← Back to CoursesAgentic AI: PhD Level

Neuroanatomy Explorer

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Memory Deck

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The Agent Loop in 3D

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Embodied, Web, and Software Agents

Manual: General · Subject: Agentic AI

Study agentic AI in concrete environments such as robots, browsers, and codebases, where perception and action become operational.

Agents in the wild

Environment classes

Agentic systems operate in web environments, software repositories, simulators, lab instruments, and physical robots. Each setting changes observability, action latency, safety constraints, and evaluation protocols.

Embodiment matters

In embodied settings, perception is noisy, actions are costly, and errors can be irreversible. This pushes agent design toward robust state estimation, contingency planning, and conservative execution.

Environment characteristics

SettingKey challengeTypical metric
WebDynamic content and prompt injectionTask success
CodeLarge action space and hidden bugsTests passed
RoboticsContinuous control and safetyCollision rate
Scientific toolsHigh-cost experimentsDiscovery quality
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Operational risk

The closer an agent gets to the physical or financial world, the stronger the case for permission gating, audit logs, and human override.

Which environment property most strongly increases the need for contingency planning?

In software agents, what is a common external verifier?

Name one reason web agents are difficult to evaluate.

What is one safety mechanism for high-stakes agents?