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07/21Architecture

Designing AI Systems.

Architecture-level design of production LLM/RAG/agentic systems: application architecture, designing for non-determinism, structured-output engineering (constrained decoding), model selection & inference economics, routing/fallback, cost/latency budgets, guardrail placement, RAG-vs-long-context, and failure/fallback design. The AI counterpart to system_design (which carries no AI content); SDK plumbing lives in ai_engineering, run/monitor in llm_ops.

  • Designing AI Systems · 1 of 3

    LLM System Design Vocabulary

    A developer counts 380 words in a prompt, yet the API reports the request as 510 units long when measured against the context limit. Which units is the limit counted in?

  • Designing AI Systems · 2 of 3

    Model Routing & Fallback

    A wrapper retries a failed primary call against a backup model with the very same body. For which upstream status code is the automatic failover guaranteed to be futile?

  • Designing AI Systems · 3 of 3

    Model Routing & Fallback

    An incoming conversation has grown past what your default destination can accept in a single call: its inputs no longer fit. Which runtime handling at the dispatch layer preserves the most information?

Three of the 100 Designing AI Systems questions in the bank.

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