Beyond the Demo: What You Can Build with an AI-First App Development Methodology

The video showcases a deceptively simple application: a frontend that lets users generate and manipulate images using OpenAI’s Image Generation API, powered by Supabase Edge Functions for backend logic and storage.

At first glance, it looks like a creative demo.

But the real value of the video isn’t the app itself—it’s the methodology behind it. Once you understand that methodology, it becomes clear that the demo is just one example of a much broader class of applications that can be built quickly, safely, and at production quality.

This article explores that methodology and the kinds of apps it unlocks.

The Core Methodology

Stripped down to its essentials, the workflow looks like this:

  1. Start with a simple frontend

    • Minimal UI

    • One clear user action (upload, click, submit)

  2. Move all intelligence to the backend

    • Edge Functions handle logic

    • Prompts and API calls are controlled server-side

  3. Leverage AI as a capability, not a feature

    • Image generation, editing, remixing, or transformation

  4. Persist everything

    • Store inputs, outputs, and metadata in Supabase

    • Make results reusable and auditable

  5. Iterate by changing prompts, not architecture

    • New ideas don’t require rewrites

    • Just new instructions

This approach dramatically shortens the distance between an idea and a working product.

Why This Method Works So Well

Traditional app development often stalls on infrastructure decisions: authentication, databases, API security, and deployment.

This methodology sidesteps that friction by:

  • Using Supabase as a ready-made backend (Auth, Storage, Postgres)

  • Using Edge Functions to safely wrap AI APIs

  • Treating the frontend as a thin interaction layer

  • Letting prompts, not code complexity, define behavior

The result is a system where experimentation is cheap and iteration is fast.

What Other Apps Can Be Built This Way?

Once you recognize the pattern, a wide range of applications become obvious.

1. Single-Purpose AI Image Tools

These are the most direct extensions of the demo.

Examples

  • Professional headshot generator

  • Anime or cartoon photo converter

  • Old photo restoration tool

  • “Ghibli-style” image generator

Why it works

  • One input, one output

  • Hard-coded prompts for consistent quality

  • Easy to monetize per generation

2. Marketing & Content Creation Apps

AI image generation is especially valuable for non-designers.

Examples

  • Social media post image generator

  • Ad creative generator

  • Product-in-context mockup tool

  • Brand asset generator

Why it works

  • Businesses want speed and volume

  • Supabase storage enables asset libraries

  • Prompts enforce brand consistency

3. Design & Visualization Tools

This methodology is ideal for visual iteration.

Examples

  • UI redesign suggestions from screenshots

  • Interior design previews

  • Packaging design mockups

  • Logo placement visualizers

Why it works

  • Multiple inputs → multiple outputs

  • Easy versioning and comparison

  • Useful for professionals and clients alike

4. Educational & Learning Apps

Visual output is a powerful teaching aid.

Examples

  • Visual explanations for concepts

  • Art style learning tools

  • History scene reconstruction

  • Interactive storytelling for kids

Why it works

  • Prompts encode pedagogy

  • Outputs can be saved and reviewed

  • Simple UI, high engagement

5. Creator & Influencer Tools

Creators value speed more than perfection.

Examples

  • YouTube thumbnail generators

  • Profile picture generators

  • Meme remix tools

  • Merch preview generators

Why it works

  • Fast iteration loops

  • High demand for variations

  • Storage enables reuse and refinement

6. Internal Tools for Teams

Not every app needs a public audience.

Examples

  • Internal design prototyping tools

  • Marketing campaign generators

  • Brand compliance visual tools

  • Creative experimentation sandboxes

Why it works

  • Auth + RLS provide built-in security

  • Edge Functions control cost and access

  • Minimal polish required to deliver value

7. Niche SaaS Products

The biggest opportunity lies in narrow, high-value use cases.

Examples

  • Real estate listing image enhancers

  • Food photography improvers

  • Fashion styling previews

  • Portfolio and resume visual builders

Why it works

  • Domain-specific prompts outperform generic tools

  • Clear buyer personas

  • Straightforward pricing models

8. Experimental & Creative Apps

Finally, the methodology excels at exploration.

Examples

  • Interactive art generators

  • AI-powered photo toys

  • Visual mashup engines

  • Hackathon demos

Why it works

  • Low cost of failure

  • Real infrastructure from day one

  • Easy to evolve into something bigger

Step-by-step

This guide walks alongside the video “Build apps with OpenAI Image Generation API and Supabase Edge Functions” and gives you copy/paste prompts + terminal commands to recreate the workflow:

  • Build a simple frontend UI

  • Create a Supabase Edge Function that calls OpenAI Image Generation

  • Store secrets securely

  • Upload images + generate variations / edits

  • (Optional) store outputs in Supabase Storage

0) Prerequisites

Accounts

  • Supabase account (create a project)

  • OpenAI API key (keep private)

Local tools

  • Node.js 18+

  • Supabase CLI

  • Docker (recommended if you want local Supabase)

Install Supabase CLI

macOS (brew)

brew install supabase/tap/supabase
supabase --version

Any OS (npm)

npm i -g supabase@latest
supabase --version

1) Create the frontend (simple React app)

You can use Next.js, Vite, or whatever you prefer. The video starts with a fast UI and then “jumps into the backend,” so we’ll do the same.

