Track
▦ AI System Design
A repeatable framework for the AI system design interview: clarify requirements, define evals, choose the AI core (prompt vs RAG vs agent vs fine-tune), then design ingestion, retrieval, agents, scaling, cost/latency math, safety and observability — ending on a full worked case study. Built for AI-engineer, applied-AI and staff interviews.
Readiness0%
Lessons0/13
Cards mastered0/23
Focused study107 min
Roadmap
5 modules1
Framework
2
RAG
3
Agents
4
Scale & Cost
5
Reliability
Modules
clear 60% to unlock the next▦MODULE 01
The Framework
A repeatable structure so you never freeze on 'design me an AI system'.
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◫MODULE 02 · 🔒
Designing RAG Systems
Ingestion to retrieval to eval — the most-asked AI design problem.
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⛓MODULE 03 · 🔒
Designing Agentic Systems
Tools, orchestration, guardrails — and when NOT to build one.
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◇MODULE 04 · 🔒
Scaling, Cost & Latency
The token-budget math and routing that make LLM systems affordable.
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◈MODULE 05 · 🔒
Reliability, Safety & Observability
Retries, prompt injection, PII, tracing — then a full case study.
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