Talking My Way Through Building an Agentforce AI Agent in Less Than 10 Minutes
During the recent Salesforce TDX, I had a consultation session at the Agentforce booth. It walked me through designing and building an AgentForce artificial intelligence-powered agent tailored for my specific need. The session demonstrated the use of AI tools to create customized agents for content distribution and audience engagement.
Kareem Salman, a distinguished solutions engineer at Salesforce specializing in AI, guided me through the process using a custom tool developed for the booth. This tool is not a Salesforce product but was designed specifically for the demonstration. And the best part of the whole exercise for me was being able to have a verbal, natural language conversation with the AI tool to actually design the agent. And the whole exercise took less than 10 minutes.
Kareem walked me through inputting basic information (e.g., name, email) and selecting the type of agent to create. Suggestions included project management agents, client engagement agents, knowledge management agents, etc. I chose to build a client engagement agent. Basically I only had to type in a few pieces of information before I had a full-blown verbal conversation with the tool to provide the kind of information it needed to design the agent I needed.
The tool automatically generates the agent's description, responsibilities, topics, and actions based on my conversation with it. And. since I chose to design an agent to help me expand the audience for my thought leadership content, the agent will focus on tasks like content distribution, audience engagement analysis, and metrics reporting.
The tool automatically generated the agent's description, responsibilities, topics, and actions based on our conversation, giving the agent the name I gave it: The "Thought Leadership Expander." It will be deployed with all the specified guidance and requirements stemming from that conversation.
The clip below is from the session with Kareem helping me get started and then giving a play-by-play as I literally had a conversation with the AI tool that facilitated helping me decide what kind of agent I needed to build, what I wanted it to do, and what actions it needed to take for the agent to do what I needed it to.
AgentForce Consultation Session Hightlights (AI summary)
- **Introduction and Roles**:
- Brent is seeking assistance in building an AI agent but admits he lacks expertise.
- Kareem, a distinguished solutions engineer at Salesforce specializing in AI, guides Brent through the process using a custom tool developed for the booth. This tool is not a Salesforce product but designed specifically for the demonstration.
- **Agent Design Process**:
- Kareem walks Brent through inputting basic information (e.g., name, email) and selecting the type of agent to create. Suggestions include project management agents, client engagement agents, knowledge management agents, etc.
- Brent chooses a Client Engagement Agent and specifies that he wants it to help distribute his thought leadership content (podcasts, videos) to a broader audience.
- **Requirements Gathering**:
- Brent outlines his goals:
- Increase weekly reach on YouTube from 500 viewers to thousands.
- Expand LinkedIn reach from 1,000 viewers to 3,000–5,000 weekly.
- Improve metrics on Facebook and X (formerly Twitter), though he is unsure of target numbers.
- Kareem emphasizes that the agent will focus on tasks like content distribution, audience engagement analysis, and metrics reporting.
- **Agent Creation**:
- The tool automatically generates the agent's description, responsibilities, topics, and actions based on Brent's input.
- The agent is named "Thought Leadership Expander" and is deployed with all the specified guidance and requirements.
- **Capabilities of the Agent**:
- The agent combines data from Brent's instructions and his website to provide actionable insights.
- It can answer questions such as "How can I expand my audience reach?" by generating responses based on both preconfigured knowledge and external sources.
- **Metrics Discussion**:
- Brent asks about the importance of "total viewing minutes" as a metric.
- Kareem explains that while it takes time for the agent to process such queries, it understands Brent's goals and auto-completes tasks accordingly.
### Outcome:
The session concludes with the successful creation of an AI agent tailored to Brent's needs for thought leadership content distribution and audience engagement. The demonstration highlights how AI tools can simplify complex processes like agent configuration by automating tasks and generating actionable insights based on user input.
This consultation serves as an example of leveraging AI for personalized solutions in CRM and content strategy.
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