Agentforce Life Sciences agent skills, topics, and actions for Customer Engagement
Key Takeaway
In Customer Engagement, the Pre Visit Planning topic uses Identify Records By Name and Generate Healthcare Provider Summary to build a provider summary tailored to the user's territory. In the mobile app, that summary works offline, unlike custom subagents and tools.
Agentforce for Life Sciences Cloud gives life sciences users AI agents built from three parts: skills, topics, and actions. For Customer Engagement, the prebuilt use case is pre-visit account summarization. A key account manager, medical science liaison (MSL), or field sales rep asks about a healthcare provider (HCP) in natural language. The agent then returns a summary of that account, tailored to the user's assigned territory. To configure it, you turn on several setup switches, create an agent from a template, and assign the right permissions.
Skills, topics, and actions
Every Agentforce for Life Sciences agent is built from the same three parts:
- A skill is a prebuilt flow for a domain job, such as previsit planning.
- A topic keeps the agent on a defined task type or subject, so conversations stay on track and can be audited.
- An action is an executable step, such as generating a summary, retrieving key record details, or updating a record.
One way to hold the model: the skill is the job, the topic is the lane the conversation stays in, and the actions are the steps the agent can take in that lane.
For example, the Customer Engagement skill pairs with a Visit Planning topic. The Visit Planning topic helps key account managers, MSLs, and field reps prepare for visits by generating contextual summaries of healthcare providers. The topic's actions are Generate Healthcare Provider Summary and Identify Records By Name.