Most prototype login screens are a shortcut. You tap a button, the screen changes, and everyone agrees to pretend the credentials mattered. The problem isn't aesthetics — it's that a faked login produces faked feedback. When test participants know the interaction isn't real, their behavior shifts and the data you collect shifts with it.

This tutorial builds the real thing: functional text inputs, a masked password field, conditional logic that validates actual credentials, a live error state, and a Face ID animation timed to feel native. The result is a login flow indistinguishable from a shipped product, built entirely in ProtoPie, no code required.

Prefer to learn by watching? The full tutorial video walks you through every step in real time.

More of a read-and-execute type? Use both, the video for context, this guide for the steps you'll want to revisit.

Your login UI imported from Figma or preferred UI tool

Step 1: Import Your Login UI from Figma and Keep Your Layer Structure Intact

In Figma, open the plugin panel, search for ProtoPie, and launch it. With your full login frame selected, choose 

 rather than Flattened. Scene preserves your layer hierarchy; Flattened collapses everything into a single image, which makes it impossible to interact with individual elements later.

Click Export. Your layers will appear in ProtoPie exactly as structured in Figma.

💡 Before moving on, rename every layer clearly. Vague names like “Rectangle 14” will cost you time the moment you start wiring interactions.

Step 2: Replace Static Input Fields with Ones That Actually Accept Text

This is the step that separates a realistic prototype from a clickable mockup. ProtoPie’s native Input layer accepts real keyboard input – meaning testers type actual text, not simulated content.

 and drag an Input layer onto your canvas. Place it inside your username field group in the layer hierarchy, than match it visually to your design:

Match the background fill to your field background

 if there’s unwanted spacing at the field edge

Copy the hex code from your original text layer and paste it into the Input layer’s placeholder color, than match the font and size

Preview. Click the field and type. Your username input is now live.

Step 3: Mask the Password Field So It Behaves Like a Real App

 and place the copy inside your password field group. Two changes make it a password field:

Text Password masks typed characters as dots automatically/ No customer logic needed.

Preview both fields. Username shows typed text, password shows dots. Exactly what users expect – and exactly what makes this prototype credible in a user testing session.

Step 4: Create the Dashboard Scene Before Wiring Navigation

Add a new scene in ProtoPie. This will become your dashboard, it can be empty at this stage. The important thing is that it exists as a navigation target before you wire the login button. Trying to set up a Jump response without a destination scene is the most common sequencing mistake in early ProtoPie builds.

Step 5: Make the Login Button Navigate to the Dashboard

, targeting your dashboard scene, Set the transition to 

Preview and tap. The scene changes. The button works, but it works regardless of what’s in the inputs. The next steps fix that.

Step 6: Use Variables to Capture What the User Types

Variables are what give this prototype memory. Without them, the inputs are just visual fields with no connection to the app's logic.

At the bottom left of the ProtoPie interface, add two variables to your login scene. Set both to 

 type, which handles letters, numbers, and special characters.

Bind each variable to its input layer using a formula. Select the username variable, click 

Do the same for password: input("Input Password").text

Toggle on the debug icons next to each variable. Green variable overlays will appear on screen showing live variable values as you type. This confirms the binding is working before you build any logic on top of it.

Step 7: Add Conditional Logic So Only Valid Credentials Log In

. Create two conditions that must both be true simultaneously:

 response inside this condition block. The scene transition now only fires when both values match exactly. Wrong credentials, wrong email format, or empty fields — none of them get through.

Step 8: Build the Error State for Failed Login Attempts

A login flow without an error state isn't a login flow — it's a one-way door. Find your error message layer, rename it 

Add a second condition to the login button trigger, the inverse of the first:

Preview the full flow. Wrong credentials surface the error message. Correct credentials jump to the dashboard. The login now has two distinct outcomes, which is what makes it testable and stakeholder-ready.

Step 9: Add the Face ID Animation – the Detail That Makes This Feel Real

Biometric login is the interaction that makes testers stop and ask if this is a real app. Here's how to build it.

 layer onto your canvas. Load your Face ID Lottie file and position the group above the iPhone frame, off-screen. Note the Y coordinate of where you want it to land — Y: 60 works well as a landing position.

 to distinguish it from the main login trigger.

