AI Product Design Sprint
Design Sprints for teams moving fast with AI
Move from idea to build with absolute technical clarity and architectural confidence – with AI integrated across every phase.
AI can build almost anything in days. The teams that win are the ones who know what to build before they start.A Design Sprint gets you there in one week.
Design Sprint Services
Together with your team, we identify opportunities, design solutions, and validate them fast. Whether you have a clear problem to solve or are still figuring out where AI fits in your product, we have a sprint built for where you are right now.
A Design Sprint is a structured process to go from a problem or idea to a validated prototype, without committing to full development first. In ours, AI is integrated across every phase: synthesizing research documents in a single session, generating layout variants during ideation, and assembling navigable prototypes while the sprint is still running. That time goes back into what matters most: product architecture, flow logic, and the judgment calls that make a prototype actually work for the user, the business, and the team that’s going to build it.
Who is this for?
- 1. The sprint works best for technical and product leaders who have a clear problem and need to validate a solution before committing to full development. Teams in fintech, healthtech, and cybersecurity who work in high-stakes environments where getting the product right the first time matters. Companies that are scaling and need to move fast with confidence.
- 2. It's also a strong fit for founders preparing for a funding round who need a validated prototype to show investors, and for product teams who need to align stakeholders around a direction before engineering gets involved.
- 3. If your company is exploring where AI can create real value, whether that means automating repetitive processes, accelerating workflows, or identifying new opportunities inside your product, the sprint includes a dedicated AI opportunity analysis as part of the process. You leave knowing what to build and where AI can make it work better.
- 4. Our team is built to absorb complexity from day one. We take the time to understand your context, your business, and the problem you're solving, and we stay focused on getting to a validated solution, however complex the path gets.
- 5. The sprint requires active participation from your side. Key stakeholders need to be available during the process, and the more context your team brings into Discovery, the stronger the output.
Our reviews
How we run it
Where you start depends on what you already have.
What happens during the AI Product Design Sprint
This is the base structure. What makes the sprint valuable is that we adapt it to what your project actually needs. The sequence, the emphasis, and the depth of each phase adjust based on your problem, your team, and the context you bring into the room.
We map your business context, your users, and the constraints your team is working with. We also run an AI opportunity analysis: where in your product or workflows could AI create real value, reduce friction, or automate something that’s costing your team time. By the end of phase one, the whole team has a shared understanding of what we’re solving and why it matters.
We define the structure of the solution. Information hierarchy, navigation flows, entity relationships. This is where the decisions that shape the entire product get made, and where your stakeholders need to be in the room. AI assists with visual mapping, and the designer defines what gets built and how it connects, based on a deep understanding of your business and your users.
We build. AI compresses what used to take days into hours: wireframes, layout variants, interactive prototype. Your stakeholders can contribute ideas using natural language prompts and see them materialized in minutes. The designer directs every decision, evaluating what to keep, what to discard, and what actually holds up against the problem we defined on phase one.
We test the prototype with real users or AI-generated synthetic user profiles. The goal of this phase is to confirm that the solution we designed actually has value for the people who will use it. We document findings, identify where the prototype holds and where it needs refinement, and deliver.
Every project is different. If your scope covers more than one use case, involves higher complexity, or needs a different structure, the Custom Sprint follows the same methodology adapted to what your project actually needs. We define the process together in a scoping call before anything starts.
Once the sprint is done, LoopBuild takes the validated prototype and turns it into a production-ready product. The Build Brief, a document that captures the technical decisions, architecture, and scope defined during the sprint, gives the development team everything they need to start building on day one.
This is the future of secure development. AI-driven teams, ready to build with you.
What is a prototype?
A prototype is a realistic simulation of your product. Users can navigate through it, interact with it, and give feedback on it. It’s built to validate your idea with real people before committing to a full build.
Depending on the complexity of the project, a prototype can range from an interactive mockup in Figma to a fully functional build. What they have in common is the goal: confirm that the solution has real value before investing in scalable development.
