Problem
- Generic AI agents lack custom rules, style, and tool access.
- Context gets fragmented in complex projects.
- Limited flexibility in tool/model selection.
Solution
- Custom Sub-agents: define rules, toolsets, and models.
- Formula = Prompt Engineering + Tools for tailored behavior.
- MCP integration for private data and external knowledge access.
- Memory & context management for consistency over time.
Use Case
- Enforcing coding styles/architectures in projects.
- Accessing private knowledge bases or code.
- Automating repetitive tasks with consistent outputs.
- Controlling safety, cost, and tool usage.
Priority
Medium – Important improvement