// AI Agent Playground

Test drive production-ready AI agents. Real implementations with error handling, caching, and fallbacks.

⚡ <100ms response 🛡️ Error boundaries 💰 Cost optimized

Choose an Agent

Code Review Agent

Automated code review focusing on bugs, security, and best practices.

Review Results

👆 Paste some code and click "Analyze Code" to see the AI review.

Try introducing a bug or security issue to see how the agent responds!

Try These Examples:

Debug Assistant

Helps identify and fix errors with step-by-step guidance.

🐛 Paste an error message to get debugging help.

Architecture Advisor

Get recommendations for system design and architecture decisions.

Constraints:

🏗️ Describe your system requirements to get architecture recommendations.

Performance Optimizer

Analyze and optimize code for better performance.

⚡ Paste code to get performance optimization suggestions.

// Under the Hood

🛡️ Error Boundaries

Every agent has fallback strategies. If the primary model fails, we gracefully degrade to cached responses or simpler models.

💰 Cost Optimization

Smart routing sends simple queries to GPT-3.5, complex ones to GPT-4. Semantic caching reduces duplicate API calls by 90%.

⚡ Low Latency

Response streaming, edge caching, and parallel processing keep responses under 100ms for cached queries.

📊 Real Metrics

Every response shows actual model used, cache hit status, and latency. No magic, just good engineering.

Note: This playground uses production patterns but with rate limiting for demo purposes. View the source code to implement in your own projects.