AI Architecture
Design systems that integrate AI components effectively. Learn patterns for AI service integration, model selection, cost management, and scalable AI infrastructure.
What You'll Learn at Each Tier
Write effective single-turn prompts and generate working code for isolated functions. Understand basic AI tool capabilities and limitations.
Apply AI tools across multi-file features. Manage context windows, iterate on outputs, and integrate AI-generated code into existing codebases.
Orchestrate AI across full feature implementations including data layer, API, and tests. Design effective prompt chains and evaluation criteria.
Architect AI-integrated applications with auth, billing, and deployment. Manage AI costs, implement caching strategies, and design fallback patterns.
Design multi-service AI architectures. Coordinate AI across monorepos, implement cross-service AI workflows, and build organization-scale AI strategies.
Sample Challenge
Tier 2 Challenge Preview
Design the architecture for an AI-powered code review system. Define the component diagram, data flow for a pull request review, model selection rationale, and caching strategy for repeated file patterns.
Evaluation Criteria
- - Component separation
- - Data flow completeness
- - Cost optimization strategy