Andrew Maddox

Category: Business

  • Various (AI) Links (Oct. 31)

  • Tuesday Links (Oct. 28)

  • Monday links (Oct. 27)

  • Sunday Links (Oct. 26)

  • Work Life Balance

    Yesterday, I saw this NYTimes story about LendingTree’s CEO sudden and accidental death.

    He was the founder and longtime CEO of the company. He was a multimillionaire and a vital part of the company’s leadership team. Yet the lede of the story implied how irreplaceable he was:

    LendingTree named its chief operating officer, Scott Peyree, as its new chief.

    So yes, folks, even the most important of corporate officers can be replaced mere hours after an accident. It reminds me that the most important things in life happen not at work (where you can be replaced at will) but at home and with your family. I doubt that his wife has already named his replacement.

  • Tuesday Links (Oct. 7)

  • AI Pricing Trends

    When Disney launched Disney+ in 2020, it came to market with a really low price: $6.99 per month. The strategy was obvious—use a bargain price to quickly build a subscriber base and compete with Netflix.

    It worked. Families eagerly added Disney+ to their lineup of streaming services, drawn by its deep library of shows and movies. But as the platform grew, investors started pushing Disney to make the service profitable. Over the next few years, Disney steadily raised prices. Today, the ad-free tier costs nearly three times what it did at launch.

    This story isn’t just about streaming. It’s a preview of what’s coming with AI services.

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    The $20 Benchmark for AI

    When OpenAI launched ChatGPT Plus at $20 a month, it wasn’t the product of intricate economic modeling. Instead, it reflected an attempt to recoup some of the enormous costs behind the scenes—training models, running massive server farms, and paying world-class researchers.

    That $20 price point quickly became the de facto benchmark for consumer-facing AI tools, with Anthropic and others adopting similar rates.

    But OpenAI has been clear that its ambitions go far beyond the current offering. Its Stargate initiative involves building massive infrastructure, partnering globally, and spending billions on data centers. At some point, investor money won’t be enough—they’ll need sustainable revenue.

    And just like Disney, the path is clear: grow the subscriber base, then gradually raise prices once users view the product as indispensable.

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    The Coming Price Climb

    Right now, $20 a month feels reasonable. But look ahead 5–10 years. As AI capabilities expand, it’s easy to imagine prices climbing to $50, $60, or even $100 per month.

    For individual consumers, that may be tough to swallow. A household with multiple subscriptions could find itself spending several hundred dollars a month on AI tools.

    For businesses, however, the math looks different. If AI can make an employee just 10% more productive, the return on investment is obvious. An employee earning $60,000 annually who produces the equivalent of $66,000 in value thanks to AI easily justifies a $100 subscription. For programmers or knowledge workers achieving productivity gains of 50% or more, companies might begrudgingly pay hundreds—even thousands—per employee, per month.

    The economics are compelling, and the pressure to raise prices is certain.

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    AI-Adjacent Tools Will Follow

    This dynamic won’t be limited to large language models. AI-adjacent tools—platforms like Jira or Siteimprove—are racing to integrate AI features into their products. The added capabilities will deepen customer reliance. But once the early adoption phase passes, I expect these vendors to raise prices as well.

    It’s the same playbook: demonstrate new value, increase lock-in, then adjust pricing upward.

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    The Staffing Equation

    All of this has implications beyond budgets. If AI makes employees 50% more efficient, organizations will rethink staffing structures. Efficiency gains don’t automatically translate into cost savings unless roles are consolidated or organizations grow.

    Take three departments, each with a similar role. If AI tools boost each person’s productivity by 50%, the organization suddenly has capacity for 4.5 units of work when only three are needed. The logical response is to reduce headcount—perhaps to two positions covering all three departments. But that requires some degree of centralization to realize these gains. Better options include company growth or redeploying personnel in areas of need or opportunity. There will be disruption of the workforce, but it doesn’t have to lead to layoffs.

