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Concept questionMedium~7 min

How do system, developer, user, and contextual instructions differ?

Explains instruction authority while keeping provider-specific message roles separate from the application’s durable trust boundary.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioMedium

~10 min

How would you build or rewrite a retrieval query for RAG?

Transforms conversational requests into bounded search inputs while preserving user intent, constraints, and traceability.

Artificial IntelligenceGenerative AILarge Language ModelsVector Databases

Architecture scenarioMedium~10 min

How would you construct useful context for a model request?

Selects relevant, trustworthy, and budgeted context instead of treating the context window as storage.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioHard~15 min

How would you design a reliable AI extraction boundary?

Combines bounded instructions, source context, a narrow schema, abstention, semantic validation, review, observability, and rollout.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioMedium~10 min

How would you separate instructions, context, and user data in a prompt?

Builds a readable request with stable instructions and clearly delimited, provenance-aware untrusted inputs.

Artificial IntelligenceGenerative AILarge Language Models

Concept questionEasy~5 min

What goes into an LLM context window?

Describes the context window as the bounded request state containing instructions, conversation, retrieved evidence, tool results, and output capacity.

Artificial IntelligenceLarge Language Models

Concept questionEasy~5 min

What makes a production prompt more than a string?

Treats a production prompt as a versioned request contract containing instructions, context, output expectations, and application-owned controls.

Generative AILarge Language Models

Architecture scenarioMedium~10 min

When should you split one large prompt into multiple steps?

Balances one-call simplicity against explicit multi-step workflows with intermediate validation and failure handling.

Artificial IntelligenceGenerative AILarge Language Models

Comparison questionMedium~7 min

When would you use zero-shot versus few-shot prompting?

Uses examples to clarify ambiguous task behavior while accounting for token cost, bias, maintenance, and evaluation evidence.

Artificial IntelligenceGenerative AILarge Language Models