Stop Chasing Unicorns and Rainbows The Dangers of Survivorship Bias in Tech
summary
Argument: survivorship bias skews expectations by highlighting winners and hiding failures. Evidence: 9 out of 10 startups fail within five years and only 1% become unicorns. Examples: legacy phone makers like BlackBerry and Nokia lose market relevance despite past success. Practical checks: use conference Q&A and hallway chats, Google compatibility and limitations, try a quick tinker before adopting—small experiments (author mentions fighting with Docker) reveal hidden costs and whether a tool actually works in real projects.
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chapters (15)
- 0:00Introduction
- 2:5280s music hits' hidden side
- 5:50Survivorship bias in tech
- 8:44Who is affected
- 10:53Startup risks
- 12:18Faded companies
- 13:43Social media bias
- 15:34Conference talks bias
- 16:38Critical questions
- 18:44Research before adoption
- 19:26Hype cycle timing
- 21:15Tinkering to avoid bias
- 23:22Sharing failures
- 24:05Conclusion and key takeaways
- 25:32Q&A
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