An Agentforce agent occasionally provides responses that reference outdated Case information. What is the MOST effective way to reduce this issue?

The correct answer is C. Improve data grounding using live Salesforce records. Data grounding connects the agent's responses to real-time Salesforce data (such as live Case records) rather than relying on the LLM's static training knowledge. By grounding responses in current records, the agent reflects the actual, up-to-date state of cases. Increasing promp

AI Features for Service (e.g., Einstein Bots, Next Best Action)

Question

Options

AIncrease prompt temperature
BRely only on static instructions
CImprove data grounding using live Salesforce records
DDisable the Einstein Trust Layer

How the community answered

(25 responses)

A
4% (1)
B
16% (4)
C
72% (18)
D
8% (2)

Explanation

Data grounding connects the agent's responses to real-time Salesforce data (such as live Case records) rather than relying on the LLM's static training knowledge. By grounding responses in current records, the agent reflects the actual, up-to-date state of cases. Increasing prompt temperature (A) makes responses more random and creative, which would worsen accuracy. Relying on static instructions (B) cannot reflect dynamic record changes. Disabling the Einstein Trust Layer (D) removes AI safety and data protection features and would not fix stale data-it would introduce security risks.

Topics

#AI Agent Accuracy#Data Grounding#Einstein for Service#Real-time Data

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