Ultimate AI Design Stack

This is the stack I use to turn rough ideas into polished, working products — fast. Every tool, prompt, and step that actually helps me build smarter with AI.

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1. ChatGPT: my thinking partner

I always start with vision.

Before touching any tools, I answer three questions:

• Who's it for?

• What problem does it solve?

• What makes it feel magical?

ChatGPT helps me unpack that fast → through conversation.

I use it to:

• Brainstorm product ideas

• Map flows and logic

• Define user journeys and interactions

• Write onboarding, error, and empty-state copy

Don't just use it as an assistant. Use it to challenge your thinking.

Example prompts:

"I'm building a journaling app. What are the 5 key screens and what components do they need?"

"Write onboarding copy for a first-time user. Include empty states and microcopy for each screen."

"Map out a daily flow for a voice-based journaling app — from open to log entry."

"Suggest 3 UX flows to reduce friction and increase activation in a productivity app."

Pro tip → Once you've nailed the flow, ask: "Turn this into a Lovable-ready prompt." It speeds up the next phase dramatically.

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2. Lovable: my AI frontend studio

This is where the UI comes alive.

Lovable lets me generate clean UI and prototype in real-time. I give it a prompt, and it gives me a real, interactive product shell.

What I use it for:

• Responsive layouts

• Navigation, forms, dashboards

• Connecting screen flows

• Rapid prototyping

Example prompts:

"Build a dashboard with a sidebar (5 items), a top nav with search and avatar, and a main area with 3 KPI cards and an activity log."

"Create a pricing page with a toggle for monthly/yearly, 3 tiers, a comparison table, and a sticky CTA."

"Design a mobile-first voice note screen with a big record button, transcript viewer, and upload status."

"Build a sign-up flow: welcome screen → email/password input → confirmation → redirect to dashboard."

Tips for better results:

→ check out my AI Prompt Hacks here

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3. Figma: still undefeated for design precision

Yes, I still use Figma from time to time.

It's still undefeated for UI design details.

If I work on a very specific design, like a pricing page, I turn to Figma and draft multiple versions.

Figma is really good for quickly trying out layout options side by side - things like:

• Should the "Pro" plan go in the middle or on the left?

• Does the toggle feel better as a switch or a segmented control?

• Is the CTA better inside the pricing card or pinned below the table?

I answer questions like these by mocking 2–3 variations on the same frame and comparing them visually. It helps me make quick layout decisions and align with the team before building.

Once I land on what feels right, I take a screenshot and prompt Lovable to turn it into code.

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4. Supabase: my instant backend

The final piece of the puzzle.

Once the frontend is ready, I plug it into Supabase to add the functionality

What I use it for:

• Auth (sign-up, login, magic links)

• Database (users, entries, habits, etc.)

• File uploads (voice notes, profile images)

• Realtime sync

• Row-level permissions

How I use it:

1. Define schema with GPT

2. Build tables in Supabase Studio

3. Hook up to the Lovable frontend

4. Add auth and logic

5. Done — live backend.

Example prompt:

"Create a user table with auth, entries table for journal posts, and file storage for voice recordings with row-level security."

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Common mistakes to avoid

1. "Starting in Figma" → Start with logic (use ChatGPT, not the canvas)

Designing visuals too early leads to pretty screens with broken flows.

Instead, figure out:

• What's the user trying to do?

• What steps do they take?

• What should happen when things fail?

Action step:

Use ChatGPT to sketch the flow:

"Map out the steps for a user to [achieve goal], including decisions and edge cases."

Use that structure to guide your UI — Figma comes later.

2. "Too many screens too early" → Focus on 2–3 critical flows

Building everything up front leads to complexity and burnout.

Start with your core loop — the smallest set of actions that delivers value.

Example for a journaling app:

• New user onboarding

• Write a journal entry

• View past entries

That's enough to test the product.

Cut what can wait:

No settings, profiles, feedback forms, or dark mode until the core works.

3. "Forgetting edge cases" → Prompt ChatGPT to uncover them

Most bugs come from unexpected situations — not the main flow.

Ask ChatGPT:

"List 5 edge cases that could break this flow, and how to handle each one."
"What happens if this data is missing?"
"What should the UI do if the user skips this step?"

Design for real-world messiness, not just ideal paths.

→ check out the full guide on Lovable here

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