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The Great Tech Deflation

๐ŸŒˆ Abstract

The article discusses the challenges faced by tech companies as they reach the plateau of the S-curve growth cycle, and the implications for the tech job market.

๐Ÿ™‹ Q&A

[01] The S-Curve Phenomenon

1. What is the S-curve growth cycle that successful products and services go through?

  • The article explains that almost all successful products and services go through a typical S-curve growth cycle:
    • Initially, the product is rolled out to early adopters
    • Then it starts to take off and has a period of "hockey stick" growth
    • Eventually, the growth tapers off

2. How do companies keep growing over time if the S-curve dynamic ultimately wins?

  • The answer is by stacking products and S-curves:
    • Apple launches the iPod, then the iPhone, then the iPad, then the iWatch, etc.
    • Amazon launches for books, then an expanded product line, then Amazon Web Services, etc.

3. What happens when companies run out of natural adjacencies to launch new S-curves?

  • The successful ones try to take over other companies' S-curves:
    • Google launches to compete with typical TV offerings
    • Amazon offers its Prime Video to compete with Netflix and Disney+
    • Microsoft offers Azure to compete with Amazon Web Services

4. What happens when companies run out of competitive S-curves to take over?

  • They can try to go after new markets, like Meta's Metaverse/VR/AR play, but this can be very expensive.

[02] The Decline of New S-Curves

1. What does the data on Series A funding for startups suggest?

  • The size of Series A funding for startups has more than tripled in the last 10 years, from ~$6m in 2012 to ~$19m in 2021, suggesting the low-hanging fruit for S-curves has been picked.

2. What are some examples of high-profile investments in potential new S-curves?

  • The article mentions examples like self-driving cars, quantum computing, and the Metaverse, all of which require a "ridiculous amount of money to get off the ground" compared to startups a generation ago.

3. What are the implications if there are no more (or very few) new S-curves?

  • The article suggests this will lead to:
    • Massive layoffs in the tech industry as companies realize they don't need as many software engineers to maintain existing products
    • An implosion in the tech job market as the need for new product development declines
    • A shift towards a focus on profitability rather than growth at all costs

4. What evidence is there of these mass layoffs already happening?

  • The article cites examples of major tech companies like Meta, Amazon, Google, and Disney laying off thousands of employees in the past year.
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