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Coding problemMedium~30 min

Build a validated structured extraction pipeline with bounded repair

Builds a schema-constrained extraction boundary that distinguishes refusal, malformed output, semantic invalidity, and safe bounded repair.

Artificial IntelligenceGenerative AILarge Language Models

Comparison questionEasy

~7 min

Compare plain JSON output, JSON mode, and schema-constrained output.

Separates prompt-requested JSON, parseable JSON modes, and provider-enforced schema adherence.

Generative AILarge Language Models

Architecture scenarioMedium~10 min

How should an application handle refusals, incomplete output, and truncation?

Separates provider refusals, safety blocks, token truncation, transport failure, and valid domain abstention.

Artificial IntelligenceGenerative AILarge Language Models

Concept questionHard~12 min

How should an application return tool results to the model?

Returns correlated, minimal, typed, and safely bounded tool results without confusing them with trusted instructions.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioMedium~7 min

How should structured output represent unknown or missing information?

Uses explicit status and field semantics so absence, null, not-applicable, and insufficient evidence are not conflated.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioMedium~10 min

How would you choose and describe tools for an AI agent?

Builds a small, task-relevant, typed toolset with clear semantics rather than exposing an entire internal API surface.

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 design a tool contract for a model?

Defines a narrow capability with a clear name, decision-oriented description, typed inputs, and safe result semantics.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioMedium~10 min

How would you design a useful JSON schema for model output?

Designs a narrow, typed, provider-supported schema that communicates the real downstream contract.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioHard~15 min

How would you evaluate structured output and tool use end to end?

Measures schema validity, tool selection, argument correctness, policy, execution outcome, repair, and final user result.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioHard~10 min

How would you evolve a structured-output schema safely?

Treats the model-facing schema and downstream consumer contract as a versioned API with compatibility and rollout concerns.

Artificial IntelligenceGenerative AILarge Language Models

Debugging scenarioHard~12 min

How would you repair invalid structured model output?

Uses constrained output where possible, deterministic parsing and validation, bounded targeted repair, and safe fallback.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioHard~12 min

How would you stream structured model output safely?

Separates user-visible progress from validated completion and prevents partial JSON or tool arguments from triggering side effects.

Artificial IntelligenceGenerative AILarge Language Models

Coding problemHard~40 min

Implement a bounded tool workflow with authorization and human approval

Builds a resumable tool workflow that validates model proposals, authorizes every action, requires approval for side effects, and remains idempotent under retries.

Artificial IntelligenceGenerative AILarge Language Models

Debugging scenarioHard~15 min

Structured outputs are valid but product quality dropped. How would you diagnose it?

Diagnoses schema-valid quality regressions across inputs, context, prompts, examples, models, schemas, tools, and downstream interpretation.

Artificial IntelligenceGenerative AILarge Language Models

Architecture scenarioHard~12 min

What must happen before an application executes a model tool call?

Applies parsing, schema and domain validation, authorization, confirmation, idempotency, limits, and audit before execution.

Artificial IntelligenceGenerative AILarge Language Models

Concept questionMedium~10 min

What problem does Model Context Protocol solve for agent systems?

Defines MCP as a client-host-server protocol for discovering and using tools, resources, and prompts without confusing interoperability with safety.

Artificial IntelligenceGenerative AILarge Language ModelsModel Context Protocol

Comparison questionMedium~7 min

When should you use structured output versus tool calling?

Distinguishes a typed final answer from a model request for the application to execute an external capability.

Artificial IntelligenceGenerative AILarge Language Models

Comparison questionMedium~10 min

When would you use RAG instead of a database query or tool call?

Chooses retrieval for ambiguous knowledge search while keeping authoritative structured operations behind deterministic services.

Artificial IntelligenceGenerative AILarge Language ModelsVector Databases

Concept questionMedium~10 min

Why can schema-valid model output still be wrong?

Separates structural validity from factual accuracy, evidence, authorization, and domain invariants.

Artificial IntelligenceGenerative AILarge Language Models

Concept questionMedium~7 min

Why should model output be treated as untrusted data?

Explains how generated text, markup, code, URLs, and tool arguments can become injection or integrity risks downstream.

Artificial IntelligenceGenerative AILarge Language Models