Shadow Supervisor – OpenEnv AI Agent Environment
An experimental OpenEnv project for AI agent supervision and evaluation.
Shadow Supervisor is an OpenEnv-based experimental AI project organized around a custom environment, supporting datasets, development scripts, and training outputs. It provides infrastructure for experimenting with agent supervision workflows and examining training behavior through generated metrics and visualizations.
Technology stack
Problem
AI agent workflows need structured environments and evaluation tools to monitor behavior and understand how performance changes during experimentation.
Approach
Organized the project into environment, data, scripts, and output modules. Developed supporting Python scripts for analyzing training metrics and generating visualizations to inspect experiment behavior.
Solution
Created an experimental OpenEnv project with environment modules, data organization, training and analysis scripts, and generated performance visualizations.
Results
Implemented the environment and experiment structure and generated training-metric visualizations from recorded outputs. Add actual agent success rates, reward improvements, and evaluation results after verifying the experiments.