The same user intent can be satisfied by chat, search, or tool execution, and the model keeps choosing the expensive path. How would you rebalance it?

Instruction: Describe how you would tune path selection when the assistant overuses costly actions.

Context: Tests how the candidate diagnoses the problem, chooses the safest next step, and reasons through recovery. Describe how you would tune path selection when the assistant overuses costly actions.

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I'd define the accuracy and freshness requirement before optimizing cost. Explaining a refund policy may use trusted context; checking the current refundable balance needs a read; issuing a refund needs an authorized write...

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Your preparation path

Work through these questions in order. Read the answer aloud, then explain it in your own words.

1. Start with the foundations

Build the vocabulary and explain the core decisions.

  1. When should a model call a tool instead of answering from context? Free sample
  2. How would you explain MCP to a product engineer in one minute? Free sample
  3. What information should the orchestrator validate before executing a tool call? Free sample

2. Apply it to a real workflow

Practice diagnosis, validation, and everyday tradeoffs.

  1. Why do idempotency and retries matter more with AI-driven tool use? Free sample
  2. How do you keep permission boundaries clear when many tools share overlapping capabilities? Member answer
  3. A user revokes access to a connected app mid-session. How should the AI workflow behave? Member answer

3. Prepare for senior discussions

Explain failure boundaries, recovery, and production choices.

  1. Design a fallback strategy when tools are unavailable, degraded, or unauthorized. Member answer
  2. How do you implement MCP step-up authorization without losing scopes or retrying forever? Member answer
  3. An MCP request resumes after user confirmation. How would you validate its requestState? Member answer

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