69. Self-Evolving Agents (MASE)
Mini-Project: Self-Evolving Agent (MASE): Intent Classifier with Sandbox Validation
A customer intent classifier that evaluates its own performance on a test set, identifies misclassified queries, asks the LLM to generate an improved prompt, and promotes candidates to production only after sandbox validation confirms improvement.
Description
MASE (Multi-Agent Self-Evolution) enables agents to improve themselves over time by analyzing their own performance, identifying weaknesses, and updating their prompts, tools, or strategies. Unlike ADAS (which searches from scratch), MASE starts with a working agent and continuously evolves it based on production feedback.
The agent monitors its own success/failure patterns, generates hypotheses about improvements, tests those improvements in a sandbox, and promotes successful changes to production.
Architecture Diagram
flowchart TD
A[Production Agent] --> B[Performance Monitor]
B --> C[Identify Weaknesses]
C --> D[Generate Improvement Hypotheses]
D --> E[Test in Sandbox]
E --> F{Improvement?}
F -->|Yes| G[Promote to Production]
F -->|No| D
style A fill:#2196F3,color:#fff
style B fill:#FF9800,color:#fff
style G fill:#4CAF50,color:#fff