Team Cognitive Load as a metric to measure Platform impact

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" summary

Organization grows from 3,000 to 4,000 people with ~300 product-tech engineers across ~40 teams, and platform work moves from ops bottleneck to an internal Kubernetes/Terraform-based platform that cuts first-deploy lead time to 10 minute lead time. That scale spawns ~4,000 microservices—>1 service per developer—causing a distributed-monolith and high human friction, so the response is measured cognitive-load surveys every 1–3 months and creation of tribe-level platform teams of ~4 people, which show reduced team load and clearer investment cases.

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" chapters (26)

1. 0:00Introduction to cognitive load
2. 1:11Defining platform teams
3. 3:16Personal experience at fintech
4. 5:27Ops team bottleneck and burnout
5. 7:14Platform team success and side effects
6. 9:01Product teams suffering from overload
7. 11:10Foundation teams losing visibility
8. 13:55Human problems vs system metrics
9. 15:00Assessing cognitive load for impact
10. 17:06Investing in tribe-level platform teams
11. 19:13Forced platform use and feedback loss
12. 20:16Replicating success organization-wide
13. 21:42Why invest in platform teams
14. 23:08Observing cognitive load trends
15. 24:53Faster feedback loops for leaders
16. 27:39Measuring cognitive load approaches
17. 31:09Scientific basis for cognitive load
18. 32:3726 drivers of cognitive load
19. 34:45Cognitive load as sense-making tool
20. 35:29Summary and platform impact
21. 35:55Q&A: Quantifying cognitive load
22. 38:45Q&A: Getting buy-in from developers
23. 41:13Q&A: Platform team in cross-functional teams
24. 44:04Q&A: Scope of cognitive load measurement
25. 46:13Q&A: Opt-in vs forced adoption
26. 48:26Q&A: Managing team disbanding and morale

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