AI Agent Operations Foundations

• Explain how computer use models (Claude Computer Use, browser automation agents) interpret screen content, generate actions, and propagate errors through multi-step workflows Understand
• Identify the common failure modes of autonomous agents: hallucinated UI elements, stale page state, incorrect click targets, infinite loops, and cascading errors from a single misinterpreted screen Analyze
• Design human-in-the-loop checkpoints for marketing agent workflows, specifying where agents must pause for approval, what information to surface, and what constitutes a stop condition Create
• Apply scope limitation principles to agent configurations: least-privilege credential access, sandboxed environments, spending caps, and domain restrictions that prevent agents from exceeding their mandate Apply
• Implement credential hygiene practices for agent deployments: OAuth token scoping, API key rotation schedules, credential vault configuration, and separation of production vs. testing credentials Apply
• Construct audit logging systems that capture agent actions, decisions, and state at each step, enabling post-incident reconstruction and compliance review Create
• Evaluate the blast radius of an autonomous agent task: what is the worst-case outcome if the agent fails silently, and what controls reduce that blast radius to an acceptable level Evaluate
• Assess whether a given marketing task is appropriate for agent automation based on reversibility, financial exposure, brand risk, and required judgment complexity Evaluate

Levels: Remember · Understand · Apply · Analyze · Evaluate · Create — highest demands most original thinking.