Online Access Free Agentforce-Specialist Exam Questions

No.# The correct answer is:
B. Create a custom retriever in Einstein Studio, and apply filters for publication date and product line

No.# Option C (Incorrect) should be " The Agent will always run flows in system mode so the running user's data access will not affect the data returned."

No.# A note on the explanation - there is a thing called Template Triggered Prompt Flows: https://help.salesforce.com/s/articleView?id=platform.flow_concepts_trigger_prompt_template_capability.htm&language=en_US&type=5

IG: @AfsarParkar

No.# B is the correct ans
References:
https://help.salesforce.com/s/articleView?id=service.cc_generative_ai_work_summaries.htm&type=5

https://help.salesforce.com/s/articleView?id=service.reply_recs_generative_ai_service_replies.htm&type=5

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No.# The best fit for enabling a sales manager to contact leads at scale with hyper-relevant solutions and customized communications is:

✅ C. Einstein Lead follow-up

Why?
Salesforce’s Einstein Lead Follow-Up is designed to help sales teams prioritize and automatically engage with leads by delivering relevant, personalized follow-up actions and communications. It uses AI to recommend next steps and tailor outreach at scale, which matches your scenario.

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No.# The correct answer is:
B. Create a custom retriever in Einstein Studio, and apply filters for publication date and product line.
✅ Why B is Correct
In this scenario, the issue is irrelevant results from outdated product versions. The search index itself is working — but retrieval needs to be more precise.
By creating a custom retriever in Einstein Studio, UC can:
Apply metadata filters (e.g., publication date)
Filter by product line or version
Restrict retrieval to only relevant documents
Improve grounding quality for AI responses
This ensures the AI assistant returns contextually accurate and up-to-date troubleshooting steps, without losing historical data that might still be useful for other use cases.
❌ Why Not A?
Modify the search index to only store documents from the last year and remove older records.
This is risky because:
Older documents might still be needed for legacy product support.
Deleting data reduces flexibility.
The issue is retrieval filtering, not indexing storage.
Search indexes in Data Cloud are meant to store broad knowledge — filtering should happen at retrieval time.
❌ Why Not C?
Use the default retriever...
The default retriever:
Searches the entire index
Does not apply custom filtering logic
Provides broad coverage, not precision
Since UC is already experiencing irrelevant results, using the default retriever will not solve the problem....

No.# answer is A