 — target the Lottie container, set Y to 

 — target the Lottie file, set time to 

. This resets the animation so it always plays from the beginning.

 — to your dashboard scene, slide in from right to left.

Step 10: Sequence the Timing So the Animation Plays Before the Scene Changes

Without delay settings, all four responses fire simultaneously, the scene jumps before the animation has a chance to play. Use the timeline delay controls to stagger them.

: 0.3s (gives the Move animation time to complete before the Lottie starts)

: 1s (gives the full Lottie animation time to play out before transitioning)

 on the Jump response. This ensures the Face ID animation returns to its starting position if a user navigates back to the login screen.

Preview the complete flow: tap Login with Face ID, the animation drops in and plays, the screen transitions. That's a biometric login that holds up in front of any stakeholder or test participant.

A login that validates real credentials, surfaces a live error state, and simulates biometric authentication doesn't just look impressive. It changes what you can do with the prototype.

Test participants engage with it the way they would a live product. The feedback you collect reflects real behavior, not accommodations for "it's just a demo." Stakeholders experience the authentication flow rather than having it explained to them. And when the logic is this precise, the prototype stops being a visual reference and starts being the specification your engineering team works from.

That's the foundation Pie Bank is built on. In Tutorial 2, we set up the dashboard, how variables carry financial state across every screen, and how to build the scroll behavior that gives premium apps their tactile feel.

Want to bring this level of prototyping to your team?

Building a realistic, testable prototype is one thing. Rolling out that capability across a design team is another. If your team is working on complex product experiences and needs to prototype at this fidelity our Creative Technologists work directly with teams to get there faster.

Tutorial 1 of 4 — FinTech Prototyping with ProtoPie

How to Build a Realistic FinTech Login Flow in ProtoPie Without Writing a Single Line of Code

We Built a Fully Functional Banking App. Without Writing a Single Line of Code.

Pie Bank looks like a real app. It behaves like a real app. The login validates actual credentials. The password field masks with dots. The balance updates when you transfer money. The camera opens when you deposit a check.

It’s a prototype. Built entirely in ProtoPie.

AI tools can generate a button, approximate a layout, even suggest interaction patterns. What they can’t do is validate the specific logic your product depends on. Pie Bank isn’t a best-guess interface. Every conditional flow, every balance calculation, every biometric trigger behaves exactly as specified. That’s the difference between a prototype that looks right and one that proves the product works.

This series breaks down exactly how it was made. Not the surface-level interactions, but the mechanics that make it feel real: the variables, the conditional flows, the hardware integrations, the math that keeps numbers accurate across every screen.

The Business Case for Prototyping at This Fidelity

validated before a single engineering ticket is created. 

that produce data you can act on, not feedback qualified with "well, it was just a prototype." 

 that happens when a decision-maker slides to send a transfer on a physical device instead of reading a spec doc that tries to explain it.

In most FinTech design workflows, the prototype is a visual reference and the logic lives in documentation. When a prototype carries real variables, live math, and conditional flows, that gap closes. The prototype becomes the specification. Fewer engineering assumptions. Fewer revision cycles.

This series was built for teams who need all three.

Meet Pie Bank: The Prototype That Behaves Like a Real App

Pie Bank is a high-fidelity mobile banking prototype with four core interaction areas. Each becomes its own deep-dive tutorial, guided by our Creative Technologists at ProtoPie.

Watch the full demo first. Then come back here to learn how each piece was built.

Four Chapters. Four Skills Every Advanced ProtoPie Prototyper Needs.

Chapter 1 - Log In Like It's Already Live

Tutorial: How to Build a Realistic Login Flow in ProtoPie

Where most prototypes fake the login, this one doesn't. You'll build functional text inputs, a masked password field, variable-based credential validation, a live error state, and a Lottie-powered Face ID animation — fully sequenced and timed. The result is a login flow that holds up in any user testing session or stakeholder demo.

