CompTIA AI Agent Essentials

Overview

CompTIA AI Agent Essentials is a 4–5-hour, hands-on course designed for non-technical and lightly technical professionals who want to build confidence working with AI agents.

Learn how AI agents differ from traditional chatbots and simple automations, and identify where an agentic approach can add value. You’ll translate real-world tasks into structured agent workflows, manage agent context, tools, memory, and knowledge, and apply guardrails to support safe and reliable use.

Through scenario-based exercises and hands-on practice in CompTIA’s proprietary Agent Simulator, you’ll learn to test and evaluate agent performance, monitor behaviour, and identify when human oversight is needed. No coding or previous experience building AI agents is required.

You’ll also validate your skills through a CompTIA CompCert assessment.

Prerequisites

No previous experience building AI agents or coding is required.

The course is designed for non-technical and lightly technical professionals who want to understand and work with AI agents in organisational environments.

Target audience

This course is designed for professionals who need to understand, evaluate, or work with AI agents as part of their role.

It is particularly relevant to:

• Product professionals
• Operations professionals
• Analytics professionals
• IT-adjacent professionals
• Other non-technical and lightly technical professionals exploring practical applications of AI agents

Objectives

By the end of this course, learners will be able to:

• Explain what AI agents are and how they differ from traditional chatbots and simple automations
• Identify appropriate use cases for AI agents and recognise when simpler AI tools or workflows are more suitable
• Translate real-world tasks into structured workflows that AI agents can execute
• Determine when tasks require reasoning and when deterministic logic is more appropriate
• Explain how context, instructions, tools, APIs, autonomy levels, memory, and knowledge affect agent behaviour
• Apply guardrails, least-privilege principles, and human oversight to support safe agent workflows
• Test and evaluate agent performance, monitor behaviour, identify issues, and communicate uncertainty or failures

Outline

Understanding AI agents and use cases

Build a foundation in AI agents and understand where an agentic approach can add value.

• Define AI agents and their core characteristics
• Compare AI agents with traditional chatbots and simple automations
• Identify suitable use cases for AI agents
• Recognise when simpler AI tools or workflows are more appropriate
• Consider how AI agents can support work across organisational environments

Translating work into agent workflows

Learn how to turn real-world tasks into structured workflows that AI agents can execute.

• Break complex tasks into smaller, manageable steps
• Structure workflows so that individual stages can be checked
• Identify where agents need to reason and where deterministic logic is more appropriate
• Translate practical work activities into agent workflows
• Consider how workflow structure can affect agent performance

Controlling agent behaviour and actions

Explore how agents use context, instructions, and tools to perform tasks.

• Understand how context and instructions guide agent behaviour
• Explore different levels of agent autonomy
• Understand how APIs and external tools extend agent capabilities
• Consider how tool access can affect agent behaviour and reliability
• Identify appropriate controls for agent actions

Managing agent memory and knowledge

Understand how agents use information to support tasks and workflows.

• Explore knowledge, short-term state, and long-term memory
• Understand how agents store and retrieve information
• Determine what information an agent should retain during a workflow
• Consider what information should be discarded
• Apply appropriate approaches to managing agent knowledge and memory

Designing safe agents with human oversight

Learn how to apply controls that support safe and responsible agent behaviour.

• Apply guardrails to help prevent agent misbehaviour
• Restrict tool access using least-privilege principles
• Identify points in a workflow where human review is required
• Understand how human oversight can support safe agent operation
• Consider how controls should reflect the risks associated with an agent workflow

Testing, evaluating, and monitoring agent performance

Develop practical skills for evaluating agent behaviour and identifying issues.

• Evaluate agent outputs against expected results
• Diagnose issues in agent workflows
• Monitor agent behaviour and performance signals
• Identify uncertainty and potential failures
• Communicate agent limitations and failures to human operators
• Practise designing and testing simulated agents using CompTIA’s proprietary Agent Simulator
• Use personalised feedback to improve agent workflows and performance

Exams and assessments

The course includes a CompTIA CompCert assessment to validate learners’ understanding and practical application of AI agent concepts.

The assessment validates the ability to:

• Reason about AI agents and their use cases
• Design effective agent workflows
• Apply appropriate safety controls and human oversight
• Evaluate agent performance

Successful completion provides a CompTIA CompCert to demonstrate the skills developed through the course.

Hands-on learning

This course combines interactive multimedia instruction, scenario-based exercises, and practical activities.

Learners will use CompTIA’s proprietary Agent Simulator to safely design and test simulated agents, apply controls, evaluate performance, and respond to realistic workflow scenarios. Personalised feedback helps learners understand how their choices affect agent behaviour and performance.