Microsoft Azure AI Engineer Associate AI-102 Practice Question
You are designing an autonomous multi-agent workflow in C# by using Semantic Kernel. A Planner agent must dynamically decompose a user goal, invoke skills exposed by two specialist agents (ResearchSkill and ReportSkill), and keep the overall conversation history so the agents can build on each other's output across multiple turns. Which Semantic Kernel feature should you use to orchestrate this interaction and persist state between calls?
Streaming Chat Completion API with a shared conversation ID
A custom MemorySkill that writes results to vector memory
Manually chaining agent calls inside a single C# method
The FunctionCallingStepwisePlanner (also referred to as the Stepwise Planner) receives a high-level goal, breaks it into smaller steps, and calls the appropriate skills in sequence. It persists the execution plan and the Kernel's context variables, so each turn can resume with full awareness of the previous steps, enabling autonomous multi-agent workflows that span several user turns.
Manual orchestration with inline code lacks the dynamic decomposition and built-in state management needed for autonomous operation. A MemorySkill only stores long-term facts but does not plan or coordinate actions. Streaming Chat Completion provides incremental tokens from the model but does not chain multiple agents together.
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Microsoft Azure AI Engineer Associate AI-102
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