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How to Rapidly Prototype Mobile UIs with Index Cards and GPT-4 Vision

Use index cards to explore a mobile flow anywhere, then give the photographed sequence enough product and platform context for an image model to refine it before rebuilding the result with real Figma components.

How to Rapidly Prototype Mobile UIs with Index Cards and GPT-4 Vision

Terry sketches mobile screens on index cards, photographs them for GPT-4 to refine, then moves the result through UX Pilot into Figma and applies Apple UI components.

Before you start

What you need

  • One mobile user task and its entry and completion states
  • Index cards, a dark pen, and a phone camera
  • A numbered screen sequence with tap targets and transitions
  • Platform UI guidance, brand tokens, content, and accessibility constraints
  • GPT-4 image analysis plus a tool that can produce editable Figma output

What you’ll make

An editable Figma prototype that preserves the tested paper flow, uses recognizable platform components, and includes the key empty, error, loading, and completion states.

Tools used

Step by step

The workflow

Follow the sequence once, then adapt the prompts, checks, and handoffs to your own setup.

3 steps

Step01

Sketch UI on Index Cards

Draw one state per index card at roughly phone proportions. Number the cards, label inputs and tap targets, show transitions, and include the empty, loading, error, and completion states needed for the task.

Step02

Upscale the Sketch with GPT-4 Vision

Photograph the cards clearly and give GPT-4 the user task, numbered sequence, platform, brand direction, content, and constraints. Ask it to describe ambiguities before producing a refined visual direction.

Example prompt
These numbered index cards show a mobile flow for [user task]. First identify ambiguous controls, missing transitions, and states. Then propose a refined [iOS or Android] layout using [brand and platform guidance], realistic synthetic content, accessible type and controls, and the same task sequence. Do not add features outside the cards.

Use even light, keep every card square to the camera, and upload enough resolution for handwritten labels and arrows to remain legible.

Step03

Convert Image to Figma Components

Use the refined direction as reference in UX Pilot or Figma. Replace generated pixels with real platform components, auto layout, tokens, variants, and editable text, then connect the prototype and test it at the target device size.

What good looks like

  • A reviewer can follow the numbered paper flow without verbal explanation.
  • The generated direction preserves the user task instead of decorating a vague sketch.
  • The Figma file uses editable components, text, constraints, and interaction links rather than a flattened image.
  • Tap targets, type, contrast, safe areas, and narrow-screen behavior meet the project requirements.

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After the steps

Runbook notes

How to recover when the loop fails and where human judgment helps.

Recover

If it goes sideways

The model guesses at unlabeled controls or missing transitions
Number screens, label tap targets and data, draw arrows, and provide the task plus expected state change.
A low-fidelity sketch produces generic or messy high-fidelity output
Add platform references, component names, brand tokens, real content, and a layout description before regenerating.
The conversion yields a screenshot rather than editable Figma components
Rebuild with the target UI kit, auto layout, text layers, variants, and prototype links, using the image only as reference.
The visual polish hides small controls, poor contrast, or broken safe areas
Apply accessibility and platform checks in Figma, then test the flow at the target device size.

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