How to develop an app with AI and cut time-to-market

Summary

In this article, you'll learn:

• Why AI alone isn’t enough to ship faster
• The real bottleneck in app development (and how to fix it)
• How to develop an app with AI: a step-by-step workflow in Miro
• What this looks like in practice: Miles & More at Lufthansa Group
• What your team can build and ship faster with Miro

If you’ve ever watched a product idea die a slow death in a backlog, you already know the problem isn’t a lack of good ideas. It’s everything that happens between the idea and the shipped product: the misaligned stakeholders, the feedback cycles that stretch across weeks, the prototypes that exist only in one designer’s Figma file, and the engineers who start building something that doesn’t match what anyone actually discussed.

AI was supposed to fix this. And in some ways, it has. Individual contributors are faster than ever. Designers generate prototypes in seconds. Developers generate code in minutes. Product managers draft PRDs before their morning coffee.

But here’s the catch: AI has turbocharged solo work while leaving teamwork almost entirely behind. And app development, the real kind that ships and scales, is not a solo activity.

According to Forrester Consulting research commissioned by Miro, 75% of leaders agree that most AI tools focus on individual rather than team productivity. And AI being implemented as point solutions is one of the top two factors dragging down organizations’ return on their AI investments.

So the question isn’t “how do I use AI to develop an app?” It’s “how does my whole team use AI together, without losing days to misalignment and rework?”

That’s exactly what this article is about.

The real bottleneck in app development isn’t what you think

Most product managers assume speed bottlenecks live in execution: engineering cycles, QA, release processes. But research tells a different story. Teams lose the most momentum during the earliest phases of product development, discovery and definition, long before a single line of code is written.

This is where ideas go to stall. It’s where three stakeholders walk out of a kickoff meeting with three different mental pictures of what you’re building. Where the user journey gets debated across twelve Slack threads and never fully resolved. Where the “quick prototype” takes two weeks because it’s sitting in a design queue.

The irony is that these early phases, where clarity matters most, are often the least structured, the most tool-fragmented, and the most dependent on getting the right people in the same room at the same time.

That’s the bottleneck worth solving. And that’s where AI, applied to real teamwork, actually moves the needle.

Miro brings your team and AI together on a shared canvas, so the full context of your project, your sticky notes, your user research, your diagrams, your prototype, stays connected from the first idea through to shipping. When you ask Miro AI to generate something, it’s working from everything your team has already put on the board, not from a blank slate.

The result is that the output is faster, more relevant, and more aligned with what your team actually decided. Teams using Miro’s AI workflows ship up to two weeks faster, on average, and move from strategy to spec 40% faster.

How to develop an app with AI: a step-by-step workflow in Miro

Tony Beltramelli, who leads product at Miro, demonstrated exactly how this works in a live challenge: take nothing but a few rough keywords and, in 15 minutes, produce everything a team would need to start pitching a startup idea and collecting feedback from prospective customers.

The output was a named startup concept, a pitch deck, a clickable mobile app prototype, a desktop web app prototype, a user journey diagram, and a project management table. All connected. All on one board. All ready for the team to react to and build from.

Here’s how you can run the same workflow with your product team.

Step 1: Start with sticky notes to capture your raw inputs

Open a Miro board and use sticky notes to capture your starting point. This could be a few product areas you want to explore, user problems you’ve heard in research, or opportunity spaces from a strategy session. Don’t overthink it at this stage.

In the demo, Tony added four sticky notes, each representing a sector: AI, drones and robots, fast delivery e-commerce, and micro-satellites. That’s it. Four ideas on a board.

The sticky notes do two things. They give the team a shared, visible starting point that everyone can react to and add to in real time. And they serve as the context layer that feeds into every AI-generated artifact that follows.

Tip: Write your prompts with as much detail as possible. The richer your starting inputs on the board, the more relevant the AI output will be. If you have existing documents, design files, or research notes, pull them onto the canvas too before you start generating.

Step 2: Build a Miro Flow to chain your whole workflow together

This is where Miro Flows comes in. Rather than generating artifacts one at a time in separate tools and stitching them together manually, you build a connected sequence of AI-powered steps on the canvas, where the output of each step automatically becomes the input for the next.

