Building is faster than ever. Knowing what to build isn't.
AI has removed the cost of making things. A working prototype that once took weeks now takes hours. But speed without direction is just a faster way to build the wrong thing.
Most teams have added AI tools to an old process. They're moving faster — in the wrong direction.
"You may just be building the wrong thing more efficiently. More power to build should increase our need to think, not reduce it."
Karri Saarinen, Co-founder · LinearThe AI Design Sprint is structured thinking for an AI-speed world. A lightweight methodology that helps design teams decide what to build — and prove it works — before it becomes expensive.
Old assumptions.
New constraints.
AI removes the bottlenecks the original Design Sprint was built around.
Three phases. One methodology.
Each phase has a human lead and AI running in parallel. Humans set direction. AI accelerates execution.
Frame — Define the right problem
Before anyone ideates, you need ground truth. AI agents research and synthesise simultaneously. The Decider sets direction. Every assumption gets challenged before solution work begins.
Multiple agents scan competitive landscape, user pain points, and market data simultaneously. 30 minutes, not 3 weeks.
Build 5–8 AI personas from real data as a starting hypothesis. A fast way to pressure-test assumptions before real users validate or disprove them in Prove.
One specific, testable question. A Claude agent challenges every assumption. Humans land on the right problem to solve.
Build — Generate solutions and ship something real
Multiple solution branches run simultaneously. AI generates at a pace no human team can match. Design and engineering work at the same time. The phase ends with a working prototype — not a Figma file.
2–3 pods explore different angles simultaneously. AI accelerates each independently. Humans curate and cross-pollinate.
Design and engineering work in parallel. Working prototype in hours, not days. AI handles the repetitive work.
Test copy at every key moment. AI synthesises the strongest elements. Team votes. Decider chooses one direction.
Prove — Get an answer, not a validation
The goal isn't to confirm the idea — it's to stress-test it. Real users. AI synthesis. One clear decision at the end of the phase.
5–7 real users on the working prototype. AI synthesises feedback and drop-off patterns in real-time.
AI simulations cover edge cases, adversarial personas, and failure modes that real sessions miss.
One page. What was learned. What was decided. What happens next. AI drafts it. The Decider signs it.
Six roles. No passengers.
Small, senior, cross-functional. Every person has a clear role and an AI toolkit to match.
Owns the sprint question. Makes the final call. Not a facilitator — a decision-maker with real accountability.
Designs the AI agent stack. Bridges human intent and machine execution. Unique to this methodology.
Runs the Frame phase. Manages synthetic user panels. Keeps the team solving for a real problem, not an assumed one.
Works at AI speed. Generates more directions in a day than a traditional sprint allows in a week.
Ships working code with AI. Turns ideas into something real that users can actually interact with.
A customer, expert, or voice from outside the team. Asks the question nobody else thought to ask.
Right tool, right phase.
Tool-agnostic but opinionated. These work well today.
Download the free
Sprint Kit.
Everything your team needs to run an AI Design Sprint. Phases, prompts, canvas, and decision memo.
No spam. Just the Sprint Kit.
