From idea to app in a day: the full flow, step by step

Step 1: define the problem before you ask for anything

The most common mistake is starting with the app. Before writing a prompt, answer three questions: who the user is, how they handle that task today, and what data the app needs and where that data lives now. The questions are simple, but the answers decide the structure of the product.

Addy Osmani, in his book “Beyond Vibe Coding”, contrasts exploratory vibe coding (describe what you want and let the model fill in the blanks) with an intent-driven way of working, where you set clear goals and constraints and critically review what the AI generates (O’Reilly, Beyond Vibe Coding). Setting goals and constraints starts with writing them down. For a one-day idea, one page is enough: user, task, three rules and what it means for the thing to work. A workable format is in how to write a PRD an agent can understand.

Step 2: generate in small blocks

Asking for the whole app in one prompt produces something hard to review. It is better to split the work into blocks: first the main screen with test data, then saving, then user access. Test each block before moving to the next. If something breaks, you know what broke it. It is the same logic as iterating with prompts without losing control.

Step 3: review data and access

This is the step most often skipped when everything moves fast. In an app that talks to the database from the browser, the database must decide who sees what. Supabase’s documentation explains this with Row Level Security: policies act like an extra filter on every query. Without those rules, an exposed table can be readable or writable by any role with grants, and in projects with default grants, new tables in the public schema can be open to anon and authenticated (Supabase, Row Level Security). Supabase is changing that default so that exposing a table to the API becomes an explicit decision (Supabase, Securing your API), but projects that already exist keep their current grants: do not assume it, check it in your project.

In practice, at this stage check:

• that every table has active access rules;
• that no secret lives in client-side code;
• that two different users see only their own data;
• what personal data the app stores and for how long.

Step 4: deploy and verify

Deploying means publishing the app at a URL reachable from the internet. Current platforms usually create a preview deployment for each change and a production deployment that can be promoted or rolled back. Vercel, for example, documents preview and production deployments from Git or its CLI (Vercel, Deploying to Vercel). It also lets you promote a preview deployment to production and do an instant rollback, which reassigns your domains to a previous deployment without rebuilding it (Vercel, Instant Rollback). If you use another platform, look for those two features before choosing it.

Before promoting a change to production, open the preview URL, test the main flow with a real account and check the error logs. If something fails, the previous deployment should be able to come back.

Example

Illustrative example: a designer wants an app so her team can log returns of prototypes to clients. In the morning she defines the problem (who logs, which fields, which states) on one page. She asks for the screen with test data and then for saving. In the afternoon she checks that each user sees only their own records and that the service key does not appear in the browser code. She publishes a preview, tests with two colleagues and promotes it to production. The flow fits in a day because the scope is small and the tests are concrete.

When does it not fit in a day?

When the app stores client data, processes payments, needs complex roles or integrates with other systems. Those cases need engineering review, which can take days. See when not to vibe code for the criteria. Osmani himself warns that the exploratory approach carries a serious risk: it can drift off course quickly, which is why he insists on critically reviewing what the AI generates.

How to apply it tomorrow

1. Write the idea on one page with three fields: user, task and success criterion. If you cannot fill a field, that part stays out of the day.
2. Split the work into three one-hour blocks: a screen with test data, saving and access. Close each block with a test that passes or fails.
3. Before deploying, check three things: database access rules, secrets kept out of browser code and a test account that is not your own.
4. Publish a preview first, test it with someone who did not build it, and only then promote it to production.

If at the end of the day you have a working URL and a list of what is missing, the experiment worked.

Before closing the day, write on a page what comes next: what is missing, who will review it and what real data the app needs. That page is the difference between a prototype that gets abandoned and one that becomes a product with an owner.

Common mistakes

• Starting to generate without defining the problem or the data.
• Asking for the whole app in a single prompt.
• Leaving database access rules for later.
• Publishing straight to production without a preview.
• Confusing “it is deployed” with “it is ready for users”.
• Having no way to return to the previous version if something fails.

Sources

• Addy Osmani, “Beyond Vibe Coding” (O’Reilly): https://www.oreilly.com/library/view/beyond-vibe-coding/9798341634749/
• Supabase, “Row Level Security”: https://supabase.com/docs/guides/database/postgres/row-level-security
• Supabase, “Securing your API”: https://supabase.com/docs/guides/api/securing-your-api
• Vercel, “Deploying to Vercel”: https://vercel.com/docs/deployments
• Vercel, “Instant Rollback”: https://vercel.com/docs/instant-rollback