2026.32: Earnings and Learnings

2026.32: Earnings and Learnings

(Photo by Ethan Miller/Getty Images) Welcome back to This Week in Stratechery! As a reminder, each week, every Friday, we’re sending out this overview of content in the Stratechery bundle; highlighted links are free for everyone. Additionally, you have complete control over what we send to you. If you don’t want to receive This Week in Stratechery emails (there is no podcast), please uncheck the box in your delivery settings. On that note, here were a few of our favorites this week. Earnings Exposure. From a content perspective, earnings can be overwhelming, especially when they all drop on the same day. Sometimes, however, the juxtaposition is clarifying. That’s exactly how I felt this quarter: Meta, Microsoft, Amazon and Google are all spending astronomical amounts of money building infrastructure from AI. Wall Street’s reaction, however, differed markedly, based on the cost of the frontier (or not), the potential for immediate monetization (or not), and the clarity of vision (or not). We tied all of these strings together on an in-person episode of Sharp Tech. — Ben Thompson OpenAI’s Answer to Apple. Last month Apple sued OpenAI and alleged that hardware chief Tang Tan, along with other Apple vets in the OpenAI hardware division (but not Jony Ive!), had stolen trade secrets as part of the company’s efforts to develop competing devices. Ben covered the initial complaint well with an Update in mid-July; this week, though, OpenAI told its side of the story and presented evidence that undermines Apple’s narrative. I loved Thursday’s Dithering episode reiterating the implications of Apple’s arguments for the tech ecosystem and and the stakes of all this that are easy to forget: Apple, by the terms of its own lawsuit, is trying to kill OpenAI’s hardware division. — Andrew Sharp All About LeBron in Philly. As you’ve probably heard by now, LeBron James stunned the NBA two weeks ago when he announced he’d be joining the 76ers. Next to a slew of underwhelming free agency options, he chose a team that will present him with young and old personalities to manage, on-court chemistry questions to answer, genuine Finals upside, as well as some wonderful downside potential in a city that’s internationally renowned for booing. We hit all of it on Greatest of All Talk: first with an emergency episode that we recorded two weeks ago (you can hear our disbelief an hour after the news broke), and then with a longer, 45-minute discussion this week. Two weeks later, I’m still shocked we’re here, and thrilled as a basketball podcaster. — AS Stratechery Articles and Updates Meta Earnings, Meta’s Timing Problems, The Financial Tail — Meta’s earnings were a bit disappointing; future promises about AI products were more disconcerting. Microsoft Earnings, Microsoft vs. Meta, The Efficiency Payoff — Microsoft’s earnings were compelling because they showed a clarity of strategy, lower costs, and a tangibility of application. The reason why is scarier. Google Earnings, The Frontier Case, Amazon Earnings — Google’s earnings seemed to confirm the Anthropic hedge; it was Andy Jassy who explained why their — and Amazon’s — capex was justifiable. Dithering with Ben Thompson and Daring Fireball’s John Gruber Vibe-Porting and Meta Enterprise OpenAI Responds Asianometry with Jon Yu ADSL Made the Modern Internet Possible Sharp China with Andrew Sharp and Sinocism’s Bill Bishop A Memory-Maker Makes History; New Robot Rules; The Open Weights Debate Rages; End of July News and Notes Greatest of All Talk Six More Questions on LeBron in Philly, Revisiting the 2016 Draft, The Top 5 Dinosaurs Sharp Tech with Andrew Sharp and Ben Thompson Microsoft’s Plan for Platform Survival, Meta and the Market’s Permission, A Lack of Situational Awareness This week’s Stratechery video is on Who’s Afraid of Chinese Models?.

Original Source

Read the full article at Stratechery →

KhanList aggregates and links to publicly available news content. We do not host full articles from third-party sources. Always verify important information with original sources.