Beyond the Twitter Clone: What Else You Can Build with This AI-First App Methodology

The video shows how to build a Twitter clone using Windsurf and Supabase, but the real takeaway isn’t the clone itself—it’s the methodology. Once you understand that workflow, Twitter is just one example of a much larger design space.

At its core, the approach is:

Describe intent in natural language → let an AI agent scaffold UI and logic → attach a real backend early → iterate by correcting behavior, not rewriting boilerplate.

This shift changes what’s practical for a single developer or small team to build.

The Methodology, Simplified

Abstracted away from the Twitter example, the workflow looks like this:

  1. Start with product intent, not architecture
    You explain what the app should do instead of how every piece is wired.

  2. Generate the UI and state early
    Feeds, forms, profiles, and layouts are scaffolded automatically.

  3. Use a real backend from the start
    Supabase provides:

    • Authentication

    • A relational Postgres database

    • Row-level security (RLS)

    • Storage and realtime features

  4. Let the database enforce rules
    Permissions, relationships, and constraints live in Postgres instead of fragile frontend logic.

  5. Iterate through conversation
    When something breaks, you paste the error back into the agent and refine behavior.

This creates a tight loop where you’re thinking at the product level instead of the plumbing level.

Below is a step-by-step “follow-along” guide for the video Using Windsurf and Supabase to build a Twitter Clone (chapters: UI → local state → Supabase auth/db → Supabase storage). It includes:

  • What to do

  • What to type in the terminal

  • What to paste into Windsurf Cascade (prompts)

Where I’m quoting/paraphrasing the video’s exact prompts/flow, I cite the transcript.

0) Prereqs

Install:

  • Node.js (18+ recommended)

  • Windsurf (with Cascade)

  • Supabase CLI

  • Docker (for local Supabase)

Terminal

# Verify node
node -v
npm -v

# Install Supabase CLI (choose ONE option)

# macOS (brew)
brew install supabase/tap/supabase

# npm (cross-platform)
npm i -g supabase

1) Create a fresh React app (Vite + TypeScript)

The video starts by creating a blank React app using Vite.

Terminal

# Create Vite + React + TS
npm create vite@latest twitter-clone -- --template react-ts
cd twitter-clone

# Install deps
npm install

2) Start Windsurf Cascade and generate the UI (Chapter ~0:26)

The workflow: UI first, then backend later.

2.1 Install Tailwind (common for this stack)

If you want to match the “modern Twitter clone UI” vibe, Tailwind helps.

Terminal

npm install -D tailwindcss postcss autoprefixer
npx tailwindcss init -p

Update tailwind.config.js:

/** @type {import('tailwindcss').Config} */
export default {
  content: ["./index.html", "./src/**/*.{ts,tsx}"],
  theme: { extend: {} },
  plugins: [],
}

Update src/index.css:

@tailwind base;
@tailwind components;
@tailwind utilities;

2.2 Prompt Windsurf Cascade to build the UI

In the video, the first big Cascade instruction is essentially: “Create the UI for a Twitter clone app using Supabase”.

Cascade prompt

I’m building a Twitter clone app (React + TypeScript + Tailwind). Create a modern Twitter-like UI with:

Home timeline feed

Compose tweet modal / composer

Tweet component (content, author, timestamp, like button)

Left nav (Home, Profile)

Basic Profile page route (can be a stub for now)
Use clean component structure and sensible dummy data/state so everything renders.

Important: keep it working locally with mock data first.

(Then accept the changes in Windsurf as you review them—this mirrors the “accept / mass accept” flow the presenter uses.)

2.3 Run the dev server

The presenter runs the dev server once the app is ready.

Terminal

npm run dev

3) Add local state (Chapter ~10:24)

Goal: make UI interactive without Supabase yet.

Cascade prompt

Replace mock tweet data with local state:

Store tweets in state

Allow “compose tweet” to add a new tweet to the timeline

Allow like/unlike locally (toggle)

Keep components typed (TypeScript interfaces)

Keep everything working without a backend

Sanity check: you should be able to compose a tweet and toggle likes in the UI.

4) Add Supabase locally + Auth + Database (Chapter ~17:29)

The video uses the Supabase CLI and has Windsurf generate the DB objects (tables/triggers/functions/migrations).

4.1 Initialize & start local Supabase

Terminal

supabase init
supabase start

This launches a local Supabase stack and outputs local URLs + anon/service keys.

4.2 Add Supabase client library

Terminal

npm install @supabase/supabase-js

4.3 Create tables/triggers/functions via Windsurf (migration-first)

The key “big ask” in the transcript is:

“Create all the Supabase tables, triggers and functions necessary to run this app… create all the database migration files…”

Cascade prompt (close to video)

Create all the Supabase tables, triggers, and functions necessary to run this app.

Create DB migration files for everything

Tables: profiles, tweets, likes (and anything else needed)

Enable row level security

Add RLS policies so:

users can read public tweets

users can create tweets as themselves

users can like/unlike tweets

users can update their own profile

Add any triggers needed (e.g., profile row creation on signup)

4.4 Apply migrations

Terminal

supabase db reset

The video repeatedly uses supabase db reset while iterating (especially when fixing schema/policies).

4.5 Wire the app to Supabase auth + DB

Cascade prompt

Connect the React app to local Supabase:

Create a Supabase client (env vars)

Add authentication UI (sign up / sign in / sign out)

Replace local tweet state with database reads/writes

Insert tweets into the tweets table

Fetch tweets for the timeline (include author profile fields)

Implement likes persisted to likes table

The video hits some query/typing/runtime issues during this stage and iterates by telling the agent what’s broken (e.g., timeline query issues, likes counting, etc.).

