Portfolio scope
Digital commerce and platform portfolio planning.
AI Product Leadership
Turn AI plans into products teams can own and ship.
I help enterprise teams move from AI ambition to clear ownership, practical adoption, and measurable product delivery.
Practice reach
Product practitioners supported through coaching, practice, and portfolio leadership.
Commerce lift
Checkout conversion lift tied to unified commerce platform work.
AI-native discovery
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.
When AI work has no clear owner
Clarify decision rights, product bets, intake, and delivery accountability.
When intake creates noise instead of decisions
Turn requests, ideas, and stakeholder pressure into a manageable product system.
When platform choices need adoption and proof
Connect technical direction to user adoption, team workflows, and measurable 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.
Current thesis
AI makes building easier. It makes product management harder.
Generative AI can produce a convincing prototype before an organization has agreed on the problem, the outcome or the work required to make change stick. As building gets easier, product management has to become more rigorous about connecting purpose, evidence and results.
Ask Brian