Better Stories, Better Software
summary
Argues that which story a project adopts changes outcomes: claiming free/open source versus proprietary yields different bugs usability privacy profiles and different business models; proposes concrete tools like append-only logs and universal infinite undo to make catastrophic mistakes unexpressable; shows how extensible languages and meta-programs remove drudgery by automating repetitive patterns; treats events as first-class to reconcile mutation and immutability. Examples and code live in the linked repository.
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chapters (12)
- 0:00Stories shape software
- 1:16Programming vs program stories
- 3:05Decomposing vs cooperative programming
- 4:29Expertise vs shared learning
- 5:11Debugging vs program semantics
- 6:17Catastrophes vs failures
- 6:59Languages as machines vs humans
- 8:05Repetitive code vs automating drudgery
- 9:30Imperative vs functional models
- 10:54Weaving stories from paradigms
- 11:58Bad stories vs dynamic processes
- 13:22Q&A
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