The Great Tech Deflation

🌈 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.

🙋 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 YouTube.tv 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.