Web Development · Intermediate
Generative AI App Integration
Build production-ready integrations between generative models and your applications. You will design prompt pipelines, implement retrieval-augmented flows, and ship a capstone that demonstrates secure API usage. Mentors review each integration milestone with written feedback on architecture and error handling.
Features
- OpenAI and open-weight model API patterns
- RAG pipeline design with vector stores
- Prompt versioning and evaluation harnesses
- Rate limiting and cost monitoring dashboards
- Human-in-the-loop review workflows
- Deployment to containerized environments
Outcomes
- Ship a working LLM-powered feature with documented API contracts
- Demonstrate observability for token usage and latency
- Present a capstone reviewed by a senior integration mentor
Min-jun Park
Former platform engineer; led API integrations at a Busan SaaS startup.
FAQ
Solid JavaScript or Python fundamentals are required. Deep learning theory is not a prerequisite; we focus on integration patterns.
Reviews
"The RAG lab in week 6 finally made chunking strategies click. My capstone routes support tickets through a reviewed prompt chain—not perfect, but deployable."
"Mentor notes on my rate-limiter implementation saved a week of debugging. Clear material on streaming responses."