AI adoption maturity - A four-stage ladder from individual chat use to end-to-end processes, driven by growing user fluency, system access, and governance.
Pattern
AI-native SDLC - A software delivery loop where each stage leaves a committed artifact, agents work between human approval gates, and production evidence returns as new intent.
Measuring an AI rollout - Judge an AI tooling rollout by comparing concurrent cohorts against pre-set baselines, and lead with expansion rather than hours saved.
Agents propose, people and policy accept - Route every agent change through pull requests so that required checks, code owners, and approval gates, not the agent, decide what is accepted.
Risk-based autonomy - Give agents more autonomy on low-risk, reversible work and keep human approval for high-risk and production changes, widening scope gradually.
Self-improving skill loop - A scheduled agent reads human feedback on another agent’s output and opens a pull request that edits that agent’s skill file.