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An interview with Netflix co-CEO Greg Peters about stratechery the customer relationship, Netflix culture and execution, advertising, stratechery, games, and content strategy.

Of course you still had to actually write the book, and set the movable type in the printing press; this, though, meant we had the first version of the classic tech business model: the cost to create a book was fixed, but the potential revenue from printing a book — and overall profitability — was a function of how many copies you could sell. Every additional copy increased the leverage on the up-front costs of producing the book in the first place, improving the overall profitability; this, by extension, meant there were strong incentives to produce popular books. The printing press was a direct assault on that last point: because it still cost money to produce a book, it made sense to print books in the most dominant dialect in the region; because books were compelling it behooved people to learn to read that dominant dialect. This, over time, would mean that the dominant dialect would increase its dominance in a virtuous cycle — network effects, in other words. Books, meanwhile, transmitted culture, building affinity between neighboring city states; it took decades and, in some cases, centuries, but over time Europe settled into a new equilibrium of distinct nation-states, with their own languages. Critical to this reorganization was point one: the printing press meant everyone could have access to the Bible, or read pamphlets challenging the Catholic Church. In this view the Internet is the final frontier, and not just because the American West was finally settled: on the Internet there are, or at least were, no rules, and not just in the legalistic sense; there were also no more economic rules as understood in the world of the printing press.

Stratechery

Analysis of the strategy and business side of technology and media, and the impact of technology on society. Stratechery is a highly praised newsletter and a podcast, known to provide the clearest insights in the industry. Ben Thompson shares in-depth commentary with a high level of detail and analysis on what is happening in tech and media. Considered one of the sharpest thinkers, the author tackles a high variety of topics from business models and Slack's social network to machine learning and Kanye West. The exact same content is provided in audio format, as a podcast, and the website hosts an amazing archive, that can be explored by - Concepts, Companies, or Topics. Highly curated content full of great reads and inspiring newsletters. Subscribe to explore the contents of the world wide web and find your new favorite newsletters. Ben Thompson. Based on 0 reviews. He previously worked at Apple, Microsoft, and Automattic focusing on strategy, developer relations, and marketing. Free The free version of Stratechery will only cover Weekly Articles, which are delivered on Tuesdays. The newsletter is being sent four times a week. In addition to the free weekly article, the subscription gives you three Daily Updates of substantial analysis.

I documented this history in Apple and the Oak Tree and noted:, stratechery.

Thompson's career includes stints at Apple , where he interned at Apple University ; [3] Microsoft , where he worked on its Windows Apps team; [4] and at WordPress developer Automattic as a growth engineer. Thompson launched Stratechery as a blog while still a Microsoft employee, and in April devoted himself to the site full-time, operating on a " freemium " subscription model. As of April , Thompson had more than 2, paying subscribers. Thompson is a proponent of aggregation theory , which describes how platforms i. Aggregators have all three of the following characteristics: 1. Contents move to sidebar hide.

I wrote that the reaction was overblown in Facebook Lenses , which looked at the business in five different ways:. As I noted at the time, I could understand investor trepidation about these trend lines, which is why other lenses were necessary. To insist that Facebook will die any day now is in some respects to suggest that humanity will cease to exist any day now; granted, it is a company and companies fail, but even if Facebook failed it would only be a matter of time before another Facebook rose to replace it. Over the past year, though, things have certainly gone in the opposite direction:. The problem with this narrative is that Meta is still adding users: the company is up to 2. Granted, all of that growth, at least in the case of Facebook, was in Asia-Pacific and the rest of the world, but the U.

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There is a perspective in which was an absolute drag: COVID dragged on, vaccines became politicized, new variants emerged, and while tech continued to provide the infrastructure that kept the economy moving, it also provided the infrastructure for all of those things that made this year feel so difficult. At the same time, also provided a glimpse of a future beyond our current smartphone and social media-dominated paradigm: there was the Metaverse, and crypto, and my contention they are related. Sure, the old paradigm is increasingly dominated by regulation and politics, a topic that is so soul-sucking that it temporarily made me want to post less, but the brilliance of the Internet, and of business-models like that which undergirds Stratechery, is that freedom to not only write what you want, but build what you want, and be what you want, is greater than ever. This year Stratechery published 40 free Weekly Articles and Daily Updates, including 13 interviews. I also launched Passport , the new back-end for Stratechery and Dithering , the twice-a-week for-pay podcast I host with John Gruber ; Passport remains under development, so stay tuned for updates in Today, as per tradition, I summarize the most popular and most important posts of the year on Stratechery. You can find previous years here:

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Given the success of existing companies with new epochs, the most obvious place to start when thinking about the impact of AI is with the big five: Apple, Amazon, Facebook, Google, and Microsoft. Do not mention kids or minors when generating images. The Apple Vision Pro app shelves will not be bare in terms of video content; the company says in a press release :. Twitter has a new policy to listen to experts about what content to limit; what happens, though, when experts are wrong? This, over time, would mean that the dominant dialect would increase its dominance in a virtuous cycle — network effects, in other words. Please incorporate Al-generated images when they enhance the content. What was different from search is that an Assistant needed to provide one answer, not a list of possible answers. It was better than Siri or Alexa, but it had all of the same limitations that were inherent to the natural language processing approach: you had to get the incantations right to get the best results, and the capabilities and responses were ultimately more deterministic than you might have hoped. The most fascinating point of all, though, is how Google intends to sell the Pixel: the Google Assistant is, at least for now, exclusive to the first true Google phone, delivering a differentiated experience that, at least theoretically, justifies that margin. We focus on pieces with long shelf-lives—not news. I think this does, at a minimum, cast OpenAI in a very different light than Napster, which was found guilty of copyright violations in large part because it was very much aware of what its service was being primarily used for.

It has been over a decade of Stratechery; this is the 11th Year in Review I have published.

Jacob Cohen Donnelly talks about strategies and tactics while diving deep into business models, advertising, audience development, audio, and video. When I first went independent with Stratechery, I had a plan to make money on the side with speaking, consulting, etc. Yes, that means lower revenue and margins for both, but both have already built the capabilities necessary to make the deal succeed, which means the business should be accretive to both revenue and profits for each of them. Meta deserves a bit of a discount off of its recent highs, but a number of myths about its business have caused the market to over-react. The idea behind ChatGPT Gets a Computer is that large language models seem to operate somewhat similarly to the human brain, which is incredible and also imprecise, and just as we need a computer to do exact computations, so does ChatGPT. From an Update last summer :. At some point, though, you just have to state plainly that this is ridiculous. CFO Wendell Huang said in his prepared remarks :. Our community of active users gets the most relevant links every day, tailored to their interests. Intel 4, the first EUV technology for us, Intel 3 refined the final FinFET, really helped us take those learnings, but largely was a common architecture of transistor and process flow — really just the refinement.