Quiz
2667 questions of the kind that actually get asked — in interviews, in architecture review boards, and by the person who has to run the thing at 3 AM. Every answer states the trade-off rather than the slogan, and says when the obvious choice is the wrong one.
All areas2667
Architecture Fundamentals81
Distributed Systems101
Data Architecture90
Cloud Architecture87
Networking86
API & Integration Architecture78
Reliability & Resilience88
Observability81
Performance & Capacity Engineering90
Security Architecture95
Cost Architecture & FinOps92
Business Architecture93
Architecture Communication91
Enterprise Architecture91
Legacy Modernization92
AI-Era Architecture86
Software Architecture & Engineering84
Architecture Patterns84
Architecture Decision-Making91
The Architect's Meta-Skills92
Delivery & Release Engineering93
Platform Engineering & Developer Experience92
Testing & Quality Architecture90
Data Platform Architecture88
Streaming & Real-Time Data93
Data Governance & Semantics81
Frontend & Experience Architecture91
Edge, Mobile & IoT88
Regulatory & Data Protection Architecture90
Assurance, Audit & Model Risk88
59 questions in AI-Era Architecture.
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Guardrails advanced
A platform must prevent harmful outputs in a user-facing AI feature. Where should guardrails sit, and what does each layer catch?
2 min answer guardrailslayersmoderationfalse-positives -
Guardrails advanced
An insurance company wants an LLM to draft claim decision letters. What is your architecture?
2 min answer ai-governanceguardrailshuman-in-the-loop -
Human in the Loop advanced
A pipeline combines automated processing with human review at scale. How should the boundary between them be designed?
2 min answer scale-aihuman-in-looproutingquality -
Human in the Loop advanced Multiple choice
An AI system routes decisions to human review. The override rate is 0.3%. Is the oversight working?
2 min answer oversightautomation-biasdesign -
Human in the Loop advanced
Design the moderation path for user-generated content at high volume, where both false positives and false negatives are costly.
2 min answer moderationmloversightdesign -
LLM Application Architecture advanced
A workspace product adds AI features over user content. Which architectural decisions dominate, and which are commonly deferred at cost?
2 min answer llm-applicationpermissionslatencycaching -
LLM Application Architecture advanced
An LLM chat product serves millions of multi-turn conversations. How do KV-cache reuse, prefix caching, continuous batching and session affinity change the architecture, and what breaks when a session lands on a different GPU?
3 min answer character-aikv-cacheprefix-cachinginference -
LLM Application Architecture advanced
Zoom publicly describes the architecture behind its AI Companion as a federated approach - its own models used alongside third-party frontier models, with work routed by task rather than every request going to a single provider. What problem does that structure solve that a single-provider design does not, and where would copying it be a mistake?
3 min answer model-routingmulti-providercostevaluation -
LLM Evaluation advanced
A platform ships AI features and cannot tell whether changes improve or degrade quality. What evaluation infrastructure is required, and in what order?
2 min answer evaluationregressionofflineonline -
LLM Evaluation advanced
A team ships an LLM feature and cannot tell whether changes improve it. What evaluation infrastructure is needed, and what does it not solve?
2 min answer unacademyevaluationgolden-setregression -
LLM Evaluation advanced
You are asked to prove an AI assistant is good enough to launch. How do you construct the evidence?
2 min answer evaluationlaunchgovernance -
LLM Evaluation advanced
Your RAG assistant gives confident answers that are subtly wrong. Where do you look first?
2 min answer ragevaluationdiagnosis