You've shipped with AI. Now you're hiring, fielding investor questions, and realizing that what worked as a solo builder breaks down the moment a second engineer touches your codebase. This system is built for that exact inflection point. AI Engineering OS gives developer-founders a complete operational framework – from how you select and commit to AI coding agents, to how you govern prompts across a team, to how you walk into due diligence with a defensible security narrative. Every section connects to the next: architecture decisions inform your eval infrastructure, your eval infrastructure supports your documentation culture, and your documentation culture anchors your hiring and onboarding protocols. The result is an engineering organization that can grow without losing the quality control you built alone.
What's included
- A scored agent selection framework with explicit criteria for evaluating and committing to AI coding agents at team scale – so agent choices become defensible decisions, not individual preferences
- A prompt governance system covering versioning, ownership, review gates, and a prompt registry structure – giving your team a repeatable process for managing prompts as engineering assets rather than ad hoc inputs
- An eval infrastructure design section covering lightweight regression detection and output quality pipelines – so you can catch AI-introduced regressions before they reach production or a code reviewer
- A security posture module that addresses threat models and secret management for AI codebases, plus guidance on framing your security story for investor due diligence
- A documentation culture protocol built around living docs, AI-versus-human verification standards, and Architecture Decision Record templates – including a full ADR example with context, decision, alternatives considered, consequences, and review trigger sections
- Team scaling protocols with hiring criteria, role templates, and code review standards specifically designed for AI-generated output – so your first hires inherit a system, not a mess
- A 30/60/90-day implementation roadmap with milestone structure and an investor-readiness checklist – giving you a sequenced path from current state to a team and codebase you can put in front of a term sheet
