🧠 Engineering Culture

The Bayesian Trap: Why Techies Ditch New Tools After One Bad Swing

Silicon Valley's full of half-tried experiments. Bayes' math shows why ditching that new framework too soon is a classic human screw-up—and how to beat it.

Illustration of a doctor handing test results with probability charts overlayed on a developer at a computer

⚡ Key Takeaways

  • One failed path doesn't mean the goal's impossible—Bayes conditions on evidence, not absolutes. 𝕏
  • Tech history's full of pivots that beat bad priors; quitters miss them. 𝕏
  • Build experiment trackers: separate P(tool|path) from P(tool) to stay sane. 𝕏
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Originally reported by dev.to

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