Good morning, {{ first_name | AI enthusiasts }}, and welcome to our 9,436 new readers. Last week, industry insiders were warning that AI could kill us all. This week, the conversation has shifted to slowing it down.
Anthropic CEO Dario Amodei just published an essay making the case for deliberately pacing AI development… and in a rare show of unity, some of his biggest rivals — OpenAI included — have agreed.
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Dario Amodei makes the case for AI slowdown
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The Rundown Roundtable: Our AI use cases
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Send a one-page proposal minutes after sales calls
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AI helps catch more fetal brain defects in hospitals
AI SLOWDOWN
Image source: X / The Rundown
The Rundown: Anthropic CEO Dario Amodei is known for sprawling essays, and in his latest, he has called on AI labs to slow the rate of capability gains so safety can catch up, citing recursive self-improvement of models as the core reason of concern.
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Amodei said AI is now speeding its own development, and in 6–12 months, a swarm of agents could be capable of taking over the entire internet.
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For pacing, he proposed embedding third-party evaluators inside labs, plus safety standards among democratic labs and coordination with authoritarian regimes.
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Fellow leaders agreed, with Sam Altman committing to evaluators, Musk saying “Dario is right,” and Demis Hassabis and Satya Nadella backing the direction.
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Trump dismissed slowdown advocates as “negative forces” pushing “things that won’t happen,” noting the U.S. should keep its lead since “whoever wins AI wins.”
Why it matters: This rare show of unity, alongside recent leaps in math and warnings from researchers, hints that these labs’ unreleased models may be showing capabilities like never before. Slowing the pace won’t be simple, though, given that some want open development, some call it regulatory capture, and others don’t want to slow down at all.
TOGETHER WITH ORACLE
The Rundown: LinkedIn just replaced its AI writing button with one to report AI slop instead. AI doesn’t sound like you because it writes from zero every time. Authentic writing is built on three kinds of memory.
In this blog, you’ll find:
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Reflection loops that adjust style over time
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Code and the notebook to build AI that sounds like you
THE RUNDOWN ROUNDTABLE
Darren, Director of Media: I built an AI story-scouting workflow to find potentially viral stories for Instagram, YouTube, and TikTok without recycling topics we’ve covered.
First, the workflow reviewed Rowan’s public short-form archive to create a coverage map of past topics and editorial taste. It uses that map as a filter to distinguish a new angle from another version of the same AI launch, robot demo, or research story.
Every morning, it scans priority sources, including AI and technology coverage from major newspapers and tech blogs, The Rundown newsletters, company announcements, research papers, and updates from major AI and robotics companies.
Each potential story is checked for four things: a clear visual hook, a technical idea that can be explained in 45–90 seconds, broad audience interest, and meaningful novelty compared with Rowan’s past coverage and the previous week’s recommendations. It keeps every story that clears the bar rather than forcing a fixed number.
The final brief is ranked by strength and sent as one compact Slack DM each morning.
Kenny, Head of Sales: I built a running coach with Claude.
After years of using apps to track runs, I wanted something closer to an actual coach instead of just a collection of data points. I opened a Claude Project, connected it to Google Calendar, and gave it standing instructions with real guardrails.
It has been my coach for the last six months and has helped me avoid injury while increasing my monthly mileage. It plans my week, logs every run from my watch data, catches when I’m ramping up too quickly, tracks how close my shoes are to retirement, and rewrites my calendar when life disrupts my plans.
AI DIAGNOSIS
Image source: Images 2.5 / The Rundown
The Rundown: A randomized trial across five Chinese hospitals just found that giving sonographers an AI assistant during live prenatal ultrasounds raised their detection of specific fetal brain malformations, without more false alarms.
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The trial, one of the first tests covering AI in the scanning room, used PAICS, a deep-learning AI trained to flag 10 specific fetal brain malformations in real time.
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With PAICS, sonographers’ detection sensitivity rose from 78.6% to 87.3%, with the gains holding across most subgroups and false positives staying steady.
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Human involvement played a key role, as PAICS alone often scored worse than the assisted sonographer, who correctly overrode about 60% of its mistakes.
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The trial covered only high-risk pregnancies and brain malformations, ran entirely in China, and AI-assisted scans also took ~40 seconds longer than regular scans.
Why it matters: While the AI conversation fixates on risk, its role in healthcare keeps advancing — especially in detection — helping teams catch problems earlier and get patients care sooner. This trial shows another useful shape of it, with AI serving as a second set of eyes (not a replacement) working alongside humans.
COMMUNITY AI WORKFLOW OF THE DAY
▸ Thy built an AI gardening app with climate zone tracking
Today’s workflow comes from reader Thy Toeung:
“What do you do when your wife says you talk about AI too much? You listen to her, and when she has a problem, you frantically write it down and build it with AI.
My wife enjoys working with her plants. She’s new to gardening and is learning each day, but was having trouble keeping track of everything. Which tree did she plant in the front yard last year? It seemed to be struggling — would it do better somewhere else? And would rain reach the potted flowering planters while we were out of town, or would she need someone to help?
I used Claude Code and Fable to develop an app that my wife could run on her phone, with all the data stored locally. Now she’s excited about ‘her app’ and the things she can add to it. She has even shared it with others, including people across the country, so we added climate zone settings to make it useful in other parts of the country.”
OpenAI CEO Sam Altman told Fortune that the company won’t IPO in 2026, saying right now would be an “ill-advised moment” to go public, given the AI safety concerns.
25 Fields Medalists signed a declaration warning that AI’s race to solve math problems is sacrificing understanding, attribution, and the human process that advances the field.
The Pentagon is considering a $5B loan to AI cloud startup Fluidstack to strengthen U.S. manufacturing and supply chains for data-center components, WSJ reported.
At the BRICS Summit in New Delhi, China proposed an open-source AI community to support shared AI development, training, and industrial use across member nations.
Anthropic and Google DeepMind’s AI safety researchers Joe Benton and Josh Engels resigned to join METR Evals, with both warning that AI capabilities are outpacing safety.