Welcome back to This Week in Stratechery!
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On that note, here were a few of our favorites this week.
- What We Learned from Big Tech’s First Quarter. Apple, Amazon, Meta, Google and Microsoft all reported earnings last week, and as four of the five megacaps continue to pour massive sums into AI (first quarter CapEx was more than three times that of the Manhattan Project), there are no signs of that pace slowing. Ben broke it all down across several days, including divergent market reactions to great Google numbers and Meta numbers that were arguably even better, as well as the stories for Microsoft and Apple after Q1. Sandwiched between those Daily Updates, Tuesday’s Article zoomed out to connect Amazon’s infrastructure spending history with its AI strategy going forward. All of it was a great way to parse numbers that continue to boggle the mind, and strategy that actually looks a lot more rational than the numbers sound. — Andrew Sharp
- A Conversation with Joanna Stern. How does one write a book about a tech story that seems to change every other week? Joanna Stern accepted that challenge, and explained how it went in this week’s Stratechery Interview. The resulting conversation is a delightful glimpse into the process for one of the most creative tech writers alive and the making of a book that Ben loved. Stern’s shares her thoughts on using an LLM to make a career change, as well as how AI is changing medicine (and mammograms), and limits of LLMs that are still very real. To the latter point, if you’d like to learn more about how ChatGPT misdiagnosed a preying mantis pregnancy, start with this week’s interview, and then you can buy the book here. — AS
- What’s Next for the Celtics? Like many others across the media, I picked the Boston Celtics to make the NBA Finals in June. Alas, they barely made it out of April and were eliminated in the first round to Joel Embiid and the 76ers. The GOAT podcast recapped that disaster first on Monday with a salute to the Sixers (now bittersweet after two losses to the Knicks), and on Thursday’s episode, a longer look at the mess in Boston and a variety of thorny choices from here. Get caught up on all of that and the rest of Playoffs, and if you need an additional hoops fix, this week’s Sharp Text is a salute to the maddening charms of the Minnesota Timberwolves. — AS
Stratechery Articles and Updates
- Google Earnings, Meta Earnings — Wall Street loved Google’s earnings, and hated Meta’s, even though the latter’s core business was more impressive. The difference is that Google is monetizing its investments now (and it might be all Anthropic).
- Amazon’s Durability — Amazon looked behind in AI in the training era, but is well place in the inference era, thanks to its continued investment in the long-term.
- Microsoft Earnings, Apple Earnings — Microsoft unveils its new agentic business model, and Apple confronts shortages in memory and chips even as the Mac benefits from AI.
- An Interview with Joanna Stern About Living With AI — An interview with Joanna Stern about her new book about living with AI, and starting her own media company.
Sharp Text by Andrew Sharp
- The Wolves Are Why We Do This — A salute to the playoff Timberwolves. Plus: Notes on Vogue history, NBA upheaval, and the “geo” in geopolitics.
Dithering with Ben Thompson and Daring Fireball’s John Gruber
Asianometry with Jon Yu
Greatest of All Talk with Andrew Sharp and Ben Golliver
- The Sixers Get Their Moment in the Sun, A Nightmare for Celtics Fans, Thoughts on the Way Into the Second Round
- A Championship Response from the Spurs, What’s Next for the Celtics?, Pre-Lottery Thoughts and Emotions
This week’s Sharp Tech video is on Messaging AI in 2026.
Facts Only
Executive Summary
Full Take
The narrative presents a constant tension between exponential technological investment and the market's ability to rationally price or react to those shifts. The sheer scale of AI CapEx, compared to historical benchmarks, serves as a foundational fact, yet the context provided is mostly focused on divergent company earnings and specific, often anecdotal, interviews about the *experience* of AI rather than the structural mechanisms driving these investments. This framing risks obscuring the systemic implications of resource allocation and regulatory friction inherent in this accelerated pace of change. The inclusion of highly specific, sometimes sensational, anecdotes (e.g., ChatGPT misdiagnosing a pregnancy) alongside high-level strategic analysis creates an aesthetic of high-stakes uncertainty. The pattern suggests an attempt to leverage the public's fascination with AI's potential and risk to generate engagement, often sacrificing rigorous, systemic analysis for immediate, digestible narratives.
Patterns detected: ARC-0043 Motte-and-Bailey, ARC-0024 Ambiguity
Implications: The focus on divergent market reactions and speculative AI claims suggests a pattern where the complexity of technological shifts is simplified into polarized narratives of success and failure, potentially distracting from the foundational, long-term operational costs and societal consequences of these massive, unconstrained investments.
Bridge Questions: What is the quantifiable impact of the reported AI CapEx on the broader economic ecosystem outside of the reporting companies? How do the reported differences in earnings between Google and Meta reflect fundamental differences in monetization strategy versus core business operations? What is the systemic risk introduced by using highly anecdotal examples to contextualize complex scientific and ethical discussions about LLMs?
Sentinel — Human
The text exhibits strong human characteristics, presenting as a curated editorial newsletter with a distinct voice and specific, nuanced references.