From Cursor to Production: The Vibe Coding Rescue Engineer Playbook

Your Vibe Coding application already looks like a product. There are screens, users, and maybe even paying customers. Then comes the stage where a small fix breaks three screens, production behaves differently from your laptop, and nobody is quite sure whether a secret key made its way into the browser.

This is exactly where a Vibe Coding Rescue Engineer comes in — a senior software engineer who takes a system built quickly with Cursor, Lovable, Bolt, Replit, Claude Code, or a similar tool, and moves it from an impressive result to a product you can operate, secure, and maintain.

This article is an expanded adaptation of the post From Cursor to production: a rescue playbook, with additional lessons from professional sources on securing AI-generated code.

What is a Vibe Coding Rescue Engineer?

The goal is not to replace your AI tools or to throw away what has already been built. The goal is to take engineering ownership of the gap between “it works in the demo” and “we can rely on it in production”.

A rescue engineer typically reviews six areas:

1. Architecture and maintainability — are there clear boundaries between components, or does every change ripple through the whole system?
2. Identity and authorisation — is enforcement happening on the server and in the database, rather than by hiding a button in the UI?
3. Secrets and data — are API keys, tokens, and sensitive information stored in the right place?
4. Testing — are the critical flows tested automatically before deployment?
5. Operations — are there logs, monitoring, alerts, and a safe way to roll back to a previous version?
6. Performance and cost — will queries, API calls, and AI model usage hold up under real load?

Why an MVP that looks finished still isn’t production-ready

AI tools excel at completing the task in front of them. Ask for a sign-up form and they will try to produce a working sign-up form. But they don’t always hold the full organisational context: permission policies, privacy requirements, budget limits, service-level agreements, or failure scenarios.

In The VibeSec Reckoning, the Thoughtworks team describes how, while scaling up a prototype, an AI tool suggested making storage public and granting a service account overly broad permissions. In both cases a person who asked the right question stopped the risk before it went live.

A prompt asking the model to be secure provides guidance, but it does not enforce security. Production needs tests, scans, authorisation rules, and deployment policies enforced outside the model’s control.

A five-stage rescue process

1. Freeze changes and map the system

Before fixing anything, pause the stream of new features for a moment. Build a reliable picture of the system: repositories, environments, third-party services, tables, user roles, payments, and critical business processes.

The deliverable is not a long slide deck, but a short operational map that explains:

• what goes into the system and what comes out of it;
• where sensitive information is stored;
• which actions change money, permissions, or customer data;
• what must keep working during the rescue;
• who has access to each environment.

2. Triage risks by impact

You don’t start by cleaning up variable names. You start with whatever could expose information, harm customers, or take the business offline.

Priority	Examples	First action
Critical	Secret key in the browser, open database, admin route without authentication	Block, rotate keys, and fix permissions
High	Payments without webhook verification, no backup or restore	Protect the process and add tests
Medium	Duplicate dependencies, copy-pasted code, partial error handling	Incremental refactoring
Low	Inconsistent design, lint warnings, unclear names	Handle after the core is stable

This ranking preserves business momentum. It also makes it possible to decide, on evidence, whether to fix, replace a specific component, or — only in exceptional cases — rebuild part of the system.

3. Harden identity, permissions, and secrets

Look for authorisation checked only on the client, missing database access controls, secret service keys in frontend code, and overly broad cloud permissions. For Supabase tables exposed through the Data API, this includes checking Row Level Security policies.

At this stage you:

• rotate exposed keys and move secrets into a secrets manager or server-side environment variables;
• apply least privilege to every user and service;
• test every protected endpoint while signed out, as a regular user, and as an administrator, including attempts to access another user’s records;
• verify webhook signatures and prevent duplicate processing;
• add secret and dependency scanning to the CI pipeline.

Automated tools help, but they don’t replace human review. In its July 2026 announcement, GitHub introduced a security review command in public preview for the Copilot app. It looks for issues such as injection, cross-site scripting (XSS), unsafe data handling, and weak cryptography, complementing code scanning, Dependabot, and secret scanning.

4. Wrap the core in tests and observability

There’s no need to reach perfect test coverage straight away. Start with the paths that must never break:

• sign-up, sign-in, and password reset;
• creating an order or a payment;
• view and edit permissions;
• writes to the database;
• integration with a third-party service;
• an AI flow that produces a decision or changes business state.

For each path, add a success test, an expected-failure test, and a log that makes it possible to understand what happened. Then set up health checks, error monitoring, response-time metrics, and alerts on unusual increases in cost or failure rate.

5. Release gradually and document what comes next

A rescue is only finished when the team can keep developing without depending on the rescuer. That means a staged deployment, with backups, a rollback plan, and a post-release checklist.

The handover includes at least:

• a short diagram of the architecture and the critical flows;
• run and deployment instructions;
• a list of required secrets — without the values themselves;
• key technical decisions and the reasoning behind them;
• a prioritised backlog of remaining debt and risks;
• working rules for the AI tools, plus tests that block an unsafe change.

Fix or rebuild?

Rewriting the whole system can cost more than targeted repairs. A UI that has already been tested with users, business logic that works, and reliable integrations are assets worth keeping.

Consider rebuilding a component only when at least one of the following holds:

• you cannot prove where the data-access boundaries are;
• there is no way to make a change without taking the system down;
• the current structure blocks a basic business requirement;
• the cost of testing and fixing is clearly higher than a controlled replacement;
• dependence on a platform or library creates a risk you cannot reduce.

Where practical, replace components gradually: migrate one flow, measure the result, and then continue. This can keep the product available while limiting the impact of each change.

How do you know you need a Vibe Coding Rescue?

These signs justify a closer review. A single serious issue, such as an exposed secret or missing access control, calls for immediate action:

• every AI fix creates a fault somewhere else;
• nobody knows which keys were exposed and which are still active;
• there are real users, but no tests for the critical paths;
• development works and production fails;
• there is no clear ownership of permissions, backups, or incidents;
• another engineer cannot safely change or deploy the system without undocumented knowledge;
• usage is growing, but costs and response times are unpredictable.

Summary: keep the speed, add engineering accountability

Vibe Coding is an excellent way to prove an idea quickly. Rescue engineering isn’t a punishment for that speed — it’s the stage where initial success becomes a business asset you can keep building on.

The right order is simple: map the system, rank the risks, close the gaps, protect the critical flows with tests, improve observability, and release gradually. That keeps what already works and replaces only what is genuinely risky or fragile.

Built a product in Cursor, Lovable, Bolt, Replit, or Claude Code and unsure whether it’s ready for real users? Read about our Vibe Coding Rescue service or talk to us about a focused code review.

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Sources and further reading:

• From Cursor to production: a rescue playbook — AiHIRE
• The VibeSec Reckoning — Martin Fowler / Thoughtworks
• Security reviews in GitHub Copilot — GitHub Changelog
• Vibe Code Rescue: failure patterns and recovery workflow