Fix Vibe Code

AI coding tools have changed what a founder can do alone. With Lovable, Bolt, Replit, v0 or Cursor, you can go from idea to working product in a weekend, without hiring a single engineer. That is a real achievement, and often the fastest way to learn whether anyone wants what you are building.

Then the product meets real customers, and things start to slip. A fix in one place breaks something in another. The AI that wrote the code starts going in circles. Pages slow down as users grow. An investor asks who reviewed the security, and the honest answer is nobody. A developer looks at the codebase and says it would be easier to start again.

That is not a failure. It is what happens when software is built without anyone making the engineering decisions that keep it stable as it grows: how data is structured, who can access what, how errors are handled, and how changes are tested before they reach customers. The AI wrote the code. Nobody owned the judgement.

Fix Vibe Code is how we add that judgement. A senior Supernova team works out exactly what you have, fixes what is dangerous first, keeps everything that is sound, and turns your product into something you can safely sell, grow and hand to future engineers, without throwing away the progress you have made.

Signs your product needs help

Most founders recognise several of these:

• Every fix breaks something else. Changing one screen breaks another, and nobody can say why.

• The AI is going in circles. Prompts that used to work now undo earlier fixes or rewrite whole sections.

• You are afraid to deploy. There are no automated tests, no staging environment, and no easy way to roll back a bad release.

• It slows down as you grow. Pages that were instant for ten users take seconds for a thousand.

• Secrets are in the wrong place. API keys sit in the browser code, or the database lets any logged-in user read other people's data.

• Payments or logins are fragile. Customers get charged twice, webhooks fail silently, or password resets do not arrive.

• Your AI or cloud bill is climbing faster than your revenue, and you cannot see why.

• A due-diligence question stopped you. An investor, enterprise customer or partner asked about security, data protection or architecture, and you did not have an answer.

• A developer wants to start again. Every engineer who looks at the code recommends a rebuild, and you cannot judge whether they are right.

If two or three of these sound familiar, the product is carrying risk that will grow with every new customer. The good news is that most of it can be fixed without starting again.

Is this for you?

You are likely a good fit if you are:

• A non-technical founder who built the first version with Lovable, Bolt, Replit, v0, Cursor or similar tools, and is now stuck

• A startup with early users or revenue whose product has become unstable, slow or risky to change

• A team that inherited code from a freelancer or agency that has moved on, and cannot tell how good it is

• A founder preparing to raise who needs the product to stand up to technical due diligence

• A founder about to sign an enterprise customer who needs security, permissions and data handling done properly

It is not the right fit if:

• The idea itself is still unproven. If you do not yet know whether customers want it, start with Product Ideation & Discovery. Fixing the code of the wrong product is wasted money.

• You only want new features added to the existing code without addressing what is underneath. We will not stack new work on a foundation we know will fail.

• It is a large legacy enterprise system. That is a modernisation project, scoped separately.

The six-stage rescue framework

Every rescue follows the same six stages, in the same order: Assess → Stabilise → Secure → Restructure → Harden → Hand over. The order matters. We fix what can hurt your customers first and what slows your team down second, and we leave polish for last. Each stage ends with an exit gate we must pass before moving on.

Stage 1 — Assess

What do we actually have, and what is dangerous?

We never start fixing before we understand the product. In three to five days, a senior engineer reviews the whole system.

• Code and architecture review: how the product is structured, where the logic lives, what is duplicated and what is fragile.

• Security scan: exposed secrets, login and permission gaps, database access rules, vulnerable third-party packages.

• Data review: how data is stored and related, and whether it can grow without corrupting itself.

• Critical-flow walkthrough: we run sign-up, the core action and payments the way a customer would, and record what breaks.

• Platform and cost review: hosting, the database service (often Supabase or Firebase), third-party tools, and what is driving your AI and cloud bills.

Every issue is ranked by severity: critical (can hurt customers or the business now), high (will break as you grow), medium (slows the team down) or low (cosmetic).

What you get: a Rescue Report in plain language, a ranked risk register, our fix / refactor / rebuild recommendation, and a fixed-price plan for the work.

Exit gate: you understand exactly what is wrong, what it puts at risk, and what we propose, before you commit to anything more.

Stage 2 — Stabilise

Can we stop the product breaking?

First we put in the safety net that most AI-built products are missing.

• Version control so every change is tracked and can be undone.

• Backups of your database, tested by actually restoring them.

• Separate environments: a staging copy of the product where changes are tested before they reach customers.

• Error monitoring so we know about a failure before your customers tell you.

• Critical bug fixes in sign-up, login, the core action and payments.

Exit gate: the core customer journeys work reliably, and the team can see when something goes wrong.

Stage 3 — Secure

Is customer data and money safe?

Security issues are the most common, and most dangerous, problem in AI-generated code. They are also usually invisible until someone exploits them.

• Secrets: API keys and passwords moved out of the browser code and into secure storage, and rotated where they were exposed.

• Login and permissions: making sure users can only see and change what they are allowed to.

• Database access rules: closing rules that let any user read or edit other users' data.

• Input checks: every form and API checks what it receives, so bad data and common attacks are blocked.

• Payments and webhooks: verifying that payment notifications are genuine and cannot be faked or processed twice.

• Dependencies and privacy: patching vulnerable packages and reviewing how personal data is handled.

Exit gate: no critical or high security issue remains open.

