Module 17
AI System Design & Architecture
Design AI-native products that scale to millions
Lessons
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17.1
AI System Design Patterns
Locked60 min
17.2
Multi-Modal AI Architecture
Locked75 min
17.3
AI Observability & Operations
Locked60 min
17.4
Scaling AI Infrastructure
Locked55 min
Expert Lens
Founder
Think like a founder: what user pain, distribution channel, pricing, and retention loop does this AI capability unlock?
Systems
Think like a first-principles systems builder: separate demos from durable products, and measure the bottleneck the model actually removes.
Infrastructure
Think like an AI infrastructure leader: account for data, latency, cost, reliability, evaluation, and deployment constraints before scaling.
Objectives
- Design scalable AI systems from first principles
- Architect multi-modal AI products
- Build observable, maintainable AI infrastructure
- Lead technical AI strategy at any scale
Capstone
AI Architecture Document
Complete system design document: architecture diagrams, data flow, scaling strategy, observability plan, and cost model.
A technical architecture document any engineering team could execute.
Real Examples
- Design an AI assistant with authentication, retrieval, tool permissions, evals, monitoring, and fallback paths.
- Choose between fine-tuning, RAG, prompt engineering, workflow automation, and human review before building.
- Document model calls, data flow, access rules, evaluation data, and deployment assumptions.
Mastery Checks
- Explain the core concept without buzzwords.
- Build a small working artifact, not just a note or prompt.
- Define an evaluation rubric and test against at least five edge cases.
- Estimate operational cost, failure modes, and human review requirements.