Build AI features that hold up in production.
What it does
Guides development of production-ready AI features through LLM integration, retrieval design, prompt engineering, and cost control.
When to use it
Use when the request clearly matches its AI product development capabilities and patterns.
How to use it
It changes how the agent develops AI features by requiring output validation and versioned, tested prompts.
What you provide
- An existing project
What you need · 6
Routes backend implementation to backend, including backend integration for AI features and vector storage for RAG; an installation requirement is unstated.
Routes UI, component, streaming, and chat implementation to frontend; an installation requirement is unstated.
Routes cost, billing, usage, and optimization work to devops for monitoring; an installation requirement is unstated.
Routes security, PII, and data protection work to security when AI handles sensitive data; an installation requirement is unstated.
Access · 0
No additional actions listed.