Stage 4 — Restructure

Can the team change it without fear?

This is where we remove the tangle that makes every change risky. We work in priority order and keep everything that is sound. No patching, and no rewriting for the sake of it.

• A clear data model: data structured so that it stays consistent as features are added.

• Separated logic: business rules pulled out of screens and into one place, so a change is made once instead of in five copies.

• Duplication removed: the repeated, near-identical code that AI tools tend to generate.

• Automated tests on critical paths: sign-up, the core action and payments are checked automatically before every release.

• Consistent standards: naming, structure and error handling that any engineer can follow.

Exit gate: a change to one part of the product no longer breaks another, and the critical paths are covered by tests.

Stage 5 — Harden

Will it hold up as you grow?

We apply the same production-ready standard we use for every MVP: reliable, usable, secure and observable enough for your customers.

• Performance: slow pages and queries fixed, tested against the usage you expect next.

• Cost control: AI and cloud spend reduced through caching, smarter model use and right-sized hosting.

• Release pipeline: changes tested and deployed automatically, the same way every time.

• Rollback: a bad release can be reversed in minutes.

• Analytics verified: you can trust the numbers you show investors.

Exit gate: the product meets the production-ready standard, and no critical release blocker remains.

Stage 6 — Hand over

Can someone else safely own it?

A rescue is only finished when the product no longer depends on us, or on the AI tool, to survive.

• Documentation and an architecture map: how the system fits together, in language a new engineer can follow.

• A runbook: how to deploy, roll back, restore a backup and respond to an incident.

• A technical debt register: what we deliberately left for later, and what it will cost if ignored.

• A next-step roadmap: what to build, fix or hire for next.

Exit gate: an engineer who has never seen the product could safely maintain and extend it.

Fix, refactor or rebuild: an honest answer

The question every founder asks is whether to fix what they have or start again. Engineers who prefer clean slates often say rebuild. Agencies paid by the hour often say whatever keeps them busy longest. We decide from the evidence in the Rescue Report, and we tell you which way it points.

A rebuild is rarely the first answer, and never the default. When we do recommend a rebuild, we show you the numbers behind it, and it moves into our MVP Build & Launch process.

How we deliver

A small senior team. A technical lead owns every decision and reviews every change. Software engineers do the fixing and refactoring, using AI tools to move faster, but under senior review, never prompting blindly. QA tests each stage before it is released. A product lead joins when the fixes touch the customer experience or the roadmap.

You keep shipping while we fix. We work in small, tested releases behind feature flags (switches that let us turn a change on for some users first), so the product stays live and your customers are not disrupted. Urgent new features can continue alongside the rescue, built on the parts we have already made safe.

Typical timeline

Three moments you are in the room:

1. Rescue Report walkthrough: we show you what we found, what it puts at risk, and what we recommend, in plain language.

2. Weekly progress review: what was fixed, what was released, what we found along the way, and any decision we need from you.

3. Handover session: we walk you, and anyone you hire, through the product, the documentation and the roadmap.

What you leave with

The point of a rescue is not a tidier codebase. It is a product you can confidently sell, grow and hand to others. You leave with:

• A Rescue Report: an honest, plain-language picture of what you had and what it put at risk.

• A stable product: core journeys that work reliably, with monitoring that spots problems before customers do.

• A secure product: customer data, logins and payments protected, with a security checklist you can show investors and enterprise buyers.

• A codebase engineers can work with: a clear structure, consistent standards and automated tests on the paths that matter.

• Safe releases: a staging environment, an automatic release pipeline and one-click rollback.

• Lower running costs: AI and cloud spend brought under control.

• Full documentation: an architecture map, a runbook and a register of the debt we deliberately left for later.

• A next-step roadmap: what to fix, build or hire for next.

You own all of it, including the code, the documentation and the report, from day one.

Ways to work with us

Every rescue starts with the same small step. You decide what happens next once you have seen the report.

The audit fee is credited against the fix if you go ahead within 30 days.

How we price. Fixed scope and a fixed fee, agreed after the audit, so you know the full cost before the work starts. We do not sell open-ended hours. Anything new that appears mid-way is shown to you, priced and agreed before we do it.

Our promise. We will never promise bug-free software; nobody honestly can. We promise that you will know exactly what you have, that every critical risk we find will be fixed or clearly signed off by you, and that you will leave with a product you, and the next engineer, can safely build on.

What is not included unless scoped: new feature development beyond what the fix requires, a full redesign, formal penetration testing, compliance certification, legal advice, and ongoing maintenance after handover.

What we need from you: access to the code repository, the hosting and database accounts, the AI tool or platform the product was built on, and third-party services such as payments and email. We also need one person who can make decisions, and an honest account of what has been going wrong.

Keep the speed. Add the judgement.

AI coding tools did their job. They got you from idea to a working product faster and cheaper than was possible a few years ago. Using them was not a mistake, and you should keep using them.

What they cannot do is own the decisions that keep a product stable, secure and easy to change as it grows. That takes experienced engineers who know what to keep, what to fix first and what can wait.

That is what a rescue gives you: the speed you already had, with the judgement your product now needs. And when the product is safe and stable, the next step is usually growth. We can help with that too, through Iteration, Growth & Scaling, a Fractional CTO, or by building the engineering team that will own your product next.

Built it with AI? Let's make it last.