4.6 Optional: enable realtime refresh for tweets

The transcript notes the timeline doesn’t refresh until realtime is enabled for the table.

Cascade prompt

Enable realtime updates for tweets so the timeline refreshes automatically when tweets are inserted/updated/deleted. Make the UI update efficiently (don’t refetch everything if possible).

5) Add Supabase Storage for profile images (Chapter ~54:09)

At this point, tweets + likes work, but profile images aren’t loading; then they add Supabase Storage so users can upload avatars.

5.1 Create a storage bucket + policies (via migrations)

Cascade prompt (matches the video intent)

Add Supabase Storage so users can upload profile images from the Profile page:

Create a storage bucket (e.g., avatars)

Add storage RLS/policies so:

anyone can read avatar images

only authenticated users can upload/update their own avatar path

Update the DB schema to store avatar_url (or storage path) on profiles

Build/finish the Profile page UI to upload an image and update profile

5.2 Apply changes

Terminal

supabase db reset

5.3 Confirm end-to-end behavior

The final flow is:

  • sign up

  • upload a profile image

  • post a tweet

  • see avatar in the tweet

  • like/unlike works

6) “Debug loop” prompts you’ll reuse a lot

When something breaks, the most effective pattern is:

Cascade prompt templates

  • Fix a failing feature

    The timeline isn’t showing tweets after posting. Make sure tweets are being properly queried and rendered. Here’s the error: <paste error>

  • Fix a bad query

    The query joining profiles/likes is wrong. Update it to return tweet + author + like count + whether the current user liked it.

  • Fix RLS issues

    I’m getting a permission denied / RLS error when inserting into <table>. Update the policies so authenticated users can do <action> safely.

  • Fix storage + profile upsert

    Upload works, but updating profile fails with a NOT NULL username constraint. Don’t overwrite existing profile fields when updating avatar.

If you tell me whether you’re following this with (A) local Supabase only or (B) a hosted Supabase project, I can tailor the exact .env values, recommended folder structure, and the “cleanest” schema (profiles/tweets/likes + indexes + policies) for a copy-paste setup.

What Other Apps Can Be Built This Way?

Once you recognize the primitives behind the Twitter clone—users, content, relationships, permissions, and feeds—a wide range of applications become natural extensions.

1. Social & Community Platforms

Twitter is just one shape of a social graph.

Examples

  • Niche community networks

  • Internal company social feeds

  • Discussion forums or Q&A platforms

  • Event- or interest-based communities

Why it fits

  • Users, posts, comments, and likes are straightforward relational models

  • Auth and permissions are critical (RLS handles this cleanly)

  • AI excels at generating feed-based UIs

2. Marketplaces & Platforms

Replace “tweets” with “listings” and you get a new class of products.

Examples

  • Freelancer or consultant marketplaces

  • Job boards

  • Local services platforms

  • Peer-to-peer marketplaces

Why it fits

  • Profiles + listings + interactions

  • Role-based access (buyer vs seller)

  • Search and filtering are database-native

3. Internal Tools & Admin Dashboards

Often the highest ROI use case.

Examples

  • Admin panels

  • Inventory tracking tools

  • Operations dashboards

  • Moderation or review systems

Why it fits

  • CRUD-heavy interfaces are easy for AI to scaffold

  • Schemas evolve quickly

  • Visual clarity matters more than design polish

4. SaaS MVPs

This methodology is ideal for validating ideas quickly.

Examples

  • Productivity tools

  • Scheduling or planning software

  • Analytics dashboards

  • Vertical SaaS (recruiting, real estate, logistics)

Why it fits

  • Real backend from day one

  • Easy iteration on data models

  • Scales naturally if the idea works

5. Content & Media Platforms

Twitter is already a content platform—this generalizes easily.

Examples

  • Blogging platforms

  • Newsletter tools

  • Creator publishing dashboards

  • Media aggregation apps

Why it fits

  • Auth + content + engagement loops

  • Storage for images and media is built in

  • AI removes repetitive UI work

6. Collaboration & Productivity Tools

Many collaboration tools are “social apps in disguise.”

Examples

  • Team discussion tools

  • Task or project managers

  • Knowledge bases

  • Feedback and idea boards

Why it fits

  • Shared data + permissions

  • Clear relational structure

  • Easy to layer in realtime features

7. Education & Learning Platforms

Swap “posts” for “lessons” or “discussions.”

Examples

  • Course platforms

  • Learning communities

  • Mentorship networks

  • Training dashboards

Why it fits

  • Role-based access (students, instructors)

  • Structured progress tracking

  • Community interaction baked in

The Real Unlock

The power of this methodology isn’t speed alone—it’s scope expansion.

It enables:

  • UI generated instead of handcrafted

  • Infrastructure that’s real, not mocked

  • Correctness enforced by the database

  • Iteration through language instead of boilerplate

So the key question shifts from:

“Can I build this?”

to:

“Is this mostly users + data + rules?”

If the answer is yes, this AI-first workflow can probably build it—quickly and credibly.

If you’d like, I can:

  • Map a specific app idea to the Twitter-clone schema

  • Write a ready-to-use Windsurf prompt for a new product

  • Outline the Supabase tables and RLS policies

Just tell me what you want to build next.

Vibe Coding, SupabaseFrancesca Tabor