By 2028, 33% of enterprise software apps will include agentic AI in their operations. This highlights that, while there are some ethical concerns about its use, AI agents are no longer just a promising concept—they’re becoming a reality. However, although they are indeed more autonomous than other AI systems, learning how to build AI agents requires careful preparation.
In other words, business users can create and customize AI agents on the platform using only natural language—no deep coding knowledge is required. But what does the building process look like? What is the ideal digital ecosystem to make it work properly? In today’s article, we’ll explore how to build AI agents using the Agentforce platform.
What Is Agentforce Agent Builder?
Let’s start with Agent Builder, one of the main features of Agentforce. This is Salesforce’s low-code tool designed for customizing and building AI agents across various business functions. With it, business users can create a task for their agents by defining topics using natural-language instructions and setting guardrails.
The platform also includes features for testing agent responses and enabling seamless human handoff when needed. Built-in templates make it easy to launch agents tailored for customer service, sales, or e-commerce, streamlining automation efforts for businesses.
How Are AI Agents Build?
Building AI agents requires a combination of several techniques. However, they can be summarized to the following six:
- Data collection: Gathering large, diverse datasets to train the AI models.
- Model training: Using supervised, unsupervised, and reinforcement learning methods to train the AI models.
- Natural language processing (NLP): Enabling the AI to understand and interact using human language.
- Reinforcement learning: Allowing the agent to improve its actions based on feedback and rewards.
- Decision-Making Algorithms: Implementing algorithms that help agents analyze data and determine the best course of action.
- Action Generation: Developing mechanisms for agents to execute decisions in real-world applications.
Agent Builder simplifies this process, making it easier for business users to build their agents without extensive coding expertise. However, this is not completely autonomous. So, let’s analyze how to build AI Agents in Agentforce platform.
How to build AI Agents in the Agentforce platform?
Step 1: Define the Agent’s Role
The process of building AI agents starts by specifying their role and purpose or, in other words, the job to be done by them. This involves determining the tasks and objectives it will handle, such as responding to customer inquiries, assisting with sales, or automating services and workflows.
Step 2: Create Topics Using Natural Language
Once you define the agent’s role, define their main tasks by describing them in simple, natural language. This step lets you set up conversational prompts and restrictions (also known as “guardrails”), so the agent knows what actions to take in specific scenarios.
Step 3: Assign Intelligent Actions
Select from various pre-configured intelligent actions, workflows, and responses that align with the agent’s objectives. These out-of-the-box topics allow the agent to handle conversations and perform necessary actions, using Apex logic and prompts when more customization is needed.
Step 4: Test and Monitor the Agent
Finally, use the Agent Builder monitoring tool (Plan Tracer) to test how your agent will respond in different situations. This step also includes configuring human handoff options, so the AI agent can seamlessly transfer complex cases to human agents.
While building AI agents is not difficult, it’s not as easy as pushing a button. To make the most out of these tools, you must set the integrated digital ecosystem they need to perform tasks properly. Otherwise, you are buying problems, not solutions. At Inclusion Cloud we are here to help. Let’s meet and see how to prepare.
What type of AI agents can I build?
Agentforce AI agents allow to scale the workforce of several industries. Thanks to their user-friendly, low-code customization capabilities, business users of several industries can benefit from multiagent systems. Nevertheless, to save you some time, we’ve put together their main roles and functions in various sectors as follows:
| Industry | Tasks |
| IT | Monitor security threats. |
| Share network insights. | |
| Resolve helpdesk support cases. | |
| Healthcare | Engages with patients, providers, and payers to resolve inquiries and provide summaries. |
| Banking | Analyzes data. |
| Manage client requests. | |
| Personalized service across retail, commercial, and investment banking. | |
| Retail | Share campaign insights. |
| Manage customer outreach. | |
| Resolve cases for fashion, grocery, and convenience retailers. | |
| Operations | Assistance in managing plan creation, resourcing needs, and tracking progress across teams. |
| Customer Experience (CX) | Analyze customer surveys and reviews. |
| Suggest retention improvements. | |
| Manage omni-channel experiences. | |
| Analytics | Share data insights. |
| Create visualizations. | |
| Suggest data-driven actions. | |
| Finance | Provide insights on financial reporting. |
| Assesses risks. | |
| Fraud detection. | |
| Resolve compliance-related queries. |
The technological framework behind AI agents’ deployment
As we saw, building AI agents is not difficult. Thanks to Agentforce Agent Builder, any business user can do it using only natural language queries to set tasks and guardrails. However, deploying AI technology requires more than this. Since agents rely heavily on up-to-date data, you will need an integrated technological infrastructure for them to perform their tasks properly.
Without cloud storage capacity, seamless data flow, and proper access to essential information, these tools can’t deliver the value every CIO is striving for. On top of that, the overcrowding of apps without central management fosters problems such as SaaS sprawl and drives software costs through the roof. But don’t worry. At Inclusion Cloud we can help you. Book a meeting and let’s plan the integrated AI deployment your business needs.
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