Portfolio planning across digital commerce and platform work.
AI Product Leadership
Turn AI plans into products teams can own and ship.
I help enterprise teams clear up ownership, intake, adoption, platform choices, and how progress gets measured.
Product practitioners supported through practice, coaching, and portfolio leadership.
Checkout conversion lift tied to unified commerce platform work.
Faster initial engagement, triage, and discovery through AI-native workflow.
Where I can help
Three places where AI product work usually needs a firmer hand.
AI product strategy
Turn loose AI plans into product bets with ownership, intake, adoption, and proof.
Product operations
Clarify how work enters the system, how choices get made, and how teams learn.
Platform product
Connect platform choices to developer experience, product adoption, and shipped outcomes.
Selected outcomes
Proof that strategy connected to operating moves and shipped work.
Enterprise AI
AI product platform convergence
Moved fragmented enterprise AI work toward an executive-backed platform operating model with clearer ownership, governance, adoption paths, and product accountability.
Product Operations
Product operating system for enterprise delivery
Shaped product operations around intake, planning, delivery, launch, measurement, tooling data quality, and product competency rather than isolated process fixes.
Developer Platform
Developer platform and AI-assisted delivery
Connected developer experience, observability, AI-assisted delivery, and reliability practices into a platform product narrative with measurable engineering outcomes.
How I work
From AI ambition to a shipped product system.
Tools do not make AI shippable. Teams need ownership, governance, adoption, measurement, and delivery to work together.
- 01AI ambition
Executive intent, market pressure, and experiments need a product frame.
- 02Platform ownership
Clarify what becomes governed capability, what remains exploration, and who owns adoption.
- 03Operating rhythm
Connect intake, discovery, roadmap, funding, delivery, launch, and learning.
- 04Adoption paths
Help product and engineering teams know where AI belongs in real workflows.
- 05Measurement
Tie adoption to product accountability, developer experience, and shipped outcomes.
Ask Brian