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2948 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 areas2948 Architecture Fundamentals91 Distributed Systems101 Data Architecture90 Cloud Architecture87 Networking96 API & Integration Architecture87 Reliability & Resilience99 Observability92 Performance & Capacity Engineering100 Security Architecture105 Cost Architecture & FinOps102 Business Architecture103 Architecture Communication102 Enterprise Architecture100 Legacy Modernization102 AI-Era Architecture106 Software Architecture & Engineering93 Architecture Patterns94 Architecture Decision-Making101 The Architect's Meta-Skills102 Delivery & Release Engineering103 Platform Engineering & Developer Experience102 Testing & Quality Architecture102 Data Platform Architecture98 Streaming & Real-Time Data103 Data Governance & Semantics91 Frontend & Experience Architecture101 Edge, Mobile & IoT98 Regulatory & Data Protection Architecture99 Assurance, Audit & Model Risk98
Difficulty Any beginner intermediate advanced

6 questions in Chunking & Retrieval.

  1. Chunking & Retrieval intermediate

    A live assistant serves 1.8M documents chunked at a fixed 512 tokens with no overlap. You need to move to structure-aware chunks of about 900 tokens with 15% overlap and a newer embedding model, with no downtime and no quality regression. What is the sequence?

    3 min answer chunkingre-embeddingmigrationshadow-traffic
  2. Chunking & Retrieval advanced

    A retrieval system over code and documentation performs poorly. Which chunking decisions matter, and what is the common mistake?

    2 min answer chunkingretrievalstructurecontext
  3. Chunking & Retrieval advanced

    Review this ingestion pipeline. An HR assistant covers 4200 policy documents totalling about 9 million tokens. Ingestion runs a semantic chunker, generates three hypothetical questions per chunk and embeds those too, ensembles two embedding models, builds a knowledge graph of entity links, and adds a parent-document store. The nightly rebuild takes 11 hours and one engineer maintains all of it. Retrieval quality has never been measured. What would you remove and what would you keep?

    3 min answer ragingestionover-engineeringevaluation
  4. Chunking & Retrieval intermediate Multiple choice

    Review this retrieval setup. An assistant over a policy corpus retrieves the top 5 chunks. Users complain it cites the 2023 edition of a policy. Inspection shows the corpus holds about seven near-identical revisions of every document and the top 5 are usually five revisions of the same page. Which change would you make first?

    2 min answer chunking-retrievaldeduplicationversioningtop-k
  5. Chunking & Retrieval intermediate

    Users report the assistant gets numbers wrong when answering from documents containing tables. Diagnose.

    2 min answer ragchunkingquality
  6. Chunking & Retrieval beginner Multiple choice

    Users say the assistant's answers lack context, so a team proposes raising chunk size from 400 tokens to 1200 across a 60000-document policy corpus. Retrieval still returns the top 5 chunks. What is the dominant effect of that change?

    3 min answer chunkingretrievalembeddingsprecision