Mastery Stage

The mastery stage focuses on organizational governance: making AI Coding costs visible, calls controllable, capabilities measurable, and team practices sustainable.

Learning sequence

1. Token and task cost analysis.
2. AI Gateway and model call governance.
3. Benchmark and real engineering capability assessment.
4. Team specifications, asset library, workflow and evaluation mechanism.

Governance closed loop

Costs are visible → calls are controllable → capabilities can be evaluated → team sustainability

Stage acceptance

• Ability to explain the sources of task costs and establish cost attribution.
• Able to design model routing, permissions, quotas, auditing and downgrade strategies.
• Ability to create evaluation sets that are closer to team work than public benchmarks.
• Able to transform personal best practices into team assets and continuous improvement mechanisms.