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    Planning for the Future

    The lesson from Disney+ is clear: early low prices are temporary. AI services are following the same trajectory, and organizations should prepare now.

    • Expect rising subscription costs—both for core AI platforms and for AI-enhanced tools.
    • Budget for increases of 50% or more annually over the next few years.
    • Plan staffing structures to capture the efficiency gains AI makes possible. I’m sure companies will prefer growth and redeployment, but that’s not always assured.

    AI will reshape productivity in profound ways. But as with streaming, the honeymoon pricing phase won’t last forever.

  • AI Free Agency

    From the Wall Street Journal: Mark Zuckerberg Announces New Meta ‘Superintelligence Labs’ Unit and a partial reorganization of Meta.

    Mark Zuckerberg announced a new “Superintelligence” division within Meta Platforms, officially organizing an effort that has been the subject of an intense recruiting blitz in recent months.

    Former Scale CEO Alexandr Wang will lead the team as chief AI officer, and former GitHub CEO Nat Friedman will lead the company’s work on AI products, according to an internal memo Zuckerberg sent to employees that was viewed by The Wall Street Journal. 

    This after another WSJ article last week about “the list”, designed to ameliorate Meta’s recent disappointing Llama work.

    All over Silicon Valley, the brightest minds in AI are buzzing about “The List,” a compilation of the most talented engineers and researchers in artificial intelligence that Mark Zuckerberg has spent months putting together. 

    Facebooks’ pivot from virtual reality / metaverse (Facebook -> Meta) to AI suggests that the metaverse was the wrong bet. I suspect Zuckerberg knows it, too, but this huge spending spree aligns with Zuck’s ethos, move fast and break things.

    In a world where a really good basketball player (Shai Gilgeous-Alexander) can command $285 million over four years, spending upwards of $100 million per transformative engineer seems like a relative bargain.

  • If AI Lets Us Do More in Less Time—Why Not Shorten the Workweek?

    It’s a good question for work (particularly for white collar roles) — if workers are more productive because of AI, should the workweek be shorter?

    This question is increasingly central to debates about the future of work and closely tied to the growing interest in the four-day workweek. According to Convictional CEO Roger Kirkness, his team was able to shift to a 32-hour schedule without any pay cuts—thanks to AI. As he told his staff, “Fridays are now considered days off.” The reaction was enthusiastic. “Oh my God, I was so happy,” said engineer Nick Wechner, who noted how much more quickly he could work using AI tools.

    Aside from his contention for boss of the year award, Kirkness recognizes the key criteria for success: getting your work done. If the work can be done faster, companies can choose: (1) reduce the total number of hours worked per employee (without reducing headcount); (2) reduce headcount by a commensurate number (in Convictional’s case, 20%); (3) grow the company to do more work with a similar number of employees.

    As a worker, I’m sympathetic to the idea of shorter work weeks, but I suspect that growth is a more realistic option. Employees continue to work similar hours, but increased productivity leads to company growth (but not headcount growth).

  • Politico: Artificial intelligence threatens to raid the water reserves of Europe’s driest regions

    Amazon and Microsoft are considering building data centers in Aragon (northeastern Spain), a prospect that some in Europe are concerned about because of water use.

    This is an extension of an ongoing conversation in the EU:

    Much has been written about A.I.’s energy demand and carbon footprint. But running a data center is also extremely thirsty work. In 2024, Europe’s data center industry consumed about 62 million cubic meters of water, which is equivalent to about 24,000 Olympic swimming pools.

    After reading this, I thought, geez, that’s a lot of water. But when converting this to acre-feet, it’s roughly 50,000 acre-feet. A large number, for sure, but not astronomically large. By comparison, Granger Lake in Texas stores roughly the same amount of water.

    In 2022, total water usage in Texas eclipsed 15 million acre-feet, of which approximately 7.5 million acre-feet were consumed by irrigation. This makes the 50,000 figure from Europe seem negligible for an population of 450 million.