LLM Agents, Part 5 - Communication Protocol in Agentic Systems

🌈 Abstract

The article discusses the use of Event-Driven Architecture (EDA) in the context of multi-agent systems, building upon the previously introduced Service-Oriented Architecture (SOA). It explores how EDA can complement SOA to create more responsive and adaptable multi-agent systems, using a biotech sales organization as an example.

🙋 Q&A

[01] Service-Oriented Architecture (SOA) for Multi-Agent Systems

1. What are the key benefits of using SOA for multi-agent systems?

• SOA allows for breaking down complex processes into manageable, independent services, promoting modularity and flexibility.
• It enables services to communicate through well-defined interfaces, resulting in a system that is less prone to disruption when changes are made.
• For example, updating the lead qualification service in the biotech sales system does not affect other services like proposal writing or viability assessment.

2. How does SOA provide a solid foundation for structuring multi-agent systems?

• SOA tells us what the components are (the different services) but does not address how these components interact or manage their internal workflows.
• To create truly responsive and adaptable systems, we need to go beyond static structures and incorporate patterns that handle the flow of information and the progression of tasks.

[02] Event-Driven Architecture (EDA) for Multi-Agent Systems

1. What is Event-Driven Architecture (EDA) and how does it complement SOA in multi-agent systems?

• EDA is a software design pattern that emphasizes real-time system response to events, such as a new lead being identified or a proposal being finalized.
• In EDA, components (agents or services) produce and consume these events, triggering further actions across the architecture.
• EDA promotes decoupled, asynchronous interactions, making systems more flexible and scalable, which is crucial for complex, real-time interactions in multi-agent systems.

2. What are the key benefits of using EDA in the context of the biotech sales system?

• Real-time Responsiveness: EDA ensures that when an event like identifying a new lead occurs, multiple agents can start immediately, such as the lead qualification and market analysis agents.
• Decoupling: Agents or services react to events independently, without any direct connection, allowing the system to remain modular and flexible.
• Scalability: New agents can be easily integrated to listen for relevant events and act without disrupting existing workflows.

3. How does the event bus and event schemas work in an EDA-based multi-agent system?

• The event bus is the backbone of the EDA system, routing events between producers and consumers.
• Event schemas define the data structure, standardize communication, and ensure correct data interpretation between agents and services.
• This standardization allows agents to communicate consistently, ensuring that data is interpreted correctly, similar to predefined contracts (APIs) in a microservices architecture.

4. What are some of the challenges in implementing EDA in multi-agent systems?

• Event Storage: Efficient event storage is crucial as the system grows and the number of events increases.
• Debugging Complexity: Tracing the flow of events in a large system can be challenging, and distributed tracing tools are often required.
• Over-communication: If not carefully managed, the system can become overwhelmed with too many events, leading to performance bottlenecks.