1Z0-1127-25 Prompt Engineering Practice Question
A prompt engineer is designing a ReAct pattern prompt to enable an LLM to use external tools. Which of the following is a key characteristic of the ReAct pattern?
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
✓
The model produces a chain of thought followed by an action, then observes the result and continues reasoning
ReAct interleaves reasoning steps (e.g., 'I need to find the current weather') with actions (e.g., 'Action: call weather API') and observations, allowing the model to reason and act in a cycle.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The model uses a single tool call to answer the question
Why it's wrong here
ReAct may involve multiple tool calls in a loop.
- ✓
The model produces a chain of thought followed by an action, then observes the result and continues reasoning
Why this is correct
Correct: ReAct alternates between reasoning, action, and observation.
- ✗
The model generates a final answer without any intermediate steps
Why it's wrong here
ReAct explicitly requires intermediate reasoning and actions.
- ✗
The model is fine-tuned specifically for tool use
Why it's wrong here
ReAct is a prompting pattern, not a fine-tuning technique.
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