Built a mvp / prototype with GitHub Copilot?
We'll make it production-ready.
You built a prototype with an AI tool and it works — on your machine, with your test data, for the happy path. Now you need real users to validate your idea. The goal isn't perfection — it's getting to a state where real people can use it safely and reliably. That means fixing the critical gaps without over-engineering.
MVP / Prototype challenges in GitHub Copilot apps
Building a mvp / prototype with GitHub Copilot is a great start — but these challenges need attention before launch.
Identifying what actually needs fixing
Not everything needs to be production-grade for an MVP. The challenge is knowing which shortcuts are acceptable (visual polish, advanced features) and which aren't (security, data loss, broken core flows). Our audit prioritizes fixes by impact.
Security minimum
Even an MVP handles user data. You need authentication that works, data isolated per user, no exposed secrets, and HTTPS. You don't need enterprise-grade security, but you need the basics done right.
Deployment
Your app runs locally but deploying it involves environment variables, domain configuration, SSL, and build optimization. First-time deployment is where most AI prototypes hit unexpected issues.
Error handling
When something goes wrong (and it will), your users should see a helpful message — not a white screen or a raw error. Basic error handling is the difference between 'this app is buggy' and 'something went wrong, please try again.'
Core flow reliability
Your main user flow (signup → core action → outcome) must work every time. Edge cases in secondary flows can wait, but the core path needs to be solid for your MVP to generate valid learnings.
What we check in your GitHub Copilot mvp / prototype
Common GitHub Copilot issues we fix
Beyond mvp / prototype-specific issues, these are GitHub Copilot patterns we commonly fix.
Insecure code patterns from training data
Copilot sometimes suggests patterns from its training data that are known to be insecure — like using eval(), innerHTML, or outdated crypto functions.
Hardcoded secrets in suggestions
Copilot occasionally suggests placeholder API keys or credentials that look real and get committed to version control.
Inconsistent code style across files
Different completions use different patterns — sometimes callbacks, sometimes async/await, sometimes .then(). The codebase becomes inconsistent over time.
Subtly incorrect logic
Copilot completions often look correct but contain off-by-one errors, wrong comparison operators, or missed edge cases that cause intermittent bugs.
Start with a self-serve audit
Get a professional review of your GitHub Copilot mvp / prototype at a fixed price.
External Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 vulnerability check
- SSL/TLS configuration analysis
- Security header assessment
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerability analysis
- Code quality review
- Dependency audit
- Architecture review
- Expert + AI code analysis
Complete Bundle
Both scans in one package with cross-referenced findings.
- Everything in both products
- Cross-referenced findings
- Unified action plan
100% credited toward any paid service. Start with an audit, then let us fix what we find.
Frequently asked questions
Can I build a mvp / prototype with GitHub Copilot?
GitHub Copilot is a great starting point for a mvp / prototype. It handles the initial scaffolding well, but mvp / prototype apps have specific requirements — identifying what actually needs fixing and security minimum — that need professional attention before launch.
What issues does GitHub Copilot leave in mvp / prototype apps?
Common issues include: insecure code patterns from training data, hardcoded secrets in suggestions, inconsistent code style across files. For a mvp / prototype specifically, these issues are compounded by the need for identifying what actually needs fixing.
How do I make my GitHub Copilot mvp / prototype production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most GitHub Copilot-built mvp / prototype apps, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.
How much does it cost to fix a GitHub Copilot-built mvp / prototype?
Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger mvp / prototype projects, we provide a custom fixed quote after the audit — no hourly billing.
Get your GitHub Copilot mvp / prototype production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.