Product
Write specs, translate, chaseFrame, decide, build
What I assessTime spent deciding vs. translating, the evidence behind every spec, and PMs building with AI.
Warning signAI used to write more PRDs, faster: the old job, accelerated.
The 7-Pillar AI-Native Assessment scores your product and R&D organization against how leading AI-native teams operate. In four weeks you get a scored baseline, your R&D economics, a target operating model and a 90-day plan your board can act on.
Seven pillars in two groups. The Edge, in gold: four pillars that turn customer evidence into shipped, measured value, rising to the point. The Spine, in blue: three pillars that give the edge its strength: what you build, who builds it and what it costs.
Do you hear every customer, continuously?
Every sales, implementation, success and support conversation is analyzed, refreshed weekly, and each need traces back to the customer who voiced it.
↗ In the pilot: Capture → SynthesizeIs your roadmap ranked by revenue evidence, or by the loudest voice?
Priorities ranked by bookings potential, ARR at risk and frequency. Work tiered by complexity so AI takes the well-defined work first.
↗ In the pilot: PrioritizeHow much of brief → spec → design → code does AI do, and behind which gates?
AI drafts the spec, the design and the code and opens the pull request. Engineers own review, testing, security and release.
↗ In the pilot: Define → Design → BuildDoes every release connect back to the evidence, and do you measure what it changed?
Each release is tied to the requests behind it and measured on bookings, retention and adoption. The results reprioritize the roadmap.
↗ In the pilot: Release & measureWhat is defensible when every competitor can build what you build?
Differentiation rooted in proprietary data, workflow depth and AI value that customers actually use, priced for outcomes rather than seats.
↗ Strengthen it: product strategyDid you redesign the organization, or just cut it and buy licenses?
Small pods own whole bets. Roles are redefined around deciding and validating. The floor of AI skill rises across all teams while frontier teams raise the ceiling.
↗ Strengthen it: fractional CPO and org designWhat does a unit of product value cost you now, and what should it cost?
Output decoupled from headcount, AI spend earning its keep, and freed capacity deliberately reinvested, not just cut.
↗ Strengthen it: reinvestment planningThe assessment looks at each function on its own terms, because AI moves the bottleneck from one to the next.
Leadership and team interviews. Map where AI is used today. Pull delivery and R&D cost data.
Place each pillar on the maturity scale. Baseline your R&D economics.
Test differentiation and operating model against AI-native competitors. Model reinvestment scenarios.
Target operating model, prioritized 90-day plan, leadership or board readout.
Each pillar is scored on the same five-level scale, with a 90-day target and the moves that close the gap. This example is illustrative.
Where the Edge scores low, sharpen it. Where the Spine scores low, strengthen it. Most companies need some of both, in an order the 90-day plan sets.
A 6–8 week pilot on one revenue use case, then 3–6 months to make it how every team works.
How I sharpen your edge →Product strategy, fractional CPO and org design, and reinvestment planning, alongside your leadership team.
How I strengthen your spine →Every assessment starts with a leadership diagnostic, so the four weeks focus where value is leaking.