How Software is Developed for Privacy Professionals
summary
Claims that most privacy failures originate in code and become costly once databases fill, and that shift left automation (scanning commits and CI pipelines) finds leaks earlier. Describes a scanner that produces technical PIA evidence from code, flags unexpected SDKs and analytics calls, and surfaces when data flows to vendors like OpenAI or Stripe. Recommends threat modeling in the SDLC, testing on staging to avoid using real customer data, and continuous checks in CI/CD.
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chapters (10)
- 0:00Software and privacy intro
- 3:33Software development lifecycle
- 6:02Shift left in privacy
- 9:14Privacy by design
- 11:41Key takeaways on trust
- 13:27Security and privacy link
- 15:14Privacy in AI systems
- 17:02Overcoming team gaps
- 18:49Privacy threat modeling
- 20:19Q&A
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