Designing Agent-to-Agent (A2A) Architecture in Salesforce

April 27, 2026
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Designing Agent-to-Agent (A2A) Architecture in Salesforce
Summarize this blog post with:

As Salesforce builds out with AI capabilities such as Einstein and Agentforce, the design of automation is also evolving. These conventional approaches like Flows, Apex triggers and integrations remain applicable but are not adequate to handle dynamic and complex business processes.

In this case, Agent-to-Agent (A2A) architecture comes in.

Instead of a single system or level of logic, A2A architecture allows a team of intelligent agents to talk to each other, cooperate, and work simultaneously. Such a viewpoint allows systems to be more adaptable, scalable, and able to cope in complexity of the real world.

In this article, we are going to discuss how to build A2A architecture in Salesforce in a simple and crisp way, yet keep it professional and practical.

What is Agent-to-Agent (A2A) Architecture?

Agent-to-Agent (A2A) is an architectural pattern, where a number of AI/logic based agents communicate with each other to accomplish tasks.

Every agent has a unique role and they communicate and collaborate with each other rather than operating in isolation.

In simple terms:

  • One agent receives a request
  • It delegates parts of the task to other agents
  • Each agent processes its part
  • Results are combined to produce the final output

This is unlike traditional automation, where a single process attempts to manage all aspects of the workflow from beginning to end.

Why A2A Architecture Matters in Salesforce

Salesforce environments are getting more and more complex Companies handle:

  • Multiple data sources
  • Different departments (sales, service, finance)
  • Real-time customer expectations

Traditional automation has limitations:

  • It follows predefined rules
  • It struggles with dynamic decision-making
  • It becomes difficult to maintain as complexity grows

A2A architecture addresses these challenges by:

  • Breaking down logic into smaller units
  • Allowing agents to make contextual decisions
  • Enabling collaboration between different functional areas

This results in systems that are:

  • More modular
  • Easier to scale
  • Better aligned with business processes

Core Components of A2A Architecture

Designing A2A architecture necessitates have identity of its major components.

1. Orchestrator Agent

The orchestrator is the system’s central point of control.

Its responsibilities include,

  • Getting the the original request (from user, API, or system)
  • Understanding the intent of the request
  • Deciding which agents need to be involved
  • Managing the flow of communication
  • Combining responses from different agents

The orchestrator doesn’t execute heavy business logic on its own. However, it is concerned with coordination and decisions.

2. Specialist Agents

Specialist agents are responsible for specific business domains.

Examples include:

  • Order Agent (handles order-related data)
  • Billing Agent (handles payments and refunds)
  • Support Agent (handles customer cases)
Each agent:
  • Has access to relevant data
  • Contains logic related to its domain
  • Performs a well-defined task
This separation ensures clarity and reduces the risk of errors.
Each agent:
3. Communication Layer

Agents must have a means of communicating among themselves. In Salesforce, this could be achieved by:

  • Apex method calls
  • REST APIs
  • Platform Events
  • Messaging frameworks

The communication should be structured and consistent. JSON is commonly used for passing data between agents.

Example:
{
   "requestType": "OrderStatus",
   "orderId": "ORD12345",
   "customerId": "CUST001"
 }
4. Data Layer

Agents rely heavily on data. The data layer may include:

  • Standard and custom Salesforce objects
  • External systems via APIs
  • Data Cloud for unified data access

It is important that agents work with:

  • Accurate data
  • Real-time information
  • Minimal duplication

How A2A Flow Works in Practice

Let’s consider a real-world scenario.A customer asks: “Can you check my order status and tell me if I am eligible for a refund?”

Here’s how A2A architecture handles this:

  1. The orchestrator receives the request
  2. It identifies two intents:
    • Check order status
    • Check refund eligibility
  3. It calls:
    • Order Agent
    • Billing Agent
  4. Each agent processes its task independently
  5. Results are sent back to the orchestrator
  6. The orchestrator combines the responses
  7. Final answer is returned to the user
This method enables parallel processing and shorter response time.

Basic Apex Example for Understanding

Here is a minimal example that show how an orchestrator could call multiple agents.

public class OrchestratorAgent {

 	public static String handleRequest(String requestType) {

     	if(requestType == 'OrderStatus') {
         	return OrderAgent.getOrderStatus();
     	}
     	else if(requestType == 'RefundCheck') {
         	return BillingAgent.checkRefundEligibility();
     	}

     	return 'Unsupported request';
 	}
 }
It’s a simplified illustration, but you can see how one agent assigns tasks to other agents.

