a senior who has been taking various medications for years, who keeps reviewing various Facebook reels proclaiming wondrous results from ingesting several different natural substances (mainly at high costs), I decided I should venture out and try a couple of these wondrous solutions. However, before doing so, I created a list of pertinent questions regarding actual results, drug interactions, and product comparisons leading to recommendations for my personal situation.
I ran the prompt through 3 different LLMs and reviewed their responses. In the end, the responses provided considerable pertinent information and assisted me in making a well-informed decision.”
How do you use AI? Tell us here.
That’s it for today!
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Rowan, Joey, Zach, Shubham, and Jennifer — the humans behind The Rundown
