AI coding operating models for engineering teams
Teams get value from AI coding tools when delegation, review, governance, and ownership are shared across the organization. This guide explains the operating model behind safe agent use, team skills, MCP access, and review boundaries across Cursor, Claude Code, and Codex.
What teams need before scaling subagents
Subagents create leverage only when teams define clear delegation boundaries, review expectations, and repeatable context. The training focus is not more parallelism by default, but knowing which work can be delegated safely and which AGENTS.md, Codex MCP, skills, or team instructions control the run.
What the workshop installs
Teams leave with shared agent instructions, repository conventions, Codex code review checklists, and examples for turning repeatable engineering work into skills that engineers can inspect and improve.
How we measure success
The target is smaller review burden, faster setup on real tasks, fewer abandoned agent runs, and clearer rules for when engineers delegate, review, or own the work themselves.
Related training topics
Bring this into your team
We tailor the training to your codebase, adoption stage, and review standards.
Book a 15-minute sync