Discover
Define the opportunity, audience, unmet need, business case, and the assumptions the engagement must test.
AI product strategy / brand / prototype
AI Product Sprint, from idea to evidence.
Turn a promising AI opportunity into a positioned, named, and testable product direction your team can validate, fund, and build.
Product signal
Find the signal in the noise.
Start with the user problem and the business decision, not a model looking for a use case.
Opportunity frame Focused
User problemDefined
Business valueMapped
AI advantageTestable
Delivery riskVisible
From opportunity to evidence
No prototype required. Start with the opportunity.
Bring a rough idea, a problem worth solving, or an existing concept. I help shape the product, name and position it, design and build the prototype, and validate the experience and market case before recommending what to build.
Prototype & validation
Make the idea real enough to test.
Design the experience, compare approaches, and test the product and market assumptions that should shape the next investment.
Prototype review In test
Core workflowInteractive
Failure statesMapped
Human reviewPlaced
Success criteriaMeasurable
The engagement
From opportunity to evidence, in five stages.
Name & position
Develop the product name, value proposition, narrative, and early brand direction that make the idea legible.
Prototype
Design the core experience and build a working prototype around the riskiest product and market assumptions.
Validate
Test the concept against realistic user scenarios, buyer signals, technical constraints, and success criteria.
Decide
Turn the evidence into a product recommendation, prioritized roadmap, and a practical production scope.
What you leave with
A useful handoff, not a theater deck.
Every artifact is designed to help a product and engineering team decide, estimate, and move. The exact package adapts to the question, while the outcome stays concrete.
01
Product and market brief
The problem, audience, opportunity, constraints, competitive frame, and success measures.
02
Name and positioning
A product name, value proposition, narrative, and messaging direction grounded in the audience.
03
Brand direction
A focused visual identity direction that gives the product a distinct, credible presence.
04
Interaction prototype
A realistic, testable experience for the highest-value workflow and riskiest assumptions.
05
Validation findings
Evidence from product, user, and market scenarios, including failure modes and open questions.
06
Technical direction
A clear view of model, data, integration, privacy, and implementation considerations.
07
Decision memo
What to build, what to defer, what remains uncertain, and the next investment worth making.
Product decision
Decisions backed by evidence.
Finish with a recommendation your team can explain, challenge, and act on.
RecommendationProceed with focus
Build the validated workflow first.
Defer adjacent automation until quality and adoption signals are established.DirectionClear
UnknownsNamed
Next stepScoped
PositionA clear audience, name, narrative, value proposition, and brand direction
PrototypeA working experience built around the assumptions that matter most
EvidenceProduct and market findings that support a confident next decision
Relevant experience
Complex products made understandable.
Eskam brings senior product strategy, interaction design, prototyping, and design-system thinking to consequential workflows.
Best fit
For teams facing an expensive product decision.
The AI Product Sprint is designed for founders, product leaders, and innovation teams with a real opportunity but incomplete definition or evidence.
- You have an AI opportunity, user problem, or early idea that needs product definition.
- You need a name, positioning, and brand direction that make the product credible.
- You need to align product, design, engineering, and leadership.
- You want to test the experience before committing to a full build.
- You need a senior partner who can connect strategy, UX, and implementation.
Frequently asked
AI Product Sprint FAQ
What kinds of AI products are a good fit?
The engagement works best around a specific opportunity or product decision: an AI feature inside an existing product, a new AI-native experience, an internal workflow, or an early idea that needs definition and evidence.
Do we need an existing prototype?
No. We can begin with a rough idea, a user problem, a business opportunity, or an existing concept. Defining, naming, designing, and building the prototype can all be part of the engagement.
Do you work with an existing product and engineering team?
Yes. The sprint is designed to work with the people who own the product, know the users, and will carry the work forward. I can lead the sprint independently or embed with an existing product, design, and engineering team.
Is the prototype production code?
The prototype is built to answer product and interaction questions quickly. Depending on the stack and scope, parts may be reusable, but the primary outcome is validated direction and a production-ready plan rather than a rushed production system.
What happens after the sprint?
You can take the plan to your internal team, continue with Eskam through implementation, or use the artifacts to align stakeholders, secure budget, and brief another delivery partner.
How is an engagement scoped?
We start with a working session to define the decision, the people involved, and the prototype boundary. From there, you receive a fixed scope, schedule, and fee before the sprint begins.
Start with the decision
Ready to ship something that matters?
Bring the opportunity, the constraints, and what you need to learn. We’ll turn it into a focused sprint.
Book a working session