AgentForce

What is AgentForce?

Salesforce Agentforce is an AI-powered platform designed to create and deploy digital agents that can automate tasks, improve productivity, and enhance customer service. 

Building Blocks of Agents-

Agents-

• These are the core AI assistants that perform tasks and interact with users.
• They are more autonomous than other conversational AI solutions, able to identify opportunities for action and initiate tasks within defined parameters
• An agent can perform business tasks on behalf of the users.

Topics –

• Topics define the scope of an agent's capabilities and categorize the tasks it can handle.
• They guide the agent in understanding user requests and applying the appropriate actions and instructions. For example, a topic could be "Account Management" or "Order Status Lookup".

Instructions

• Instructions provide guidance to the agent on how to execute actions and interact with users.
• They define the agent's decision-making process and ensure consistent and appropriate responses.

Actions

• Actions are the specific tasks an agent can perform, such as looking up order status, updating account information, or generating a return label.
• These can be standard Salesforce actions or custom actions built for specific needs.

Reasoning Engine

• The reasoning engine orchestrates the interaction between topics, actions, and the Large Language Model (LLM)
• It determines which topics and actions are relevant to a user's request and guides the agent's actions accordingly
• Agentforce is using Atlas Reasoning Engine

Large Language Model (LLM)

• The LLM enables the agent to understand natural language, communicate effectively with users, and generate relevant responses.

Security

• Einstein Trust Layer

What are the Five Attributes of an Agent?

• Role
• It's similar to the roles that you've already defined today across your Customer 360. 
• For example, if you're using Sales Cloud, you've defined roles for your SDRs and your account executives - their metrics and dashboards.

• Data
• All of this data is already in the Salesforce Platform.
• Structured data like your custom fields as well as unstructured data like Slack conversations and knowledge articles. 
• With our new Data Cloud Zero Copy Partner network, you can also pull in all of your external data lakes and warehouses to be activated by Agentforce. 

• Actions
• When you think about what workflows you want your Agent to be able to perform and automate.
• These are the actions you've already built - the business processes into the Salesforce platform - every flow, every line of APEX code, every API integration, it’s all available for you to point and click and empower your Agentforce.

• Channels
• Thanks to the Salesforce platform, Agentforce has access to every digital channel natively within Salesforce whether that's Slack, Whatsapp, or your company website. 

• Guardrails and Trust 
• Provide an Agent with guardrails around what they can and cannot do. 

 What is Einstein Trust Layer?

AI agents are integrated with the Einstein Trust Layer, which is a secure AI architecture natively built into Salesforce. Designed for enterprise security standards, the Trust Layer lets you benefit from generative AI without compromising your customer data. It also lets you use trusted data to improve generative AI responses.

• Data grounding: The Trust Layer ensures that generative prompts are grounded and enriched in trusted company data.
• Zero-data retention: Your data is never retained by a third-party LLM provider.
• Toxicity detection: Potentially harmful LLM responses are detected and flagged.
• AI monitoring: AI interactions are captured in event logs, giving you visibility into the results of each user interaction.

 What are AI Guardrails?

AI guardrails are mechanisms that ensure your AI project operates legally and ethically. You need guardrails to prevent AI from causing harm with biased decisions, toxic language, and exposed data. Guardrails are necessary to protect your project from technical attacks.
There are three types of AI guardrails—security guardrails, technical guardrails, and ethical guardrails.

• Security Guardrails-These guardrails ensure that the project complies with laws and regulations, and that private data and human rights are protected. Common tools here include secure data retrieval, data masking, and zero-data retention. Secure data retrieval means that your project only accesses data that the executing user is authorized to access. For example, if a person with no access to financial records triggers a response from the AI model, the model shouldn’t retrieve data related to financial records. Data masking means replacing sensitive data with placeholder data before exposing it to external models. This ensures that sensitive data isn’t at risk of being leaked. Model providers enforce zero-data retention policies, which means that data isn’t stored beyond the immediate needs of the task. So, after a response is generated, the data used is no longer available.
• Technical Guardrails-These guardrails protect the project from technical attacks by hackers, such as prompt injection and jailbreaking, or other methods to force the model to expose sensitive information. Cyberattacks can cause your project to generate untrue or harmful responses.
•  Ethical Guardrails-These guardrails keep your project aligned with human values. This includes screening for toxicity and bias. Toxicity is when an AI model generates hateful, abusive, and profane (HAP) or obscene content. Bias is when AI reflects harmful stereotypes, such as racial or gender stereotypes. As you can imagine, that’s a disaster! Since AI learns its responses, toxicity and bias could be a sign that your data is introducing unwanted language and ideas to your model. Toxicity detection identifies responses that might have toxic language, so you can review it manually and make adjustments to reduce toxicity.

What is Agentforce Data Library?

Agentforce Data Library is a Salesforce feature designed to enhance the accuracy and relevance of AI agents' responses by providing them with access to an organization's trusted data. It uses "grounding" to index various data sources, allowing AI agents to base their answers on accurate and specific information.
Here's a breakdown of what it is and how it works:

What it is:

A centralized repository for structured and unstructured data, including

•  Knowledge articles
• File uploads (e.g., PDFs, text, HTML)
• Web sources
• Salesforce fields and records

How it works:

·       Data Ingestion: You upload or connect your data sources to the Data Library.

•  Indexing: The Data Library indexes this content, making it searchable for AI agents. This process also automates several configuration steps in Salesforce Data Cloud and Prompt Builder, such as creating data streams, mapping data objects, and setting up search indexes and retrievers.
• Grounding: When an AI agent receives a query, it uses the indexed data to "ground" its response. This means it retrieves the most relevant information from your specific data library to ensure its answers are accurate, contextual, and aligned with your organization's policies and information.
• Generative AI Integration: The retrieved information is then combined with Generative AI to formulate a clear, helpful, and natural-language response.

Agentforce for Sales

• Agentforce SRD
• In sales, an SDR (Sales Development Representative) is an entry-level role focused on generating and qualifying leads for a sales team. They are the first point of contact for potential customers, engaging with them through various channels like cold calling, emailing, and social media to identify if they are a good fit for the company's products or services. SDRs do not close deals; instead, they pass qualified leads to sales representatives
• Agentforce SDR, also known as AI SDR agents, helps your team nurture leads at scale 24/7. SDR agents are proactive, autonomous agents that send personalized outreach, answer your customers’ questions accurately, and even book meetings on your behalf. This is transformative for sales teams and allows them to focus on building customer relationships and pipeline growth. Here, you learn more about these agents.
• Agentforce Sales Coach
• Sales teams continually face new challenges. A sales rep leaves, and the team scrambles to cover until a new hire is up to speed. An inexperienced sales rep needs support for a negotiation with a new customer they’re struggling with. Managers just don’t have the time to review every deal and give every seller the 1:1 coaching they need.Good news: Salesforce now offers a solution that helps managers and sales reps alike. Sales coaching in Agentforce is like having a personal trainer in Salesforce. 
• Agentforce Sales Coach provides deal-specific, personalized feedback to sellers on their messaging and customer communication. It provides
• Autonomous, on-demand coaching: Reps can receive guidance anytime, without needing a live coach
• Pitch practice before meetings: Sellers can rehearse their pitch and get tailored, actionable feedback based on the deal and its current stage
• AI-driven role-play scenarios: Reps can practice tough conversations with a simulated “customer” or “buyer.
• Personalized feedback on role-plays: Reps can improve their approach using insights specific to their deal.