A week in AI is like a year in other industries. I hope these issues become your weekly source of AI information, inspiration, and ideas.
Good morning. Six things I read and listened to in the past few days that I haven’t stopped thinking about.
🤝 This edition is kindly brought to you by Miro
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Here’s the uncomfortable part of cheaper AI models that nobody really talks about: when inference gets cheaper, your customers can build a version of your product for less than it costs to buy yours. The a16z team lays out what that actually means for every AI company trying to hold a price.
94% of enterprise buyers expect their AI spend to go up. 37% expect it to at least double within a year. The money is coming. The question is who keeps it.
“Growth is becoming an engineering problem.” That’s the first line, and everything after earns it.
Anita Kirkovska writes about what it actually looks like to run marketing at scale with agents. Comparison articles hitting tens of thousands of views in a day. Personalized onboarding that pushed day-one activation from 27.5% to 37.4%. An automated leaderboard that drove half the company’s traffic in a year. She also covers the mistake: scaling creators before they actually understood the product. Specific, honest, practical.
On a podcast last week, the OpenAI CEO said it’s “quite terrible” that people have RAM sitting in personal computers when data centers don’t have enough of it. His argument is utilization — a data center runs near 100%, your laptop doesn’t.
The internet reacted the way the internet reacts. I’ll leave the discourse there.
What I’ll say is this: the gap between how the people building AI infrastructure think about resources and how everyone else experiences them is getting wider, not narrower. Worth noticing.
Revenue up 47% from Q2. Operating loss back up too. IPO coming.
This is the AI story that doesn’t get told as loudly as the growth numbers. The business is working. The losses are also working. At some point those two lines have to cross, and whoever figures that out first wins something the others don’t.
Alex Davis just raised a $10 billion fund. His firm, Disruptive, has 30 people and has stayed out of the spotlight until now. He’s planning around 10 investments, with checks up to $1 billion each. His track record: $6 billion returned on $2 billion invested, with early bets on Palantir, Airbnb, and Spotify, and recent ones on ElevenLabs, Databricks, and Reflection AI.
He’s also running Groq as executive chairman. And in his first ever podcast interview, he said something I want more people to hear: he predicts real pain for the wave of developers borrowing heavily to build data centers without understanding the financing or the chip economics. “I could see a lot of people getting hurt putting a lot of debt on these projects.”
He also said: “I don’t want an AI culture.” He expects his team to use the tools. He won’t shrink the firm because of them.
Worth an hour of your time.
Anthropic just opened a paid research residency for people with strong technical skills who have never worked in AI safety. No ML background required — they train you on the job.
Placements run 6 weeks to 6 months. Pay is $350K to $500K annualized. You get a mentor, GPU compute, and access to Claude models. Research areas include interpretability, AI control, and red-teaming.
Applications close November 22.
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