Tutorial: Building a Smart Dashboard with Variables and Tactile Scroll

A UI that remembers. Every balance, every account state, every data point on the dashboard is stored in variables — the app carries your financial state as you navigate through it. We'll also build the paging container that gives the scroll its premium, tactile feel. The kind of detail that turns a demo into a conviction.

Tutorial: Transfer Logic, Dynamic Lists, and Slide-to-Send in ProtoPie

Transfer logic that actually does the math. We build the full send money flow: dynamic account and recipient lists, the slide-to-send component that prevents accidental transfers, and the variable math that keeps balances accurate across the entire session. Stop writing specs that explain how the balance should update. Show them.

Tutorial: Camera Layer Integration and Physical Device Interactions

Hardware that feels indistinguishable from the real thing. We use ProtoPie's camera layer to build a live check deposit flow — real camera feed, capture simulation, and an instant balance update on confirmation. When stakeholders can hold the device and complete the interaction themselves, the conversation changes.

The full series rolls out every few weeks. But if you have a project running now and need to move faster, you don't have to wait for each tutorial to drop.

Our Creative Technologists offer private sessions where you work through your specific prototype directly with them. Your interactions, your logic, your questions.

4 deep-dive tutorials. One fully functional banking app. No code. 

The Zero-Code Banking App: Validate Complex FinTech Logic Before Engineering Starts

The Challenge of Delivering High-Fidelity Prototypes Under Tight Deadlines

Design agencies and consulting firms face many challenges. One challenge we've already covered is 

The solution? Let decision-makers experience what the 

 will feel like through an immersive and 

 using a high-fidelity prototyping tool like ProtoPie.

But there's another hurdle: designers often have just days to deliver a functioning prototype with 

, and stakeholders expect it to be high-fidelity.

Design Agencies Spend Time Figuring Out 'How' Instead of Perfecting Creative Details

, complex interactions and the reality of tight agency deadlines is real. 

When a designer has to struggle to discover how to get all of this done, finding time for creative details is not doable.

, creating realistic prototypes under a tight deadline can feel impossible. With ProtoPie, delivering 

  on schedule is entirely possible, and much easier thanks to 

) has everything you'd consider a complex interaction, and it's fully functional and ready to present to stakeholders and clients.

A prototype like this one can be done quickly. Let's dive into how design agencies and consulting firms 

How ProtoPie Helps You Save Time and Remove the Heavy Lifting Out Of The Way

Traditional prototyping tools like Figma force you into a "

"—you have to think about variables, conditional "

" logic, and syntax before a single pixel moves. 

 tools give you almost no control over the output. (See why control matters just as much as speed in our 

ProtoPie combines simple, visual logic with AI, giving you 

. ProtoPie's logic is linear and visual, mapped exactly to human intent:

Using AI Prototyping to Build Complex Interactions on Tight Deadlines

 handles the heavy lifting, but we are not talking about "vibe coding." You can describe in plain language what you need to get started quickly, and AI generates the complete structure in minutes.

With the heavy lifting of interaction logic handled, 

designers can focus on micro-animations and user experience refinements

. With ProtoPie AI, designers complete three days of work in just three hours.

Get an Effortless Start With Full Control Using ProtoPie AI

ProtoPie AI generates fully transparent, visually editable interaction logic that you can see exactly what triggers activate which responses, modify timing curves directly in a timeline view, adjust 

 through visual flow editing, no code, no abstracted menus, no hidden connections.

How to Stay on Schedule Even When Clients Change Their Minds

Imagine you've finished a prototype, but your client says, "

" Sounds like a nightmare, right? With ProtoPie, it's not an issue at all.

" approach to interaction design makes rework incredibly easy because you stay in one scene. The logic is additive: 

Plus with ProtoPie AI, rework isn't a hassle. ProtoPie AI preserves what you've already built, you can tweak each interaction as needed without starting from scratch.

Start Fast and Maintain Realism All the Way Through

With ProtoPie, speed doesn't mean sacrificing realism. 

Your prototype maintains full fidelity from the first interaction to the final presentation, so stakeholders experience exactly what the end product will feel like, 

When it's time to present, clients and decision-makers interact with a fully functional prototype that mirrors the final product across real-world scenarios and devices.

, and more, giving you the full capability to test all possible scenarios and actions your users can experience.

