I help companies decide what to build with AI, then enable them to design and build it.
Understanding is the highest-leverage work in product, and AI has raised the stakes. When building gets fast, a few weeks learning what is actually true, what existing tools already cover, and what only your business can build saves months of building the wrong thing.
Organizations across 10 industries, from global data companies to state government.
20+ years of building products, in more industries than most teams ever see.
I have spent 20+ years building software as a designer, an engineer, and a product leader, at startups, growing companies, and global enterprises.
Most problems a product team runs into have been solved somewhere before, often in another industry. Having seen them is what keeps an engagement from spending its first months relearning them, or scoping the wrong thing. Knowing what to leave out is worth as much as knowing what to build. AI has made building fast, which makes that judgment worth more, not less.
Industries and domains
- Legal
- Telecom
- Homebuilding
- Higher education
- Fraud and identity
- Health cost-sharing
- Media and publishing
- Cybersecurity training
- Credit and consumer data
- Government and public sector
Decide
Decide what to build
- DiscoveryFind out what is true before committing budget to building it.Stakeholder interviews · Customer conversations · Contextual inquiry · Market research · System diagnosis · Product scoping · Findings and recommendation
- Where AI fitsDecide where AI belongs in your work and your product, and where it does not.Rethink the workflow · Connect before building · Control and autonomy · What is truly yours · Capture what your people know · Data readiness · AI in the product · Findings and recommendation
- RoadmappingA roadmap leadership agrees to and engineering can plan against.Alignment sessions · Capacity planning · Themes and sequencing · Review cadence · Rolling horizon
Organize
Set up how the team works
- Process and methodologyA working rhythm that separates strategy from the daily queue.AI in the workflow · Operating rhythm · Intake and triage · Strategic cycles · Stakeholder prioritization · Work breakdown · Written playbook · Training and enablement
- Product-org stand-upProduct discipline for a company that has been shipping without it.Decision rights · Request intake · Design and concept reviews · Requirements practice · Goal-linked backlog · Product coaching
Design & build
Design it and build it
- Design with AIInterfaces for complex, high-stakes work, including the AI inside them.AI interaction design · Design workshops · User research · Information architecture · Interface design · Prototyping · Design systems · UX review
- Development with AIA scoped build, AI features included, delivered to production and handed over.AI features and agent access · Architecture · Frontend engineering · Pipelines and integrations · Data model and migration · Production hardening · Handover
Principles
A few things hold true on every engagement, whatever it covers.
One person across the whole product
Product, design, and engineering sit with one person, so nothing is lost between a strategy, a design file, and the code.
AI multiplies judgment
I build with AI every day, across research, design, and code, and I help teams work the same way. It moves work faster in whatever direction it is pointed, so choosing the direction matters more. The decisions stay with people.
Understand before committing
Every engagement starts by finding out what is true, whether that is a dedicated discovery engagement or the first weeks of a larger one.
Scope is defined up front
Each statement of work names its scope, deliverables, and end date before it starts. It can cover one service or a few that belong together, such as design and a roadmap. Each one earns its place on its own merit.
You keep the decisions
Recommendations come with the reasoning behind them. Whether to build, and who joins your team, is always your call.
How we engage explains how an engagement is scoped and bought.
He not only points out what could be improved, he comes to the table with concrete solutions, ready to implement them.
Christy FolleseUX Research Manager, Amazon · Via ExperianAlan pushed the organization harder than anyone reasonably could to improve as a product, engineering, and design team.
Amy ChalfenExecutive and advisor, growth B2B tech · Via ExperianAn impressive combination of design, engineering, leadership, and influencing skills.
Rajiv VariaDesign executive, Feedzai · Via Experian