Frequently Asked Questions
Common Questions About Building Scalable Multi-Agent Systems
Everything you need to know before registering.
What makes a multi-agent system scalable? +
A scalable multi-agent system has three properties: explicit context boundaries so agents do not interfere with each other's state, semantic blueprints that keep each agent focused on its specific domain, and MCP-structured communication that provides typed, validated interfaces between agents. This combination lets you add agents and complexity without proportional increases in coordination failures.
How do context boundaries prevent scaling problems in multi-agent systems? +
Context boundaries define exactly what information each agent receives and what it can write back to shared state. Without boundaries, agents accumulate context from all previous interactions causing context rot. With boundaries, each agent works with a clean, relevant context at every invocation maintaining consistent performance regardless of how many agents are in the system.
What is context rot and how does this workshop prevent it? +
Context rot is the gradual degradation of agent performance as context windows fill with accumulated, increasingly irrelevant information from past interactions. The memory engineering techniques in this workshop prevent context rot through context compression, selective retrieval, and explicit context lifecycle management that keeps each agent's working context fresh and relevant.
How does MCP help multi-agent systems scale? +
MCP provides typed, validated interfaces between agents that prevent the informal coupling that breaks at scale. Each agent's interface is explicitly defined: what inputs it accepts, what outputs it produces, what errors it can return. This makes agent communication predictable and testable, which is essential for systems with many agents interacting in complex patterns.
How do I add new agents to an existing multi-agent system without breaking it? +
The Glass-Box architecture makes adding agents safe through explicit interface contracts via MCP, isolated context management per agent, and comprehensive logging that shows exactly how a new agent affects existing agent behavior. The workshop covers agent addition patterns that let you extend your system incrementally without regression.
What performance metrics should I monitor in a scaled multi-agent system? +
Key metrics include per-agent context window utilization (to catch context rot early), citation coverage in RAG responses (to monitor retrieval quality), inter-agent communication latency (to catch coordination bottlenecks), safeguard trigger rates (to monitor adversarial input patterns), and end-to-end task completion rates. The Glass-Box logging layer captures all of these automatically.
