Beyond AI-assisted development, building applications with AI at the core is becoming standard. Learn how to architect AI-powered applications effectively.
Components of AI Applications
- Language models for reasoning
- Vector databases for semantic search
- Retrieval-augmented generation (RAG) systems
- Agent frameworks for autonomous behavior
- Feedback loops for continuous improvement
- Monitoring systems for reliability
Architecture Patterns
API-First: Use AI through cloud APIs for simplicity
Self-Hosted: Run models locally for privacy and control
Hybrid: Use cloud for complex operations, local for privacy-critical
Essential Considerations
- Cost management (API calls add up)
- Latency and responsiveness
- Hallucination prevention
- Safety and content filtering
- Monitoring and logging
- User feedback integration
Tools and Frameworks
LangChain, AutoGPT, HuggingFace Transformers, and LLaMA Index simplify AI application development significantly.
Keywords: AI application development, LLM integration, AI architecture, AI software