Series
AI-Assisted Delivery Governance
Operating models for using AI in serious software delivery without losing architectural control.
AI tools are already in the engineering workflow. The question is no longer whether to use them - it is how to use them without eroding code quality, review discipline, or team judgment. This series builds the governance framework for AI-assisted delivery: from prompt standards and review gates to security controls, quality signals, and the leadership decisions that keep AI-native engineering sustainable.
Governance Foundations
The first essay establishes why AI-assisted engineering requires deliberate governance rather than ad-hoc adoption. It covers the failure modes of ungoverned AI use in production codebases and introduces the operating model framework used throughout the series.
Policy, Prompts, and Review
Subsequent essays cover the operational layer: how to define prompt standards, what belongs in a pre-commit review gate, how to structure AI output review without slowing delivery, and how to maintain human-in-the-loop accountability at scale.
Read the governance foundations essay first to establish the framework. The operational essays can be read independently as reference material for specific governance decisions.