In the demo, Tony connected his four sticky notes to a Miro Flows workflow with the following nodes:

• A document generator to create a startup concept brief (name, MVP description, value proposition)
• An image generator to create a logo based on the concept
• A presentation generator to produce a pre-seed pitch deck
• Two prototype generators to create a mobile app MVP and a desktop web app MVP
• A diagram generator to map the user journey for a new customer joining the app
• A table generator to create a project management tracker for building both apps

“It will basically take the four keywords we’ve defined here,” Tony explained. “They will flow into this document generator. And once the document generator is completed, this will then flow into each of these different nodes where we’re going to generate some new artifacts.”

The key insight here is sequencing. The concept document feeds the pitch deck and the prototypes. The prototypes feed the project management table. Nothing gets generated in isolation; each artifact builds on the last, the same way your team would work through the problem if you had unlimited time.

Tip: You can select which AI model powers each individual node in a Flow, and you can attach additional knowledge or allow the node to search the web for context. Use this to make specific steps more informed, for example, routing your competitive analysis node to search for recent market data while your concept brief node works purely from your board inputs.

Step 3: Review, iterate, and customize on the canvas

Once the Flow completes, everything lands on your Miro board, ready for your team to react to. This is where the human judgment comes back in.

From Tony’s 15-minute run, the output included SkyGrid, a drone and robot delivery startup concept, a complete pre-seed pitch deck covering value proposition, MVP, target market, and go-to-market strategy, a clickable mobile app prototype showing the full customer experience from browsing to checkout, a desktop version of the same experience, a user journey diagram branching from welcome screen through login and delivery tracking, and a Kanban-ready project management table for building both apps.

Every single artifact is editable. “I can move things around, change colors, and so on,” Tony noted. And crucially, each prototype is interactive straight out of generation. “If I go into the preview mode, I can interact with this prototype, just like that, a few seconds after generation.”

This matters because it means your team’s first interaction with the concept isn’t reading a document or reacting to a wireframe. It’s clicking through a working prototype on the same board where the original idea was captured. The feedback loop tightens dramatically.

Tip: After generation, invite your stakeholders to the board and run a live feedback session directly in Miro. Use sticky notes on or next to the prototype to capture reactions in real time. Everything stays in one place, which means nothing gets lost between the feedback session and the next iteration.

Step 4: Generate requirements and frame them for every stakeholder

Once the team has aligned on the concept and prototype, Miro’s AI workflows let you generate structured requirements directly from what’s already on the board. Scattered inputs and workshop conversations become polished specs in minutes, rather than days spent manually documenting decisions.

Pull in existing documentation and context, such as your concept brief or design files, to define requirements and next steps. Then frame those requirements for the right audience: slides for leadership, detailed tables for engineering, or a Kanban to track delivery. The same source material, shaped appropriately for whoever needs to act on it next.

This is where the “best product thinking shouldn’t get lost in translation” principle pays off. When requirements flow directly from the prototype and user journey your team already validated, rather than being written from memory in a separate tool, the fidelity is higher and the misalignment is lower.

Tip: Toggle the project management table to Kanban view to immediately start tracking progress against the plan. The table Tony generated in the demo included project names, descriptions, and dependencies for every major piece of work needed to build the mobile and desktop apps.

Step 5: Keep the board as your living source of truth

The Miro board doesn’t end when the flow completes. It becomes the single shared reference for engineering, design, and product throughout development. When questions come up in sprint planning, the answer is on the board. When a stakeholder asks what the user journey looks like, the answer is on the board. When you need to show progress to leadership, the Kanban is on the board.

This is what compresses time-to-market: not just generating artifacts faster, but eliminating the constant re-explanation and re-alignment that happens when context lives in different tools for different people.

As Tony put it: “This is not going to replace doing the work manually. But it just provides a base that speedtracks that work.”

What this looks like in practice: Miles & More at Lufthansa Group

The Miles & More loyalty program at Lufthansa Group ran into a version of this problem that many product teams will recognize immediately.

With very limited design resources, product managers had no practical way to visualize flows and concepts during discovery. Aligning on a solution typically took several weeks. And because nothing was validated before handoff, a six-month development cycle could end in a costly rework.

Björn Ehrlinspiel, Product Owner at Miles & More, describes what the team was working with before they started using Miro Prototypes: “Before using Miro Prototypes, there were no prototypes from the discovery phase. The product team just had ideas.”

With Miro Prototypes, that changed. The team now generates mockups and interactive prototypes directly on the Miro canvas, converting website screenshots into editable mockups, collecting feedback from end users in real time, and validating solutions before a single line of code gets written. A process that previously took more than two weeks now takes less than a day.

