Cognitive biases and failure of Agile
summary
Argues that Agile alone doesn’t fix human error and cites Chaos Report ~20% success rate in early 2000s rising only slightly by 2020, Brooks’ six failure sources (optimism, time vs work, tar pit, Conway’s law, second‑system effect, complexity), and concrete failures: Mars Climate Orbiter lost by unit mismatch, legacy trap of AngularJS v1, a microservices project that was fast but still failed, and F‑35 cost overruns. Offers pragmatic prescriptions: follow the Scrum guide as an ideal, drop practices that stop helping, favor objectivity over optimism.
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chapters (19)
- 0:00Introduction
- 2:54Software projects still fail
- 5:28Agile Manifesto's misleading influence
- 7:17Root causes beyond Agile
- 9:06Brooks on software failure
- 10:13Optimism bias in planning
- 13:08Time versus work estimation
- 14:34Conway's Law impact
- 16:42Legacy systems traps
- 17:45Conway's Law in NASA failure
- 20:41Second system effect
- 22:31Complexity and Agile's role
- 25:48True Agile beyond theory
- 28:56Practical Agile principles
- 31:15Agile adoption theory vs reality
- 33:03Mindset for better Agile
- 34:23People over processes
- 35:46Optimism versus pessimism
- 37:58Conclusion
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