FAQs
A few questions people usually ask.
When does working together make sense?
It's usually a good fit if you're one or more of the following: - Building or evolving a complex product, platform, or internal system. - Care about UX and adoption as much as features and architecture. - Need someone who can sit between product, engineering, data, and the people closest to customers. - Want a fractional partner for strategy, flows, analytics, or internal tools — not just slides. If you're looking for a body to fill a seat or someone to execute a fixed spec without discovery, we're probably not the right match.
What industries have you worked with?
I've worked across legal tech, data/analytics products, B2B SaaS, community platforms, and internal ops tooling — anywhere the system is complex and the experience has to earn trust. If your space isn't listed, that's often fine. The patterns (messy data, fuzzy ownership, adoption risk) repeat more than the industry label.
How do you usually work with teams?
Most engagements start with a short conversation, then a focused discovery phase: walkthroughs, user or stakeholder interviews, and mapping current flows. From there I shape structures, prototypes, or metrics at the right fidelity, stay involved through first ship, and refine based on real usage. I work best embedded with your team — not as a distant advisor sending PDFs.
Can you go into more detail with your select works?
Happy to — many case studies are anonymized or summarized for confidentiality. On a call I can go deeper on relevant examples: the problem, what we changed, and what moved. Works gives the headlines; published case studies and a conversation fill in the "how" and "so what."
How do you price your services?
Pricing depends on scope: fractional leadership, a defined project, or a sprint-style engagement. I typically work on monthly retainer or project-based terms after we align on outcomes. We'll talk through fit and structure on a short call before any formal proposal.
What about AI, do you know AI? (AI. AI. AI...)
Yes — in the practical sense: where AI belongs in workflows, how to instrument it, how to prototype AI-assisted tools, and how to avoid shipping "AI" that nobody trusts or uses. I'm not selling hype; I help teams decide what should be automated, what should stay human, and how the product should feel when AI is in the loop.
Do you have experience with [name here]?
Maybe — ask me directly. I've touched a lot of stacks, tools, and domains over the years. If I haven't, I'll say so and we can decide if the underlying product patterns are still a match.