Turn an Idea Into a Real AI App in Minutes

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You keep getting “AI app” ideas, but the moment you picture backend setup, model hosting, and surprise costs, the idea dies in your notes app.

You don’t need weeks of build time to validate a product. You need a fast way to plug in great models, keep your API key private, and ship something people can click today.

Here’s a simple build that turns that into a real link you can share.

How we shipped a 3-tab AI playground as a membership operator

We emulated a membership owner who wanted a private AI playground for their community, with chat, text-to-image, & image analysis. The goal was a working app in under an hour, without running servers, plus an admin-style setup page for model choice & formatting.

Why Lovable and Nebius AI Studio Works

✅ Gives you one API key that can power multiple open-source models, so you avoid stitching providers together

✅ Removes server setup and scaling work, so you can focus on the product experience instead of infrastructure

✅ Lets you test models in a playground first, so you pick what feels right before wiring it into your app

✅ Keeps costs lower by using open-source models instead of only premium hosted options

✅ Speeds up shipping, so you can validate an idea in hours, not weeks

How We Did It

Here’s the exact build we followed to create a simple AI playground app with three tabs, then secure it properly so the API key never shows up in the front-end. If you can type prompts and click buttons, you can do this.

1. Draft the front-end in Lovable

Start in Lovable and write a single prompt describing the app you want: a simple menu with three pages or tabs for a chatbot, a text-to-image generator, and a vision model that can describe uploaded images.

In a couple minutes, you’ll get a first version that looks real, but it won’t be “powered” yet. That’s fine. This step is about layout, navigation, and flow, not model wiring.

2. Create one API key in Nebius AI Studio

Open Nebius AI Studio and generate an API key for this project. Name it something obvious like “AI Playground” so you can track it later. Treat that key like a password.

If it ends up in your front-end code, anyone can copy it and run usage on your account. The whole build depends on keeping that key on the backend, not in the browser.

3. Add a backend in Lovable using Supabase

In Lovable, connect Supabase to create a backend project. You don’t need to understand the technical screens. The only thing that matters is this: the backend is where secrets live.

Once Supabase is connected, use Lovable’s chat mode to tell it you’ve connected Supabase and you want to store the AI Studio API key securely in the backend, then wire each feature (chat, images, vision) to the right model.

💫 Level Up

Building an app with AI is no longer the hard part. Shipping a usable version is.

AI Coding For Entrepreneurs is the Skill Leap course that shows you how to turn an idea into a working product using tools like ChatGPT, Lovable, Cursor, & Supabase. You’ll learn how to connect the front end, backend, database, & AI features so your app actually runs, not just demos. It’s the perfect follow-on to this week’s playground build when you want to add login, save chats, collect emails, or deploy to a real domain.

• Choose the right AI building tools for each stage, from idea to launch

• Build real app flows in Lovable, then extend them with Cursor when needed

• Connect Supabase for email capture, authentication, & data persistence

• Add AI features with APIs so your app can do real work for users

• Troubleshoot issues fast with practical prompting and debugging habits

4. Let Lovable generate the wiring plan, then implement it

Ask Lovable to create a plan for connecting the chatbot, image generator, and vision analyzer to Nebius AI Studio using the API key stored in Supabase. You’ll see a detailed checklist. Then tell it to implement the plan.

After a couple minutes, you should have a working app: chat replies show up, images generate, and the vision model describes what’s in an uploaded image.

This is the moment you go from “mock app” to “real app.”

5. Add a Setup page for system prompt + model switching

Now fix the “polish” issues that make an app feel incomplete. Create a Setup page where you can set a system prompt (hidden instructions that control how the chatbot responds) and pick models without editing code.

For example, you can set a system prompt that forces plain text responses and consistent formatting. Add a model picker so you can swap models by pasting a model name from AI Studio. Save settings so changes apply instantly.

This turns your app into a reusable playground instead of a one-off demo.

6. Add small UX wins, then publish with a security check

Ask Lovable to add a “New Chat” button so users can reset conversations without refreshing the page. Add a one-click light mode toggle so people can choose a theme. Then use the “Review security” option before publishing. Fix any issues it flags, then publish to generate a shareable link.

If you want it to look like a real product, connect a custom domain after it’s stable.

Other Use Cases

Once you can ship a basic playground like this, you can reuse the same pattern for real business workflows. The main win is speed. You can test an idea, show it to users, and learn what matters before you invest time building everything from scratch.

Here are a few ways different roles can apply the same approach:

📈 Agency owner: Create a client-facing “brand assistant” plus an image generator for ad concepts

📚 Course creator: Build a private student sandbox with chat, image creation, & vision-based feedback on uploads

🛒 Ecommerce operator: Generate product image ideas and use vision to summarize competitor screenshots

✏️ Ops lead: Spin up an internal helper that drafts emails and formats outputs consistently via a system prompt

💡 Founder: Ship a fast MVP to validate demand before paying for custom infrastructure

💡Bonus Pro Tips

Lock down the Setup page: If you add system prompts and model switching, consider making that page admin-only. You can keep it hidden, or add login so users don’t change settings. It keeps your app consistent and prevents support headaches.

Test prompts in AI Studio first: Before you wire a model into the app, test prompts in the AI Studio playground. Save the best system prompt and a few “golden prompts” (email drafting, product copy, image description) so your first demo feels strong.

Be patient & describe the bug clearly: When something breaks in Lovable, explain what you expected, what happened instead, and where it happened. If you can share a screenshot, do it. That usually gets you a clean fix without touching code.

⏭️ What’s Next

Friday’s News edition will cover the biggest updates that affect what you can build and ship right now.

Next week, we’re back with a brand new How-To that takes one practical workflow and turns it into a repeatable system.

And remember, if you’re looking for more in-depth courses and tutorials on how to level up you AI skills, Skill Leap has you covered.