Built with Continue?
Let's make sure it's production-ready.
Continue is an open-source AI coding assistant for VS Code and JetBrains that connects to various LLM providers. It offers flexibility in model choice but code quality varies depending on the underlying model used. We help non-technical founders identify and fix the issues AI tools leave behind.
Common issues we find in Continue code
These are real problems we see in Continue projects during our audits — not hypotheticals.
Model-dependent security quality
Security of generated code varies dramatically based on which LLM is connected. Some models produce much less secure code than others.
Inconsistent code patterns between models
Switching between models mid-project produces inconsistent patterns, naming conventions, and error handling approaches in the same codebase.
Context window limitations causing bugs
When the codebase exceeds the model's context window, Continue loses awareness of existing patterns and introduces contradictory code.
Missing performance best practices
Generated code often uses naive algorithms and data structures. Database queries, API calls, and data processing lack optimization.
No deployment tooling generated
Continue focuses on application code and doesn't generate Dockerfiles, CI/CD configs, or deployment scripts.
Inconsistent test quality
Test quality depends on the connected model. Some models produce comprehensive tests, others generate tests that barely cover the happy path.
Outdated patterns from older models
Older or cheaper models suggest deprecated APIs, outdated library usage, and patterns that don't align with current best practices.
Lack of project-wide consistency
Without strong project context, Continue generates code that works in isolation but doesn't follow the project's established patterns.
How we can help with your Continue 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 Continue app to production
Refactor Code
Clean up AI-generated or legacy code
Performance
Make your Continue app faster and more efficient
Add Features
New functionality, integrations, capabilities
Testing
Add tests and improve coverage
Infrastructure
Set up and manage your Continue backend
Start with a self-serve audit
Get a professional review of your Continue 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
Does the LLM choice matter for code quality?
Significantly. Different models produce very different code quality, especially for security-sensitive operations. We audit regardless of which model you used.
Can you fix inconsistencies from switching models?
Yes. We standardize code patterns, naming conventions, and error handling across the codebase to create a consistent, maintainable project.
Is Continue better than proprietary AI tools?
Continue offers flexibility and privacy (you control the model). Code quality depends on the model used. Either way, review before deploying.
Can you review a Continue-assisted project?
Yes. We look for model-dependent issues, pattern inconsistencies, and security gaps regardless of which models were used during development.
How do I choose the right model for Continue?
For security-sensitive code, use the most capable model available. For routine code, faster models work fine. We can review your model choice and its impact on code quality.
Related resources
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Get your Continue app production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.