AI system design
Practice this questionWANT TO UNDERSTAND THE CONCEPT FIRST?Learn AI system design
Beginner — What questions come before architecture?
- What task should succeed, which data is authoritative, who may access it, what errors are costly, how fast it must respond, expected load, and available budget.
- Then decide whether deterministic code or AI is needed.
Intermediate — How do you scale agent traffic?
- Estimate provider/tool call amplification, use admission controls and tenant quotas, isolate background work, and scale workers to real dependency capacity.
- More API replicas do not remove provider token limits or serialize conflicting thread updates automatically.
Senior — How do you design degraded behavior?
- Define acceptable alternatives per task: verified templates, search results, paused durable work, or staff escalation.
- Preserve data/permission/quality contracts and distinguish missing evidence, service failure, and unknown commit outcomes explicitly.
Scenario — Design an insurance assistant in two minutes.
- Use Next.js and an authenticated Node API, a bounded intent router, policy RAG, and authorized claim tools.
- Put draft validation, exact approval, and idempotent submission in deterministic services/workflows.
- Add scoped memory, durable state where needed, redacted tracing, source/outcome evaluations, and per-tenant budgets.
- Start with one assistant; justify any extra agents or MCP integration through real requirements.
Adapted from 13_AI.MD · “29.21 AI system design”. Code examples are study fragments. Difficulty and core labels are editorial estimates; version-specific behavior should be checked against your project.