Introduction
Most “build an app with AI” tools stop at the demo. They’ll generate a UI, simulate a backend, maybe stub an API call — and leave you stranded the moment you want users, auth, real integrations, or a live App Store listing. OnSpace.ai is interesting because it covers the entire arc: prompt to mobile app to App Store submission, with auth, databases, AI features, and Stripe baked in along the way.
This walkthrough takes a single product idea — an AI ad-creative generator that turns a product photo into clean ads and a short commercial — and ships it end-to-end. You’ll see how to refine the spec with ChatGPT before passing it to OnSpace, what the iterative build loop looks like, how to test directly on a real phone, and how the App Store submission actually works.
📚 Table of contents
- What OnSpace.ai actually is
- Spec first: use ChatGPT to write the prompt
- From prompt to first preview
- Connecting to GitHub for code ownership
- Testing on your phone via the OnSpace mobile app
- Adding real AI features (and topping up tokens)
- Building iteratively — one capability at a time
- Submitting to the App Store and Google Play
- When OnSpace is the right call — and when it isn’t
- Common mistakes & pro tips
- Frequently asked questions
📱 What OnSpace.ai actually is
OnSpace is a prompt-driven app platform. It generates iOS and Android apps (plus web apps and a general AI agent surface). What sets it apart from other generators:
- Built-in authentication and account creation with email verification.
- Cloud data — users, tables, edge functions, secrets, AI integrations.
- Direct Stripe wiring for payments.
- Built-in AI capabilities — image generation, video generation, model calls metered in tokens.
- One-click GitHub repo connection — you actually own the code.
- App Store and Google Play submission from inside the platform.
Free tier is enough to prototype. App Store submission needs an Apple developer account ($99/year) handled outside OnSpace; submission itself is done from the platform.
📝 Spec first: use ChatGPT to write the prompt
The single biggest predictor of a clean OnSpace build is the prompt that triggers it. Direct one-line prompts produce vague apps. The fix: spend five minutes refining the spec in ChatGPT first.
The refinement loop
- Describe the idea in your own words — what the user uploads, what they get back, what flows you want.
- Ask ChatGPT to ask clarifying questions before drafting the spec.
- Answer the questions one by one. Audience, monetisation, key screens, integrations.
- Ask for a final, streamlined prompt you can paste into OnSpace.
- Copy the result. That’s the build trigger.
The interview-style flow surfaces details you would never have included in a one-shot prompt — and OnSpace produces a better v1 because of it.
⚡ From prompt to first preview
Paste the refined prompt into OnSpace, hit go, and the platform generates the first version of the app in a few minutes. The output includes:
- A web preview you can navigate in the browser.
- A QR code that opens the app on your phone (after installing the OnSpace mobile app).
- A checklist of next steps — usually camera permissions, AI backend integration, persistent storage.
- A cloud data panel showing users, tables, edge functions, AI usage, and secrets.
- The full source tree, editable in-browser or via Visual Studio Code online.
Most v1s ship without real integrations — the camera screen is mocked, the AI buttons return placeholder data. That’s by design. The first build proves the flow; later iterations wire it up.
🐙 Connecting to GitHub
Connect OnSpace to GitHub right after the first preview. This does two things: it gives you full code ownership (you can hand the repo to a developer if you outgrow the platform later), and it lets teammates contribute via standard PR workflows.
From the OnSpace project sidebar, choose “Connect GitHub,” authorise the integration, manage org access, and the project auto-creates a fresh repo with the current source. Every iteration after that pushes commits to the same branch.
📲 Testing on your phone
Scan the QR code → install the OnSpace mobile app → sign in with the same account → open your project. The generated app runs inside the OnSpace container with full access to camera, photo library, and notifications. This is the real device behaviour you care about, not just a web preview.
📸 Run through the golden path on a real device before iterating. Buttons that work in the web preview sometimes fail on mobile (e.g. camera permissions) — you want to catch that early.
🤖 Adding real AI features
OnSpace ships with metered AI tokens. The first integration (image generation, video generation, chat completion) auto-enables when the agent decides it needs it. You get a small free pool; top up if you expect serious usage. Token economics live in the AI panel of the project dashboard.
A typical AI loop on the example app
- User snaps a photo of a product.
- Background-removal AI strips the background.
- The enhanced image goes through Gemini Image to generate variations with chosen themes (mint leaves, fire, smoke, raindrops).
- The user picks a variation; Veo 3.1 generates a short video ad.
- All assets are stored in OnSpace cloud storage; the project record now contains image and video URLs.
Costs accrue per call. Keep an eye on the AI panel during iteration so you don’t burn through your free tier debugging.
🔁 Build iteratively, one capability at a time
The mistake most people make is asking for everything in one prompt and watching half the requirements get dropped. The fix is the same one developers use for AI agents: small prompts, one capability at a time.
A reliable iteration order
- Generate v1 from the refined spec.
- Test the navigation flow on phone. Fix any dead buttons.
- Wire up authentication and email verification.
- Enable real camera and photo-library access.
- Turn on the AI integrations — one feature, one prompt.
- Add persistent storage so projects survive between sessions.
- Polish the empty states, error messages, and onboarding.
- Submit for review.
🏪 Submitting to the App Store and Google Play
From the publish panel, pick a target (App Store or Google Play), provide app metadata (icon, screenshots, description), connect the relevant developer account, and submit. OnSpace handles the packaging, signing, and metadata upload. Review timelines match the stores’ usual cadence — a few hours to a few days for Apple, faster for Google.
The $99 Apple developer fee is unavoidable; OnSpace doesn’t bypass it. But it does remove every other piece of operational friction — provisioning profiles, signing certificates, build pipelines.
⚖️ When OnSpace is the right call — and when it isn’t
✅ Strong fit
- Solo founders shipping a mobile MVP in a weekend.
- Internal tools that need auth, a database, and AI features without managing infra.
- Marketing or content-creator apps where AI image/video generation is the core loop.
- Validation prototypes you intend to test with real users before investing in a custom build.
⚠️ Less obvious fit
- Apps with complex native modules (Bluetooth, low-level camera APIs, hardware integrations).
- Workloads with strict data-residency or compliance constraints.
- Performance-critical games or real-time experiences.
- Teams who want full control over the build pipeline from day one.
💡 Common mistakes & pro tips
❌ Common mistakes
- Skipping the spec-refinement step and going one-shot.
- Asking for every feature in a single prompt and watching half get dropped.
- Testing only in the web preview, never on a real device.
- Forgetting to monitor AI token usage during iteration.
✅ Pro tips
- Connect GitHub on day one. Code ownership is leverage if you migrate later.
- Run the spec through ChatGPT’s interview-style flow before pasting.
- Cap each iteration at one capability. Verify on phone before adding the next.
- Use OnSpace’s edge functions for any logic you don’t want clients to see.
Conclusion
OnSpace stands out by being one of the few prompt-driven app builders that takes a project all the way from idea to App Store. Spend time on the spec, iterate one capability at a time, test on a real phone, and connect GitHub from day one. Treat the platform as a way to compress weeks of integration work into hours — not as a magic button that replaces engineering judgement. The apps that ship well from OnSpace are the ones where the human did the thinking and let the platform do the gluing.
Related reading: Blitzy enterprise AI coding agent — Claude Code hands-on deep dive — Claude AI review — AI coding tools worth learning in 2026 — how Crio rebuilt a startup's vibe coding team