Vibe-Code Rescue
It works on your machine.
Let's make it production-ready.
AI can get you to a working prototype in a weekend. Shipping it to real customers is a different job: security, data integrity, error handling, tests and deployment. We take what you've built and make it survivable.
Does this sound familiar?
Fast-built apps fail in predictable ways.
If you recognise more than two of these, an audit will pay for itself.
It works on your machine, and nowhere else.
Nobody can explain how the auth actually works.
The database schema drifted three months ago.
There are no tests, so every change is a gamble.
It demos beautifully and falls over under real traffic.
It was built fast by AI, and now it needs to ship.
Let us be fair
Vibe coding works. That is exactly the problem.
The tooling is excellent and the instinct to build first is a good one. What is missing is the layer that decides what has to be true before something ships.
The speed is real
A working prototype in a weekend is a genuine change. Ideas that would never have been funded now get tested.
The access is real
People with deep domain knowledge and no engineering background can build something that works. That is a good thing.
The exploration is real
Reacting to something running beats arguing about a specification. Discovery got dramatically cheaper.
Where it breaks
The same five categories, every time.
We audit AI-built codebases regularly. The failures are remarkably consistent, which is good news, because predictable means fixable.
Security
- Authorization checked in the interface but never on the server
- API keys and service tokens shipped inside the client bundle
- No rate limiting on login, signup or password reset
- User input concatenated into queries or rendered as raw HTML
Data
- No unique constraints, so duplicates are one double click away
- Migrations run by hand, so the schema drifts away from the code
- Relationships that exist only in the application's imagination
- A backup that nobody has ever restored
Correctness
- Only the happy path is handled
- No timeout or retry on any outbound call
- Non idempotent writes, so a retried payment charges twice
- A failure halfway through leaves data inconsistent
Operations
- Local and production environments that behave differently
- No rollback, so every deploy is one direction only
- No error tracking, so the first alert is a customer email
- A deploy that only works from one person's machine
Maintainability
- No consistent pattern for data, state or styling
- No tests, so every change is a gamble
- Nobody can explain why a decision was made
- The next AI change silently breaks the last one
If you keep vibe coding
Six habits that make AI-built software survivable.
None of this slows you down much. All of it prevents the failures above.
Design the architecture before you generate
Write down the data model, the auth model and where the trust boundaries are. A model given a clear structure produces far better code than one inventing structure as it goes.
Ground the model in your real codebase
Point it at real files, real schemas and real conventions. Most AI code drift comes from a model that does not know what already exists.
Ask for the failure path explicitly
Handle the timeout, the 500, the double submit, the empty state. If you never ask, it never happens.
Treat secrets as a design decision
Know which values are safe in the browser and which are not. A ten minute check prevents the most expensive category of incident.
Test where a break would hurt
Auth, payments, data integrity, and anything a customer makes a decision from. Not everywhere, just where it matters.
Deploy and observe like it matters
Reproducible builds, a one command rollback, error tracking and uptime alerts. Cheap on day one, painful to retrofit.
What production-ready actually means.
Not “it works”. These eight statements are true of software that can be trusted with real customers, real money and real data.
- Every protected endpoint checks authorization on the server
- No secrets in the client bundle or in git history
- Database constraints enforce what the code assumes
- Every outbound call has a timeout, and writes are idempotent
- Tests cover auth, payments and data integrity
- Reproducible builds with a one command rollback
- Errors and uptime monitored, with alerts that reach a human
- A new developer can find and change a feature from the README
The audit
What we look at.
A full read of the codebase against the things that decide whether software survives real users.
Security
Authentication, authorization, injection risks, exposed endpoints and the assumptions that stopped being true three iterations ago.
Secrets & configuration
API keys in the client bundle, credentials in git history, environments that differ between your machine and production.
Data integrity
Schema drift, missing constraints, migrations that were run by hand, and the records that quietly stopped matching the model.
Error handling
What happens when a third-party API is down, a request times out, or a user does something the happy path never considered.
Tests
Whatever exists, made trustworthy, then coverage where failures would actually hurt. Enough to change the code without holding your breath.
Performance
The N+1 queries, unbounded fetches and render-blocking work that never showed up in a demo with three rows of data.
Deployment
Reproducible builds, environment parity, rollback, and a deploy that isn't somebody's laptop.
Observability
Logging, error tracking and uptime monitoring, so you find out something broke before your customers tell you.
Architecture
Whether the structure can carry the next twelve months of features, or whether it's cheaper to change course now.
The path
Audit, stabilize, harden, hand over.
In that order. Fixing performance before fixing security is how rescues go wrong.
- 01
Audit
We read the whole codebase and give you an honest report: what's solid, what's risky, what's dead weight.
- 02
Stabilize
Security, data integrity, environment and deployment first, so it stops being fragile.
- 03
Harden
Tests, error handling, observability and performance, so it survives real users.
- 04
Hand over
Documented, monitored and maintainable, yours to run, or ours to keep improving.
The honest part
We won't tell you to throw away work that's fine. Most rescues keep the majority of the code and fix the parts that will hurt you. If a rewrite is genuinely cheaper, we'll say so, and show you why.
What you end up with.
Software you can change, deploy and trust, plus the documentation to prove it.
- A written audit: what's solid, what's risky, what's dead weight
- Prioritised fixes ordered by risk, not by effort
- Security holes closed and secrets rotated
- Data integrity restored and migrations made repeatable
- A test suite you can trust enough to change code
- Reproducible, rollback-capable deployment
- Error tracking and monitoring in place
- Documentation a new developer can actually follow
FAQ
Questions, answered honestly.
No sales spin. This is what people ask before they start working with us.
Get an honest read on your codebase.
Send us access. We'll come back with what's solid, what's risky, and what it takes to ship safely.