How and When You Should Build Multi-Agent Systems

Recently, Cognition and Anthropic published articles with seemingly contradictory titles, yet both teams offer shared insights into the core principles of building multi-agent systems.

The most important factor is Context Engineering. Beyond simply writing good prompts, the ability to automatically and precisely deliver the necessary context to each sub-agent within a dynamic system is emerging as a core challenge in agent development.

Effective context management requires the following strategies.

• Long conversation management: As conversations grow longer, summarization and external memory storage mechanisms are needed to prevent context overflow.
• Clear task division: The lead agent must clearly define goals, output formats, tool usage, and task boundaries for sub-agents in order to avoid duplicate work.

Design differences based on the system's purpose also matter. Systems centered on Read tasks are easy to parallelize and manage, whereas systems centered on Write tasks—such as writing code—are far more challenging, since they require coordinating conflicting decisions among agents and merging the results.