Simple Multi-Agent Architecture Running Across Our Entire Organization
We have successfully implemented a multi-agent architecture at our organization’s scale. Initially, we faced several challenges such as credential management issues, state tracking problems, and managing execution traces. However, we managed to overcome these obstacles and present our streamlined architectural design.
Our Architecture Overview
- Shared Context Layer: Our setup leverages three distinct agent classes—Observer agents at the edge, Task agents for executing actions, and Goal agents for orchestrating plans. The Observer agents gather external signals and write structured events, while Task agents handle specific tasks by performing actions and returning results.
- Goal Agents Layer: The goal agents read through the full execution history, build plans to sequence task agents, and re-plan when necessary due to changing conditions. This layer is managed using LangGraph, which uses a stateful graph structure to handle conditional branching, checkpointed states, and resuming mid-plans in case of failures.
- Task Agents Layer: The task agents are responsible for executing bounded actions with minimal privileges. They communicate using CrewAI, a role-based system that ensures proper agent assignment, shared short-term and long-term memory, and a planning agent that sequences tasks before execution begins.
- Harbor Layer: Harbor sits beneath all agents. It provides scoped access to tools, files, and workflows through its workspace model. Credentials are managed within Harbor rather than in the model context, ensuring security and accountability. Every action taken by an agent is logged with full traceability, facilitating quick debugging of failures.
- Ring-Based Protocol: The architecture uses a ring-based protocol for message routing at different layers: Kernel agents manage lifecycle operations, Orchestrators route messages based on agent metadata, Goal agents decompose intents into task plans, and Task agents execute tasks with minimal privilege. Observer agents run continuously without decision-making responsibilities.
The shared history among newer agents allows us to reduce the coordination overhead per agent over time, making our system more efficient as it grows.
Key Takeaways
- Simplified Multi-Agent Architecture: Our architecture is designed with a clear separation of concerns between different layers (Observer, Task, Goal).
- Security and Traceability: We use Harbor for credential management and trace every action taken by agents.
- Fleet-Scale Efficiency: The system benefits from the growing history among newer agents, leading to a reduction in coordination overhead per agent.
The key takeaway is that our multi-agent architecture has proven effective at managing complex operations across our organization while maintaining security and efficiency.
Submitted by /u/Silent_Employment966
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