Collaboration Patterns in A2A Architecture

There are two main ways agents collaborate.

1. Sequential Collaboration

With this pattern the agents operate in a specified order. Each step takes the previous one as its input.

Example:

  • Sales Agent confirms order
  • Billing Agent verifies payment
  • Logistics Agent processes delivery

This pattern is suitable for structured workflows.

2. Parallel Collaboration

In this pattern, a number of agents operate concurrently.

Example:

  • One agent checks inventory
  • Another checks payment status
  • Another evaluates risk
All agents operate in parallel, and the results are combined later. This scheme is well suited for complicated decision-making processes.

Designing A2A Architecture Step-by-Step

For developing the strong A2A system, do the following

Step 1: Identify the Use Case

Clearly define:

  • What problem you are solving
  • Which processes are involved
  • What outcomes are expected
Step 2: Break Down the Workflow

Divide the process into smaller tasks.

Each task should:

  • Be independent
  • Have a clear purpose
Step 3: Assign Agents

Create one agent per task or domain. Do not make agents responsible for handling multiple unrelated tasks.

Step 4: Design the Orchestrator Logic

The orchestrator should:

  • Interpret the request
  • Decide execution flow
  • Handle responses

It should not become too complex.

Step 5: Define Communication Structure

Use a consistent data format.

Example:

{
   "action": "refund_check",
   "orderId": "ORD5678"
 }
Step 6: Implement Error Handling

Always consider failure scenarios:

  • Missing data
  • API failures
  • Incorrect responses

Common Challenges in A2A Architecture

While A2A provides numerous advantages, it also presents challenges.

1. Infinite Loops

Agents may repeatedly call each other, creating loops.

Solution:

  • Set execution limits
  • Track agent calls</li
2. Error Propagation

Errors from one agent can affect the entire workflow.

Solution:

  • Validate inputs and outputs
  • Use structured data
3. Performance Overhead

Too many agent interactions can slow down the system.

Solution:

  • Optimize calls
  • Avoid unnecessary processing
4. Dependency Issues

Agents may become too dependent on each other.

Solution:

  • Keep agents loosely coupled
  • Design independent logic

Governance and Control

When systems grow increasingly independent, governance is crucial.
Security
Ensure:
  • Data access is controlled
  • Sensitive information is protected
Rules and Guardrails
Define:
  • Which agents can interact
  • What actions are allowed
  • When escalation is required

Human-in-the-Loop

For critical decisions:
  • Include manual approval steps
  • Allow human intervention
Example:
  • High-value refund requests
  • Contract approvals

Best Practices for A2A Design

  • Keep agents focused on a single responsibility
  • Use clear naming conventions
  • Maintain proper logging and monitoring
  • Test each agent independently
  • Avoid overcomplicating the architecture

Use Cases of A2A in Salesforce

A2A architecture can be applied in multiple scenarios:
Customer Support
  • Automated case handling
  • Intelligent routing
  • Resolution suggestions
Sales
  • Lead qualification
  • Opportunity analysis
  • Follow-up automation
Order Management
  • Order tracking
  • Shipment updates
  • Return handling
Finance
  • Payment validation
  • Refund processing
  • Invoice checks

Future of A2A in Salesforce

With advancements in AI, A2A architecture will become more common.
Future systems will:
  • Be more autonomous
  • Require less manual intervention
  • Provide faster and smarter responses
Technologies like:
  • Einstein AI
  • Data Cloud
  • Agentforce
will play a major role in this transformation.
Also Read

Final Thoughts

Agent-to-Agent architecture is a move from conventional automation towards intelligent cooperation. Rather than creating big, intricate workflows, organizations can design systems composed of small, specialized agents that cooperate.

The key to success lies in:

  • Clear design
  • Proper coordination
  • Strong governance
If properly implemented, A2A architecture can bring about substantial gains in efficiency, scalability, and general system intelligence.

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Written by

Dev Anand

A dynamic engineer, innovative thinker, initiative taker and multi technology professional with exceptional logical, analytical and management skills possess a decade experience in Software Development and Salesforce CRM Solutioning. Enrich experience in converting business needs to Salesforce Experience. Worked on multiple RFPs and POCs. 50+ Integrations between Salesforce and other Platforms. Experience in LWC, Aura, Apex, JS, HTML, PHP, WordPress, Magento and many others.

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