The Problem with “I Have an App Idea”
In consulting, we generate more app ideas in a single client engagement than most teams ship in a quarter. A portal for tracking Oracle module adoption. A self-serve tool for candidates to monitor their recruiting pipeline. A dashboard that maps ERP configuration decisions to delivery risk. The ideas are cheap. Building them used to be expensive.
That’s changed. The vibe-coding movement — using AI tools to generate functional app code from natural language — has collapsed the gap between “I have an idea” and “here’s a working prototype.” But it only works if you have the other two pieces in place: somewhere to store your data, and a way to get it live. This guide covers all three, with a direct link to the hands-on article for each step.
Step 1 — Vibe Code the App
You describe what you want. The AI builds it. That’s the premise — and in practice, it holds up better than it should. I’ve used it to build a full Oracle recruiting management app with candidate tracking, job posting management, and an application pipeline. The key insight is that you’re not just prompting a chatbot — you’re prompting a system that understands UI components, data models, and API patterns simultaneously.
Several tools can handle this step. I’ve tested a few, and the experience differs meaningfully depending on what you’re building:
| Tool | Best For | Guide |
|---|---|---|
| IBM Bob | Enterprise-grade full-stack apps with structured data models, complex UI, and Oracle integration context | Read the Bob guide → |
| Claude Cowork | File-aware, multi-step app building with tight integration to your local workspace and iterative refinement | Guide coming soon |
| Antigravity | Rapid UI prototyping and visual component generation with minimal prompt engineering | Guide coming soon |
| Claude Code | Terminal-native, developer-mode app building with full codebase context and git integration | Guide coming soon |
The output of this step is a GitHub repository. Your AI-generated app, committed, pushed, and ready for Steps 2 and 3. If you’re using a tool that generates code locally (Claude Code, Claude Cowork), you push the repo yourself. If you’re using a cloud-based tool (Bob, Antigravity), the export-to-GitHub path is usually one button.
Step 2 — Create Your Supabase Database
Your app needs somewhere to store data. Supabase gives you a PostgreSQL database, a REST API, and an auth layer in under 10 minutes — for free. The visual table editor means you don’t need to write SQL to create your schema. The auto-generated REST API means your AI-built frontend can start reading and writing data with no backend code required.
The output of this step is three environment variables: your Project URL, your anon key, and your service_role key. You’ll need all three in Step 3.
Covers: project provisioning, visual schema design, Row Level Security, and getting your API keys.
Step 3 — Deploy on Vercel
Connect your GitHub repo to Vercel, paste in your Supabase environment variables, and hit Deploy. Vercel detects your framework, runs the build, and serves the app from a global CDN with HTTPS. First deployment: under 90 seconds. Every subsequent push to main: automatic redeploy. Every pull request: a preview URL.
This is the step that turns your vibe-coded prototype into something you can actually share with a client, a stakeholder, or a hiring team. A real URL. A real domain if you want it. No server management, no SSL configuration, no deploy scripts.
Covers: GitHub repo import, environment variable setup, first deployment, preview URLs, and custom domains.
The Full Stack, in One View
| Step | Tool | Time | Output |
|---|---|---|---|
| 1 — Build | Bob / Claude Cowork / Antigravity / Claude Code | 1–3 hours | GitHub repository with working app code |
| 2 — Store | Supabase | <10 minutes | PostgreSQL database + REST API + 3 env vars |
| 3 — Deploy | Vercel | <10 minutes | Live URL, HTTPS, CDN, automatic redeploys |
| Total | — | 1 morning | Production-ready app, live and shareable |
What This Changes in Practice
I’ve been in enough discovery workshops to know that half the client asks that get logged as “future requirements” never make it to a backlog because the perceived cost of building them is too high. The 3-step stack changes that calculus. When a consultant can prototype and deploy a working version of a proposed solution in a morning — before the proposal is even written — the conversation shifts from “can we build this?” to “is this what you had in mind?”
That’s not a marginal productivity gain. That’s a different way of doing consulting.
The barrier to building is gone. An AI tool builds the app, Supabase stores the data, and Vercel serves it — all free tiers, all zero server management, all done in a morning. The only thing between a consulting idea and a working prototype is the time it takes to describe what you want.
Resources: Step 1: Vibe Coding with IBM Bob · Step 2: Supabase Database Setup · Step 3: Deploy on Vercel · Supabase · Vercel
Oracle Cloud Practice Lead & AI & Futuristic Technology Consultant
Christian leads Oracle Cloud implementations and AI-enabled delivery in a consulting context. He writes about the intersection of enterprise architecture, modern AI tooling, and practical delivery at guidibi.com.