Option A: Vite + React (fastest)

npm create vite@latest pix-prompt-magic -- --template react-ts
cd pix-prompt-magic
npm install
npm run dev

Your UI should include:

  • Image upload (file input)

  • Prompt textbox

  • Optional “mode” selector:

    • Transform (text + image)

    • Combine (two images + prompt)

    • Generate (text only)

  • “Generate” button

  • Result area (show returned image URL / base64)

2) Create / connect a Supabase project

Option A: Use Supabase Cloud (most common)

  1. Create a project in Supabase Dashboard

  2. Copy:

  • Project URL

  • Anon key (for frontend calls, if needed)

Option B: Local Supabase (optional)

From your project root:

supabase init
supabase start

3) Create an Edge Function for OpenAI image generation

Inside your frontend project folder:

supabase functions new openai-image

You’ll get something like:

  • supabase/functions/openai-image/index.ts

4) Store your OpenAI API key securely (Supabase secrets)

Never hardcode keys in your frontend.

supabase secrets set OPENAI_API_KEY="YOUR_OPENAI_KEY"

If using a hosted Supabase project:

supabase login
supabase link --project-ref YOUR_PROJECT_REF
supabase secrets set OPENAI_API_KEY="YOUR_OPENAI_KEY"

5) Implement the Edge Function (what it should do)

Your Edge Function should:

  1. Accept a request with:

    • prompt (string)

    • optional uploaded image(s)

  2. Call OpenAI’s Image Generation endpoint

  3. Return the resulting image (URL or base64)

Prompt to use with your coding assistant (or to implement manually)

PROMPT (Edge Function build)

Create a Supabase Edge Function that accepts a multipart/form-data POST request containing:

prompt (string)

image (file, optional)

image2 (file, optional)
It should call OpenAI’s Image Generation API using the OPENAI_API_KEY secret.
Return JSON containing { images: [ { b64_json OR url } ] }.
Include basic validation, error handling, and CORS.

6) Run / test the Edge Function

Serve functions locally

supabase functions serve openai-image --no-verify-jwt

Example test via curl (text-only)

curl -i http://localhost:54321/functions/v1/openai-image \
  -H "Content-Type: application/json" \
  -d '{"prompt":"A cute robot holding a Supabase logo, studio lighting"}'

Example test via curl (image + prompt)

curl -i http://localhost:54321/functions/v1/openai-image \
  -F 'prompt=Turn this into a Studio Ghibli-style illustration' \
  -F 'image=@./input.jpg'

7) Deploy the Edge Function to Supabase Cloud

supabase functions deploy openai-image

Now you can call:
https://YOUR_PROJECT_REF.supabase.co/functions/v1/openai-image

8) Wire the frontend to the Edge Function

Frontend fetch (JSON, prompt-only)

  • POST JSON with { prompt }

  • Receive { images: [...] }

  • Render image from url or data:image/png;base64,...

Frontend fetch (multipart, with file upload)

Use FormData() and append:

  • prompt

  • image (and optionally image2)

9) Prompts you can copy/paste (video-style examples)

A) “Ghiblify” / stylize

  • “Turn this image into a Studio Ghibli-style illustration.”

  • “Make this look like a watercolor painting, soft lighting, pastel colors.”

  • “Convert this into an 80s anime cel style frame.”

B) Product / marketing

  • “Place this product on a clean white seamless background with soft shadows.”

  • “Put this product on a kitchen counter, morning light, lifestyle photography.”

C) Combine two images

  • “Combine the subject of image 1 with the environment of image 2. Keep the subject’s identity, match lighting.”

  • “Merge these two images into a single cohesive poster, cinematic lighting.”

D) Generate from scratch

  • “A futuristic city street at night, rain, neon signage, ultra-detailed.”

  • “A minimal flat icon set for a fitness app, consistent style.”

10) (Optional) Save generated images to Supabase Storage

This is a common next step:

  1. Create a Storage bucket (e.g. generated)

  2. From the Edge Function:

    • decode base64 image

    • upload to Storage

    • return a public (or signed) URL

PROMPT (Storage add-on)

Update the Edge Function to upload generated images into Supabase Storage bucket generated and return signed URLs that expire in 1 hour. Also store metadata (prompt, created_at) in a table.

11) Recommended “production hardening” checklist

  • Add input size limits (image file size)

  • Add rate limiting (to control costs)

  • Use signed URLs for private images

  • Log request IDs (debugging)

  • Keep prompts server-side when you want consistency + safety

Quick Copy/Paste Prompt Pack (in order)

  1. UI scaffold

Build a simple frontend with: image upload, optional second image upload, prompt input, mode selector (generate/transform/combine), generate button, and results grid.

  1. Edge Function

Create a Supabase Edge Function that takes prompt + optional images (multipart) and calls OpenAI Image Generation. Return image output as url or base64.

  1. Secure key

Read OPENAI_API_KEY from Supabase secrets only. Never expose it in the frontend.

  1. Storage (optional)

Upload outputs to Supabase Storage and return signed URLs; store prompt + metadata in Postgres.

If you want, tell me which frontend you’re using (Next.js or Vite) and whether you want URLs or base64 returned — and I’ll tailor the frontend code shape + request/response format accordingly.

Final Thought

The app shown in the video is not the point.

The point is that once you have:

  • A thin frontend

  • A secure backend

  • AI capabilities behind controlled interfaces

You can build dozens of useful, viable products by changing almost nothing except intent.

The real question becomes:

What problem do you want to solve—and what prompt solves it best?

Want this adapted into a shorter blog post, a startup idea breakdown, or a technical deep dive?
I can also turn one of these app ideas into a concrete MVP plan if you’d like.

Vibe Coding, SupabaseFrancesca Tabor