Product Strategy and Execution
From demo to adoption.
For SaaS companies and larger SMBs putting AI into their product. We help you build the AI features customers will actually use, then get them launched and adopted.
Sound familiar?
84%
of product teams worry their products won’t succeed in the market.
Source: Atlassian, State of Product 2026 (opens in a new tab)
“Everyone wants an AI feature. Nobody can say which one.”
We start from what your customers do and say, then rank ideas by what they’re worth to customers and what they’ll take to build. Some ideas end up on a stop list.
customer evidence · roadmap prioritization
“It worked in the demo and broke on real customer data.”
We test AI features on your real data before the full build, so you know the accuracy and the running cost per customer up front.
prototyping · evaluations · unit economics
“We’re not sure what it should never do.”
We set the rules with you: how accurate it has to be, what’s off-limits, and what happens when it gets something wrong.
guardrails · responsible AI
“We shipped it. Hardly anyone uses it.”
We plan the launch past the code, with pricing, sales, and support ready, and an adoption target we track after release.
launch readiness · adoption metrics
How it works
- 01
Start from customers
You getA short evidence brief and a ranked list of what to build, and what to stop.
- 02
Prove it on real data
You getA go or no-go for each AI feature, based on tested accuracy and cost per customer.
- 03
Launch it properly
You getA launch plan covering pricing, sales, and support, with an adoption target.
- 04
Hand over the routine
You getA product team running discovery, decisions, and delivery without us.
What you walk away with
- A roadmap tied to customer evidence, with a written stop list.
- AI features tested on real data, with their cost per customer known.
- Clear rules for what your AI may and may not do.
- Launches that include pricing, sales, and support.
- Adoption numbers for every AI feature you ship.
Questions
How do you decide whether an AI feature is worth building?
We prototype it on real customer data, test its accuracy against real cases, and estimate its running cost per customer. If it misses the accuracy bar, or the numbers don’t work at your price, we recommend a narrower version or not building it.
We already have a product team. Why bring you in?
Good; the work is designed to strengthen the team you have. Senior practitioners stay close to the decisions, work with your product managers and engineers, and join product reviews, steering meetings, or sprints as needed. We help test priorities and features, then hand the decisions and routines back as your team takes them on.
How do you work with us?
Usually as fractional product leadership or strategic advisory for a focused engagement, typically three to six months. We only use the title fractional CPO when the role carries that authority and accountability.
Tell us where it's stuck.
A few lines about what’s blocking it is enough to start. We’ll reply to set up a conversation.