- A
Entities
Why wrong: Entities extract data but are not primary components in Agent Builder.
- B
Topics
Topics define the agent's areas of expertise.
- C
Dialogues
Why wrong: Dialogues are used in Einstein Bots, not Agentforce.
- D
Intents
Why wrong: Intents are used in Einstein Bots, not Agentforce.
- E
Actions
Actions define what the agent can do, like calling an API.
Question 768 of 1,000
AI Associate Salesforce Einstein AI Features Practice Question
This AI Associate practice question tests your understanding of salesforce einstein ai features. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company wants to build an autonomous AI agent using Agentforce that can handle customer inquiries about order status and reset passwords. Which components must be defined in Agent Builder? (Choose TWO.)
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
✓
Topics
In Agent Builder, Topics are the primary mechanism for defining the scope of an autonomous agent's capabilities. Each topic represents a distinct customer intent (e.g., 'Order Status' or 'Password Reset') and contains the instructions, prompts, and conversation flow logic for handling that specific type of inquiry. Without defining Topics, the agent would have no structured way to route or process customer requests.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Entities
Why it's wrong here
Entities extract data but are not primary components in Agent Builder.
- ✓
Topics
Why this is correct
Topics define the agent's areas of expertise.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Dialogues
Why it's wrong here
Dialogues are used in Einstein Bots, not Agentforce.
- ✗
Intents
Why it's wrong here
Intents are used in Einstein Bots, not Agentforce.
- ✓
Actions
Why this is correct
Actions define what the agent can do, like calling an API.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse the components of Agent Builder with those of Einstein Bots (which use Intents and Dialogues), leading them to select Intents or Dialogues instead of recognizing that Agent Builder uses Topics and Actions as its core building blocks.
Detailed technical explanation
How to think about this question
Agent Builder relies on a topic-driven architecture where each topic can include instructions, user-facing prompts, and optional actions (such as Apex calls or Flow invocations). Under the hood, the agent uses a large language model (LLM) to interpret user input and map it to the most relevant topic based on the topic's name and description, rather than relying on pre-defined intent classifiers. This allows for more flexible, natural language understanding without requiring extensive training data for each intent.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the AI Associate exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
- →
Salesforce Einstein AI Features — study guide chapter
Learn the concepts, then practise the questions
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FAQ
Questions learners often ask
What does this AI Associate question test?
Salesforce Einstein AI Features — This question tests Salesforce Einstein AI Features — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Topics — In Agent Builder, Topics are the primary mechanism for defining the scope of an autonomous agent's capabilities. Each topic represents a distinct customer intent (e.g., 'Order Status' or 'Password Reset') and contains the instructions, prompts, and conversation flow logic for handling that specific type of inquiry. Without defining Topics, the agent would have no structured way to route or process customer requests.
What should I do if I get this AI Associate question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
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Last reviewed: Jul 4, 2026
This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.
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