AI-102 Implement an agentic solution Practice Question
You are troubleshooting an agentic solution where the agent is not returning responses within acceptable time limits. You suspect the agent is making too many sequential calls to external tools. Which strategy should you recommend to reduce latency?
⚠ Common exam trap
Watch out — candidates often confuse throughput improvements (like adding tools or increasing token limits) with latency reduction, when the real bottleneck is the sequential dependency of tool 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
✓
Enable parallel tool execution
Enabling parallel tool execution allows the agent to invoke multiple external tools simultaneously rather than sequentially, directly reducing the total latency caused by serial tool calls. This is a core optimization in agentic frameworks like Semantic Kernel or AutoGen, where tool calls are independent and can be dispatched concurrently.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the max token limit
Why it's wrong here
Raising the max token limit only allows longer prompts and completions; it does not reduce the count of sequential external tool calls causing the delay. It is tempting because token limits govern model throughput, and increasing them helps when responses are truncated, not when orchestration latency dominates.
- ✓
Enable parallel tool execution
Why this is correct
Parallel tool execution dispatches independent external tool calls concurrently rather than sequentially, so total latency reflects the slowest call instead of the sum of all calls. This directly addresses the stem's constraint of excessive sequential tool invocations exceeding acceptable response times.
- ✗
Add more tools to distribute the load
Why it's wrong here
Adding tools increases the number of functions the agent may select and invoke, worsening sequential call latency rather than reducing it. It is tempting because distributing load across services helps throughput in parallel architectures, but the stem requires cutting the number of sequential tool calls, not spreading them.
- ✗
Reduce the thread history length
Why it's wrong here
Trimming thread history reduces prompt tokens and cost, but the sequential tool calls themselves still execute one after another, so wall-clock latency is unchanged. Tempting because shorter prompts feel faster, it would be correct only if latency stemmed from context size rather than serialised tool invocation.
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