Imagine you walk into a meeting and hand your client a phone with a prototype that 

. They tap, swipe, scan, and it responds perfectly. No "imagine this will work later" hand-waving, neither static frames. Just a real experience they can approve on the spot, and again, 

Get Complex Interactions Done Quickly, While Preserving the Level of Realism

 helps design agencies and consulting firms meet tight deadlines while still allowing time for creative refinement, delivering realistic prototypes that earn client and stakeholder approval.

 lets you experience your prototype exactly as the final product will look and feel.

The Complete ProtoPie Ecosystem—All on the Pro Plan

 and go from vision to testing your prototype.

Then click on the second button, open it, click the prototype file name, and select ‘Open in Studio’ to open the project on your desktop and explore the interactions.

Create realistic prototypes on tight deadlines. Learn how ProtoPie AI help design agencies build complex, realistic interactions in hours, not days.

How Design Agencies Create Realistic Prototypes Under Deadlines

Claim Your Free Month + 1,000 ProtoPie AI Credits Today!

, you can now transform plain language into complex interaction logic instantly.

To celebrate the launch, we’re offering 

It’s the perfect time to experiment with the future of prototyping.

 Describe what you want in natural language, and watch the interaction logic appear directly on your canvas.

 Unlike other AI tools, ProtoPie AI doesn't lock you in. Every interaction it generates is fully editable. Refine and perfect it however you want.

 Start shaping advanced behaviors immediately on your existing designs.

 Stop wasting hours on repetitive setup. Let AI handle the wiring so you can focus on refining the user experience.

 Get instant answers about Studio features, formula syntax, and interaction patterns without leaving your workspace. Ask in plain language, get working code example back.

Don’t miss out on your free month. Whether you're a solo designer or part of a pro team, see how ProtoPie AI can take your prototypes from static to interactive in seconds.

Choose the Pro Plan and enter the coupon code AI2026

Try ProtoPie AI free for one month — turn natural language into complex interaction logic instantly, with full manual control to refine every detail. Apply coupon AI2026 at checkout.

Enjoy One Month Free of ProtoPie Pro + 1,000 AI Credits!

AI prototyping tools promise instant prototypes from simple prompts. For design teams already using Figma and other prototyping software, the question becomes urgent: 

why add another tool when AI can generate interactive prototypes from anywhere?

The answer separates designers who merely generate outputs from those who validate product ideas with craft and precision. In a market democratizing generation, validation separates professional-grade prototyping from exploration tools. In data-driven organizations where stakeholders demand proof before investment, your ability to create high-fidelity, user-testable prototypes that simulate real interaction design, and then refine them with the intentionality that defines design excellence, determines whether ideas move forward or die in conversation. Anyone can prompt AI to create. What matters now is the 

refinement, the system thinking, and the quality that comes after generation.

Generation vs. Validation: Why the Distinction Matters

Today's AI prototyping tools fall into three categories, but only one is purpose-built for the validation stage where product decisions get made:

These tools excel at generating screens with AI-powered interactions—animations, variables, conditional logic, and publishable web apps. Designed for rapid exploration, seamlessly integrated into familiar design workflows.

 Interaction logic editing lacks visual transparency, complex behaviors require abstracted menus or regeneration.

Vibe coding tools generate functional applications through conversational prompts, remarkably fast for initial output and working code.

 Every refinement requires re-prompting (costs accumulate).

Purpose-built for professional-grade interactive prototyping and UX validation, protothese tools generate editable interaction logic that designers refine visually without code. AI accelerates initial setup while designers apply craft and precision to create validation-ready prototypes for stakeholder and 

 Visual editing of both appearance AND behavioral logic, professional-grade validation before committing engineering resources.

This AI prototyping tools comparison shows how these approaches differ across key dimensions:

 excel at visual exploration with direct editing of layout and appearance, but interaction logic requires abstracted menus or regeneration.

 optimize for functional prototyping but require re-prompting or development expertise for refinement.

provides professional-grade validation through visual editing of both appearance AND interaction logic, enabling direct refinement of behavioral flows without re-prompting or coding.