A prototype is not the same as a scalable codebase. When we refer to a prototype throughout this page, we mean a validation tool. Scalable, production-ready code is what comes next, in the Build Ready Sprint.
What to expect
For more than six years, we've been running product sprints, and that experience shaped how we work today. We've learned when to push a direction and when to throw it out, how to separate what the business wants from what the user actually needs, and how to get a team aligned fast enough to matter.
For a few days, your team works alongside our specialist product designers and senior engineers, inside your product. We ask the questions your team has been avoiding, debate the strategies worth debating, and build a clear plan for what to take to market. Your stakeholders are in the room when decisions get made. Throughout the sprint we look for opportunities where AI can automate or accelerate parts of your product or workflows. That's part of how we think from day one.
We move through problem definition, architecture, and prototype together, so your team is aligned; AI handles the generation, the team handles the judgment calls. We test with synthetic user profiles for early usability signals, and any research, documentation, or session recordings you bring into Discovery accelerate the process.
Finally, you get a validated prototype and the clarity to move forward, whether that means pitching investors, aligning your team, or going straight into development.
Why LoopStudio
- 1. Our specialist product designers and engineers analyze your business, your technology, and your users before they design a single screen. That's how we make sure what gets built generates real value and people actually want to use it. That judgment, built over more than six years of running sprints, is what turns a sprint into a validated direction.
- 2. We use AI to handle the mechanical work: synthesis, variants, prototypes. That frees the team to focus on what really defines the quality of a sprint, which is understanding the client's business, the real user, and the constraints of the team that will build it. We also bring hands-on experience evaluating AI opportunities within products, having helped clients across different industries find where AI creates real value.
- 3.What we've learned over six years has as much to do with people as with process. We've learned to align on scope before day one, to get genuine commitment from every stakeholder before the sprint begins, and to facilitate with enough conviction that the team stays focused on what matters. We've had testing sessions where users reshaped the direction of a product entirely, and we've learned that catching that on day four of a sprint is one of the most valuable things that can happen.
- 4.That experience shapes how we facilitate. We read the room, manage the dynamics, and make sure the sprint produces something the team can move forward with, with confidence and conviction.
- 5.Security is part of how we design, not something we check at the end. The flows we build account for security risks from the start.
Tools we use
Discovery and synthesis
Claude, NotebookLM. Architecture: Claude + FigJam AI.
Ideation and wireframing
Claude, Figma Make, Claude Design.
Prototyping
Claude, Figma Make. Visual design: Claude Design, Figma Make
UX writing
Gemini, Claude. Handoff documentation: Claude, Gemini. Code: Claude Code.
FAQ's
How long does the sprint take?
The AI Product Design Sprint runs 4 days. For larger or more complex projects, the Custom Sprint timeline is defined together in a scoping call before the sprint begins.
What if we don't have real users available for testing?
When real users aren’t available, we run testing with AI-generated synthetic user profiles to get early usability signals. The AI Product Design Sprint includes testing with real or synthetic users on day four.
Is the prototype functional code?
It depends on the tier. The AI Product Design Sprint delivers an interactive prototype built to validate your idea with real users: it looks and works like the real thing, but it runs on design tools. The Build Ready Sprint goes further: the second week moves into a functional build with scalable code, deployed and ready to share. From there, LoopBuild takes that foundation and develops the full product.
What do we need to prepare before the sprint?
Key stakeholders available during the sprint, a defined business problem or question, and any existing research, documentation, or session recordings. That material is valuable input the AI can process during Discovery to accelerate the process and align expectations.
What happens after the sprint?
Every sprint feeds directly into LoopBuild. Because discovery is already done, the sprint deliverable gives the development team everything they need to start building. The timeline depends on your priorities and availability; we have the resources to move immediately when you’re ready.
Which tier is right for us?
If you have one clear problem or feature to validate, the AI Product Design Sprint covers it in 4 days. If your project involves more than one use case or higher complexity, the Custom Sprint is built for that. If you’re unsure, a 30-minute call is the fastest way to figure it out.
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Andres Ruiz
Chief of Growth
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