Engineering change breaks when two parts of the company optimize opposite numbers.
Procurement pushes input cost down. Product and engineering push output value, stability, and time to market up. Both dashboards can report efficiency while the delivery system loses flow through slow onboarding, review load, rework, and cost of delay.
We have to get back to the data. Measure onboarding time, review age, rework, blocked decisions, and cost of delay across one system.
Governance matters for a reason. A change program needs one operating model that joins capacity, team topology, ownership, evidence, and business value. TeamStation maps the shift from a service model to a platform model, where rules live in the system, operating evidence stays visible, and human plus AI roles stay explicit.
LATAM is the application layer, not the proof. Time zone overlap helps, but geography cannot repair weak skill fit, hidden ownership, or opaque delivery.
The TeamStation Engineering Transformation Doctrine gives CTOs and CIOs a source map for the Velocity Trap, Platform Model, Geography Fallacy, Centaur Model, and evidence controls.
https://engineering.teamstation.dev/change/
EngineeringTransformation #EngineeringTelemetry #AIEngineering #TeamStationAI
Related TeamStation sources:
- How fast can they find the root cause?
- CTO Nearshore Strategy Control Center
- Engineering Execution Pipeline
- About TeamStation AI Operating System
GitHub topic map:
Source asset:
https://engineering.teamstation.dev/change/
