AI Agent Evaluation Framework (HHH+)

The Challenge

AI agents were being deployed without standardized evaluation, leading to ad-hoc assessments, safety concerns, and inconsistent quality. Needed a systematic framework to evaluate AI agents across safety, fairness, and reliability dimensions before deployment.

The Approach

Designed the framework and its structure around Anthropic's HHH (Helpful, Honest, Harmless) foundation extended with four additional pillars: Transparency, Fairness, Responsibility, and Safety — 7 pillars total. Created structured red team protocols for adversarial testing. Framework adopted by 2 production clients.

Key Learnings

• Build on proven foundations — extended Anthropic's HHH rather than inventing from scratch
• Red team protocols surface issues that standard testing misses
• Framework design requires balancing rigor with practical adoption
• Reusable frameworks > custom one-off solutions