“Miro Prototypes is insanely valuable for us because we are way faster in creating prototypes,” says Björn. “I’m way more confident that the things we are implementing for the product are really the right things. And I’m way more confident to bring that also in front of management. Miro Prototypes helps me a lot to show my vision to the management team of the product.”

The downstream effect matters too. With validated prototypes in hand before development starts, the Miles & More team can have deeper, more specific conversations with engineers about implementation trade-offs, rather than asking them to build from ideas. In short, instead of building a solution, Miles & More builds the right solution.

What your team can build and ship faster

If you’re a product manager, the promise here isn’t magic. It’s momentum.

The hardest part of building and shipping an app isn’t any one step. It’s keeping the whole team moving in the same direction through all of them. That requires shared context, fast iteration, and a way to go from “we talked about this” to “we have something concrete to react to” without a two-week lag.

Here’s what the full workflow looks like in practice:

Discovery: Capture your starting inputs as sticky notes on a Miro board. Use Create with AI to cluster ideas, generate a concept brief, and surface patterns from your research. The whole team works from the same board in real time.

Definition: Use Miro Flows to generate user stories, feature tables, and a user journey diagram from your concept brief. Surface dependencies before engineering gets involved.

Prototyping: Generate mobile and desktop prototypes with Miro Prototypes. Run a live feedback session on the canvas the same day. Iterate before anyone writes a line of code.

Planning: Generate a project management table from your prototype. Toggle to Kanban. Start tracking progress against a plan the whole team helped build.

Delivery: Keep the board as the living source of truth for engineering, design, and product. Fewer surprises, less rework, faster shipping.

This is how you cut time-to-market without cutting corners. Not by handing AI a prompt and hoping for the best, but by building a workflow where AI amplifies what your team does together, from the first idea to the shipped product.

Ready to build faster?

If your team is still context-switching between tools, chasing feedback across Slack threads, and watching good ideas stall in the definition phase, the fix isn’t another point solution. It’s a shared space where your team and AI work together, from the very first sticky note.

Try Miro free and see how fast your team can move from idea to validated prototype.

Frequently asked questions

Can I use Miro to develop an app even if my team has no design experience?

Yes. Miro Prototypes and Miro AI are built for cross-functional product teams, not just designers. Product managers can generate interactive, clickable app interfaces directly from a text prompt, without needing to know how to use design tools. You can convert screenshots of existing products into editable mockups, iterate based on team feedback, and share prototypes with stakeholders for review, all without a design background. The Miles & More team at Lufthansa Group is a good example: product managers there now generate and validate prototypes themselves, in less than a day, without relying on scarce design resources.

How does Miro keep my team's product work secure?

Miro is built with enterprise-grade security throughout. Your data is encrypted at rest using 256-bit AES encryption and in transit using TLS 1.3. Miro's infrastructure runs on AWS data centers in the EU, US, and Australia, with backups stored in additional regions. For teams using Miro AI, your data is not used to train AI models. Admins have granular control over which AI features are enabled at the organization or team level, and Miro's built-in prompt redaction protects against AI-specific attacks. Miro holds SOC 2 Type II and ISO/IEC 27001 certifications, is GDPR compliant, and is certified under the EU-US Data Privacy Framework. Enterprise teams can also add Miro Enterprise Guard for advanced data classification, intelligent guardrails, and encryption key management.

Is Miro accessible for users with disabilities?

Yes. Miro is committed to accessibility and publishes an Accessibility Conformance Report (ACR) based on VPAT. If your organization has specific accessibility requirements, you can find Miro's full accessibility guidelines and conformance documentation at miro.com/accessibility.

Does Miro integrate with the tools my engineering and product team already uses?

Miro integrates with a wide range of tools across the product development workflow, including Jira, GitHub, Confluence, Figma, Slack, Microsoft Teams, and more. For enterprise teams, Miro also supports SIEM integrations (Splunk, IBM QRadar), EMM tools (Microsoft Intune, VMware Workspace ONE), and workflow automation platforms (ServiceNow, Okta Workflows). If your team needs a custom integration, Miro provides an open developer platform with an API and SDK for building your own solutions.

Is there a Miro community where I can learn how other product teams use it?

Yes. The Miro Community is an active space where product managers, designers, engineers, and other practitioners share templates, workflows, tips, and use cases. You can join discussions, attend community events, find certified Miro experts, and browse Miroverse, Miro's library of community-created templates, to find starting points for your team's specific workflows. You can access the community at miro.com/community.

Author: The Miro team Last updated: April 10, 2026