Buyer Guides · 7 MIN
Lovable to production: what to fix before real users arrive
Built an app in Lovable? What to check before real users arrive: code ownership, database access rules, secrets, payments, tests, monitoring and maintenance.
A Lovable app is ready for production when you own the code in your own repository, every database table has access rules, no secret key is exposed in the browser, payments and emails run on server-side code, the main user flows have tests, and someone is watching errors after launch. Lovable gets you a working product fast. Production is the work that keeps it working when strangers, money and personal data show up.
- Sync the project to your own GitHub repository first, so the code is yours and can be reviewed, tested and deployed outside Lovable.
- Lovable apps often use Supabase. Supabase's own docs say a table in an exposed schema without Row Level Security is readable and writable by any role with a grant on it.
- Run Lovable's built-in security scans, then have an engineer review what they cannot see: business logic, permissions and payment flows.
- Add tests for the three to five flows that make or lose money, and error monitoring before launch day.
- Decide who maintains the app after launch, because prompts alone do not handle incidents.
- Nactore is a technology and growth company that takes prototypes to production and then helps them find users.
Why does a working prototype still need work?
A prototype proves the idea: the screens make sense and the main flow works for the person who built it. Production has to survive things a demo never meets: users who type unexpected input, people trying to read data that is not theirs, payment webhooks that arrive twice, and a database that grows from fifty rows to fifty thousand.
None of this means the prototype was a mistake. Building the first version with an AI app builder is a fast way to find out whether anyone wants the product. The gap is in what the builder is optimized for (getting something on screen) versus what production needs (staying correct and safe under real use).
Six steps from prototype to production
Step 1: own the code
Lovable's GitHub integration lets you export and two-way sync your project with GitHub, so you can back up the code, review changes in pull requests, work locally and deploy outside Lovable. Do this before anything else.
Once the code is in your repository:
- Turn on branch protection so changes land through pull requests.
- Add CI that installs, builds and runs tests on every change.
- Write a short README with how to run it locally. If nobody can run it outside the builder, nobody can fix it at 2 a.m.
Step 2: lock down the database
Many Lovable projects store data in Supabase, which is Postgres with an API in front of it. The browser talks to that API directly, so the database's own rules decide who can read what.
Supabase's Row Level Security guide is blunt: a table in an exposed schema without RLS is readable and writable by any role with a grant on it, and you should enable RLS on every table in an exposed schema. Row Level Security (RLS) is a set of rules inside the database that says, row by row, who may read or change it.
Check each table:
| Question | What good looks like |
|---|---|
| Is RLS enabled? | Yes, on every table the app can reach |
| Can a logged-out user read it? | Only if the data is meant to be public |
| Can user A read user B's rows? | No, policies compare the row's owner to the signed-in user |
| Can a user change their own role or plan? | No, those columns are only written by server code |
Test this with two real accounts, not by reading the policy and nodding. Sign in as user A and try to fetch user B's records.
Step 3: move secrets and money to the server
Anything shipped to the browser can be read by anyone who opens developer tools. OWASP's secrets management guidance warns that many organizations have secrets hardcoded in source code in plain text.
- Public keys only in the browser. Supabase's API key guide says the publishable key (the older anon key) can be shipped because Row Level Security limits what it reaches, while the secret key (the older service_role key) bypasses Row Level Security and must never leave your control. The same goes for payment and email provider secret keys.
- Payments on the server. Create checkout sessions and verify webhooks in server-side functions, and treat the webhook, not the redirect page, as proof of payment.
- Rotate anything that leaked. If a secret was ever in a commit, assume it is known and replace it.
Step 4: run the scans, then review what scans miss
Lovable's security docs describe two built-in scans, Quick scan and Deep scan, plus optional connectors such as Wiz for dependency and static code analysis. Run them and fix what they find.
Then have an engineer review the parts a scanner cannot judge:
- Business rules. Can a user apply the same coupon twice, or book a slot that is already taken?
- Authorization in server functions. Does each function check who is calling, or trust whatever the browser sends?
- File uploads. Size limits, file types, and whether uploaded files are private.
OWASP's Top 10:2025 keeps broken access control at number one and reports that 100% of the applications it tested had some form of it. That is the category most worth an expert hour.
Step 5: test the flows that matter
You do not need full test coverage before launch. You need the flows that make or lose money to be checked automatically:
- Sign up and sign in.
- The core action users come for.
- Checkout and the payment webhook.
- Anything that sends email or messages to customers.
- Account deletion, if you handle personal data.
End-to-end tests that click through these in a real browser catch most regressions when someone, human or AI, changes the code later.
Step 6: watch it after launch
- Error monitoring on the frontend and server functions, with alerts to a person.
- Uptime checks on the main pages and the API.
- Backups with a restore you have actually tried once.
- Logs that leave out personal data and secrets.
Rebuild or harden?
Most Lovable apps can be hardened instead of rebuilt. Rebuilding makes sense when the data model is wrong for where the product is going, when core logic lives only in the browser and cannot be moved cleanly, or when performance falls apart at realistic data sizes. Our prototype to production checklist covers the same decision for AI features.
Frequently asked questions
Is a Lovable app secure by default?
It includes security scans and uses established services, but your access rules and business logic are specific to your app. Someone has to check them for your data.
Do I have to leave Lovable to go to production?
No. Syncing to GitHub lets engineers work in the same code while you keep using Lovable for some changes. Agree on who changes what to avoid conflicts.
How long does hardening take?
It depends on the number of tables, integrations and user roles. A review of the database rules, secrets and payment flow is the first step, and it tells you the size of the rest.
What about compliance like GDPR?
Data protection rules apply to your app regardless of how it was built. Map what personal data you collect and why, and confirm obligations with counsel.
From working demo to working business
A prototype that people want is the hard part. Making it safe and reliable is engineering work with a known shape. Nactore takes AI-built apps from prototype to production: code ownership, database rules, payments, tests and monitoring, then helps the product find its users.
Want your app reviewed before launch? Book a free 30-minute call.
Want to apply this to your business?
Book a free 30-minute call. We will tell you what we would do first.