Built a ai wrapper / llm app with Claude Code?
We'll make it production-ready.
AI wrapper apps — products built on top of OpenAI, Anthropic, or other LLM APIs — have unique production challenges. The AI model is a black box that's slow, expensive, and unpredictable. Your app needs to handle variable response times, API failures, cost management, and output quality control in ways that standard web apps don't.
AI Wrapper / LLM App challenges in Claude Code apps
Building a ai wrapper / llm app with Claude Code is a great start — but these challenges need attention before launch.
API cost management
LLM API calls are expensive. A single unoptimized prompt can cost cents per request — which adds up fast with real users. You need token counting, cost tracking, usage limits per user, and prompt optimization to stay profitable.
Response time variability
LLM responses take 1-30 seconds depending on prompt complexity, model load, and output length. Your UI needs streaming responses, loading states, and timeout handling. Users abandon apps that feel slow.
Error handling for AI responses
The AI model might: return an error, time out, return malformed output, refuse to answer, or hallucinate. Each case needs specific handling. AI tools build the happy path but not the many failure modes.
Prompt injection and security
Users can manipulate your AI's behavior through carefully crafted inputs — making it ignore instructions, reveal system prompts, or produce harmful output. Input sanitization and output validation are essential.
Rate limiting and queuing
LLM APIs have rate limits. When many users make requests simultaneously, you need a queue system to manage the flow and provide feedback to waiting users. Without this, users get API errors during peak usage.
Output quality control
LLM responses aren't deterministic — the same prompt can produce different quality results. You need output validation, retry logic for poor responses, and potentially human review for critical outputs.
What we check in your Claude Code ai wrapper / llm app
Common Claude Code issues we fix
Beyond ai wrapper / llm app-specific issues, these are Claude Code patterns we commonly fix.
Over-permissive CORS configuration
Claude Code sometimes sets CORS to allow all origins during development and forgets to restrict it for production, allowing any website to make API requests.
Missing rate limiting
API endpoints are generated without rate limiting, allowing attackers to brute-force auth endpoints or abuse expensive operations.
Over-engineered abstractions
Claude Code creates multiple layers of abstraction, generic utilities, and design patterns for simple problems — making the code harder to understand and maintain.
Edge cases in complex logic
While Claude handles the main flow well, complex conditional logic sometimes has edge cases that produce incorrect results with unusual inputs.
Start with a self-serve audit
Get a professional review of your Claude Code ai wrapper / llm app at a fixed price.
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.
Frequently asked questions
Can I build a ai wrapper / llm app with Claude Code?
Claude Code is a great starting point for a ai wrapper / llm app. It handles the initial scaffolding well, but ai wrapper / llm app apps have specific requirements — api cost management and response time variability — that need professional attention before launch.
What issues does Claude Code leave in ai wrapper / llm app apps?
Common issues include: over-permissive cors configuration, missing rate limiting, over-engineered abstractions. For a ai wrapper / llm app specifically, these issues are compounded by the need for api cost management.
How do I make my Claude Code ai wrapper / llm app production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most Claude Code-built ai wrapper / llm app apps, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.
Get your Claude Code ai wrapper / llm app production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.