Why Generation Speed Alone Doesn’t Enable Validation

AI prototyping tools, from UI-focused platforms to code generation tools, have transformed early exploration. All of them can now generate impressive, dynamic prototypes, and many now offer direct editing of visual properties. The friction point isn't visual editability; it's 

interaction logic transparency and control

 let you edit what you see—layout, text, spacing, colors—directly on the canvas after generation. But editing 

 face a parallel challenge. You can see the output, but refining the behavioral logic requires re-prompting or diving into generated code.

Consider a multi-step form, each field needs:

 - email format, password strength, required fields

 - show error states only after submission

 - disable submit button until all fields pass

In UI-focused tools, you can access these behaviors through prototype panels and variable menus, but there's no timeline or logic map showing how interactions connect.

In code-gen tools, the logic exists in generated code that requires development expertise to modify.

Both approaches lack visual transparency into the behavioral model.

For adjustments beyond basic transitions, the workflow becomes:

This works for simple prototypes. For validation-ready prototypes requiring precision control over conditional logic, timing curves, or multi-state behaviors, the lack of visual interaction editing becomes a constraint.

More critically, your interactive prototyping capabilities determine your value to data-driven organizations. Stakeholders need product designers who can create high-fidelity prototypes that accurately simulate product behavior and deliver testable user experiences. If your toolkit lets you adjust appearances but not behavioral logic with visual clarity, you're competing at a disadvantage.

From Design Concept to User-Testable Prototype

ProtoPie AI doesn't replace your design tools, it completes the UX design workflow.

, then leverage AI to accelerate the initial interaction setup while you refine with the craft and precision that defines design excellence. AI handles the grunt work; you bring the intention, quality, and attention to detail that transforms functional interactions into exceptional user experiences. You're not migrating prototyping software, you're extending capabilities while maintaining your design systems.

Where Speed Meets Craft: AI as Your Starting Point, Not Your Endpoint

The value of AI prototyping lies not in automation alone, but in freeing designers to focus on what truly differentiates: system thinking, interaction quality, and the craft of translating complexity into clarity.

ProtoPie AI generates fully transparent, visually editable interaction logic. You can see exactly what triggers activate which responses, modify timing curves directly in a timeline view, adjust conditional logic through visual flow editing, no code, no abstracted menus, no hidden connections. This visual transparency into behavioral logic is essential for creating high-fidelity prototypes that stakeholders and users can validate. You're editing the interaction model itself, not just navigating property panels

Expert-Grade Control Without Re-Prompting

Generated an interaction that's 90% correct? Edit the remaining 10% directly in the interactive prototyping interface. Refine conditional logic, adjust timing curves, control multi-state behaviors, expert-grade capabilities without re-prompting or code. This eliminates the prompting cycle that makes code-gen tools costly at scale and gives you the control needed to simulate precise user experience behavior for testing.

ProtoPie AI understands your scene structure, variables, and layer hierarchy, a meaningful technical advantage over prompt-only tools. It reuses existing variables, respects naming conventions, and generates interactions that fit naturally into your prototype's logic. This context awareness is critical for maintaining consistency across complex validation scenarios without manual reconfiguration.

Manual refinement doesn't require additional AI calls, keeping token costs predictable. Generate the foundation with AI, then refine to create user-testable, high-fidelity prototypes manually.

The Strategic Question: Can You Validate Before You Build?

For design teams and executives evaluating UX validation tools: can you prove product ideas work through user testing before committing engineering resources?

Data-driven organizations require validated concepts tested with real users, not just generated demos. When you need high-fidelity prototypes that simulate complex interaction design and enable user testing with realistic experiences, you need interactive prototyping tools purpose-built for validation.

ProtoPie AI delivers both speed and validation depth, fast AI generation for the foundation, precise manual control for creating user-testable prototypes with accurate user experience simulations, and integrating with your existing UX design workflow.

The right AI prototyping software depends on what you're proving and to whom:

Early exploration and rapid concept generation

: Code-gen tools and UI-focused AI offer unmatched speed for rapid iteration through prompts

High-fidelity interactive prototypes needing precision validation

: Interaction design tools provide both AI generation speed and direct refinement control without re-prompting

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