AI-Native Team Structure Review

I have drafted a new, AI-native structure for my product, design, engineering, and testing groups and I need a seasoned eye on it. The driving goal is simple: make AI work for us everywhere—writing and reviewing code, shaping product roadmaps and UX, and tightening up testing, monitoring, and incident response.

Today each discipline sits in its own lane. I’d like you to challenge my thinking and shape a pragmatic target operating model that blends those lanes where it makes sense, introduces the right AI-powered workflows (Copilot-style coding, GPT-assisted research and design, autonomous test suites, etc.), and spells out the team capabilities, roles, governance, and metrics that will let us move faster without sacrificing quality.

What I expect from you
• A concise written assessment of my current draft (I’ll share slides and notes once we start)
• An improved org chart or squad model, including role definitions, AI tool responsibilities, and collaboration touchpoints
• A RACI or similar matrix showing who owns what across product discovery, build, and run phases
• A 30-60-90 day implementation roadmap with quick wins, change-management checkpoints, and measurable success criteria

I’m open on frameworks—Spotify squad, Two-Pizza, SAFe, or something bespoke—as long as the outcome is a clear, actionable operating model that bakes AI into the everyday flow of work. If you’ve redesigned engineering orgs around AI tooling, Agile/DevOps, or platform teams before, your insight will be invaluable.