AI-102 Implement an agentic solution Practice Question
You are building an agentic solution using Microsoft Semantic Kernel. The agent must autonomously decide when to call an external API to fetch real-time data. You want to minimize token usage and avoid unnecessary API calls. Which planner configuration should you use?
⚠ Common exam trap
Candidates may confuse autonomous runtime decision-making with pre-generated plans or automatic invocation of all functions. Options that rely on SequentialPlanner or ParallelPlanner either lack the ability to decide at each step or consume more tokens by executing unnecessary calls.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use an AutoInvoke kernel with a greedy action planner
An AutoInvoke kernel with a greedy action planner enables the agent to make step-by-step decisions about which function to invoke next based on the immediate context. This minimizes token consumption by forgoing exhaustive plan generation and only triggering the external API when the current step requires it. In contrast, SequentialPlanner generates a complete plan upfront, potentially including unnecessary API calls, and manual or parallel planners either lack autonomy or increase token overhead.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a SequentialPlanner with a stepwise strategy and explicit function parameter constraints
Why it's wrong here
Stepwise strategy ensures API is called only when needed.
- ✗
Use a ManualInvoke kernel with a sequential planner
Why it's wrong here
Manual invoke prevents autonomous operation.
- ✗
Use a ParallelPlanner with a function-calling model
Why it's wrong here
Parallel planner increases token usage.
- ✓
Use an AutoInvoke kernel with a greedy action planner
Why this is correct
Greedy planning may invoke APIs unnecessarily.
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