A sharp edge on a weak spine snaps.

Product strategy

What is defensible when every competitor can build what you build?

When a feature takes weeks instead of quarters, feature parity stops being a moat, for you and for the AI-native entrant chasing you. Differentiation moves to proprietary data, workflow depth and AI value customers actually use and pay for.

• Stress-test your differentiation against AI-native entrants
• Find where your proprietary data and workflows create an advantage competitors cannot copy
• Re-cut the roadmap around what stays defensible
• Pricing and packaging for AI value: seats, usage or outcomes

Fractional CPO and org design

Did you redesign the organization, or just cut it and buy licenses?

Cutting headcount before changing how work flows is how productivity collapses. The gains come from redefining roles: PMs who decide and build, designers who own the system, engineers who own architecture and the gates.

• Pod shape: a PM, a designer and a few engineers owning a whole bet
• Role definitions and career paths for product, design and engineering
• Raise the floor (AI required for simple work in every team) and raise the ceiling (frontier teams)
• Protect core delivery during the change

Reinvestment planning

What does a unit of product value cost you now, and what should it cost?

Your board will ask what AI did to R&D cost. The right answer is rarely “cut”: it is deciding what to reinvest and what to bank. No credible AI-era industry benchmarks exist yet, so I benchmark you against your own baseline and the reference case.

• Cost per shipped feature, R&D as a share of revenue, revenue per R&D employee
• AI tool and inference spend against the output it buys
• Reinvest-or-bank scenarios for the capacity AI frees up
• The board narrative