In 2025-10, delivered a GEPA-based tutorial for DSPy focused on trusted monitoring of AI-generated code. Implemented a monitor model training workflow to classify code samples as honest or malicious, integrated with the Control Arena library for dataset retrieval and evaluation, and documented the optimization process and its impact on safety metrics. The work was contributed to stanfordnlp/dspy with a single merge commit adding the tutorial. This enhances product safety posture, enables practitioners to validate AI-generated code, and demonstrates end-to-end GEPA application in DSPy workflows.

Concise monthly summary for 2025-08 focusing on UKGovernmentBEIS/control-arena. Delivered two key features that enhance data visualization clarity and configurability. Audit Budget Visualization Enhancements refactored plotting to correctly represent audit budgets, updated example scripts to align variables with audit budgets, and added saving of generated plot figures for easier review. Trusted Editor Policy Modularity and Usage Demo extracted the trusted editor into a standalone policy module, with an example evaluation script to demonstrate usage with different prompts and thresholds. These efforts improve decision-making support, reduce maintenance overhead, and enable rapid experimentation with policy prompts and thresholds.