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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
Difficulty Any beginner intermediate advanced

86 questions in AI-Era Architecture.

  1. ML Platform intermediate

    A machine-learning platform must ingest telemetry from many concurrent training runs. What are the workload's distinguishing characteristics?

    2 min answer weights-biasesml-platformtelemetryingestion
  2. ML Platform advanced

    A model performs well in evaluation and poorly in production. What are the likely causes?

    2 min answer ml-platformtraining-serving-skewdriftfeatures
  3. ML Platform advanced

    A recommendation platform's ML systems span data pipelines, training, evaluation and online serving. Where should the boundaries be, and what causes the most costly class of bug?

    2 min answer ml-platformfeature-storetraining-serving-skewboundaries
  4. ML Platform advanced

    A training run on thousands of GPUs loses several nodes mid-run. How should checkpointing frequency, elastic training, straggler detection and scheduling minimise wasted compute, and what does each checkpoint cost?

    3 min answer metallamatrainingcheckpointing
  5. Model Selection intermediate Multiple choice

    A client wants a model that follows their specific document formatting conventions and answers from their knowledge base. What do you recommend?

    2 min answer ragfine-tuningarchitecture
  6. Model Selection intermediate

    A content platform must choose between a large hosted model, a smaller hosted model and a self-hosted open model for a moderation task. What decides it?

    2 min answer sharechatmodel-selectioncostlatency
  7. Model Selection advanced

    A platform must choose which model serves which request class. What should drive the decision, and what changes over time?

    2 min answer model-selectionroutingevaluationcost
  8. Model Selection intermediate

    A recommendation service's model server is down at peak. Should the application fall back to an older model, precomputed candidates, popularity baselines or cached per-user results — and how is the fallback tested?

    2 min answer fallbackdegradationrecommendationsresilience
  9. Model Selection intermediate

    Your music recommender uses collaborative filtering. Newly released tracks are never recommended. Why, and what do you do?

    2 min answer spotifyrecommendationscold-startensemble
  10. Multi-Agent Systems advanced

    A research assistant runs a planner that fans out to four worker agents and a synthesiser that writes the final answer. One worker retrieves the wrong document and returns a fluent confident summary of it. What happens downstream and what stops it?

    2 min answer multi-agenterror-compoundingprovenancehandoff
  11. Multi-Agent Systems advanced

    A team proposes decomposing a workflow into several specialised agents that coordinate. What justifies this over a single agent with more tools, and what does it cost?

    2 min answer multi-agentdecompositioncoordinationcost
  12. Multi-Agent Systems advanced

    A team proposes five specialised agents that collaborate to handle a customer request. Assess.

    2 min answer agentsdesignpragmatism