Built with Magic.dev?
Let's make sure it's production-ready.
Magic.dev builds autonomous coding agents with extremely large context windows designed to understand and generate complex, multi-file implementations. It targets enterprise-scale codebases where standard AI tools lose track of context. We help non-technical founders identify and fix the issues AI tools leave behind.
Common issues we find in Magic.dev code
These are real problems we see in Magic.dev projects during our audits — not hypotheticals.
Complex implementations that are difficult to maintain
Magic.dev's ability to generate large, multi-file implementations means it can produce sophisticated code that works but is hard for human engineers to understand, debug, or extend.
Security decisions made at scale without explicit review
When Magic.dev generates an entire feature spanning many files, security decisions — API authentication, data access patterns, input validation — are embedded throughout without a clear review surface.
Over-engineered solutions for straightforward requirements
Magic.dev tends toward comprehensive, extensible implementations. Simple CRUD operations may receive complex abstraction layers, generic type systems, and plugin architectures that add maintenance burden.
Dependency on Magic.dev's specific AI model for future changes
Complex generated codebases are easiest to modify by re-running Magic.dev with updated prompts. This creates dependence on continued access to their service for ongoing development.
Memory and compute assumptions from large context analysis
Implementations generated from large codebase context sometimes assume memory and compute availability that doesn't match your production environment.
Cross-file bugs from large-scale generation
Multi-file generation at scale introduces subtle inconsistencies between files — mismatched interfaces, incorrect type assumptions, and broken invariants that don't appear until runtime.
Generated tests don't cover cross-module interactions
Tests for individual files are generated, but the integration points between modules — where most bugs in complex systems live — often go untested.
Inconsistent naming conventions across generated files
At the scale Magic.dev operates, subtle naming inconsistencies accumulate — different conventions in different files, generic identifiers, and undocumented abbreviations.
How we can help with your Magic.dev project
From security reviews to deployment, we cover everything you need to go from prototype to production.
Security Review
Deep security analysis and hardening
Fix Bugs
Resolve issues and unexpected behavior
Deploy & Ship
Get your Magic.dev app to production
Refactor Code
Clean up AI-generated or legacy code
Performance
Make your Magic.dev app faster and more efficient
Add Features
New functionality, integrations, capabilities
Testing
Add tests and improve coverage
Infrastructure
Set up and manage your Magic.dev backend
Start with a self-serve audit
Get a professional review of your Magic.dev project at a fixed price. Results reviewed by experienced engineers.
Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 checks
- SSL/TLS analysis
- Security headers
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerabilities
- Code quality review
- Dependency audit
- AI pattern 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.
How it works
Tell us about your app
Share your project details and what you need help with.
Get a clear plan
We respond in 24 hours with scope, timeline, and cost.
Launch with confidence
We fix what needs fixing and stick around to help.
Frequently asked questions
Is Magic.dev suitable for production codebases?
Magic.dev is promising for complex, large-scale tasks. However, the generated output needs thorough review — particularly for security decisions and maintainability. Human engineers need to be able to work with the code without Magic.dev assistance.
How do I review a large Magic.dev-generated implementation?
Start with security surface area: auth, data access, and input handling. Then assess architecture for over-engineering. We provide structured reviews of Magic.dev output, including actionable simplification recommendations.
Can SpringCode simplify Magic.dev's over-engineered output?
Yes. We identify abstraction layers that add complexity without value and simplify them while preserving the functionality. The goal is code your team can maintain without re-running the AI.
What types of projects benefit most from Magic.dev?
Projects with genuinely complex requirements — multi-service architectures, complex business logic, or large migration tasks — benefit most. Simple CRUD apps don't need this level of tooling.
Can you add tests to a Magic.dev-generated codebase?
Yes. We add integration tests covering cross-module interactions and behavioral tests that verify the implementation meets requirements, not just that individual units run.
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Get your Magic.dev app production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.