mastra-ai-architecture-rules

Best practices for AI service architecture design involve applying capability-aware principles, separating agent and workflow responsibilities, and maintaining minimal architecture to ensure safety and avoid overengineering.

To structure agent and workflow task scopes in AI services, you separate responsibilities among agents, workflows, tools, workspaces, memory, and storage to ensure scalable and maintainable system boundaries.

You should apply capability-aware architecture principles before structuring your AI system to ensure optional features are used safely and minimally, preventing overengineering and maintaining robust security.

To avoid overengineering scalable AI systems, adopt minimal architecture guidelines that simplify technical design, enforce strict task scopes, and ensure robust safety considerations are incorporated from the start.

Following architecture safety guidelines does not limit capabilities but ensures optional features are used minimally and responsibly, preventing unbounded actions while maintaining a robust and secure AI service environment.

The best way to separate storage and memory responsibilities in AI architectures is to follow strict task scope guidelines that define clear boundaries for data persistence and contextual memory management.