John Robert, Lead Data and AI Platform Engineer, discusses evaluating AI agents beyond success rate. Talks about failures of AI projects, the uniqueness of AI agents, and the evaluation process. Creating a Framework for AI Agent Evaluation: Four Evaluation Categories - performance, business, safety, and cost. Metrics creation to enhance AI projects. Includes task completion rates, reasoning quality, accuracy evaluation, tool execution, response time, and recovery time checks. Examining KPIs, Safety, Security, and Cost in AI Agent Projects: Consider ROI, user satisfaction, time-saving, code review, adoption, engagement, risk, regulations, unauthorized actions, and cost efficiency. Checking Infrastructure and Security Metrics: Evaluate project reliability, online presence, errors, resources, prompt injection, data leakages, authorized actions, tool usage.