Agentic AI Human-Agent Collaboration Design Patterns
1hIntermediate2026-02-18
Authors
Thomas Erl
Course details
What is this course about?
As autonomous AI systems are becoming a greater part of business operations and work environments, it’s becoming increasingly important to understand how these systems need to be designed to collaborate with humans. Often, the more responsibility agentic AI systems are given, the more human involvement and oversight become necessary. In this new course, LinkedIn Top Voice and best-selling author Thomas Erl explains the common roles that need to be established for humans and AI agents to successfully work together. This course basically explores a number of specialized implementations of the human-in-the-loop concept, whereby AI systems are designed specifically for both humans and AI agents to carry out different parts of an overall workflow. The design patterns covered range from foundational collaborative designs, to system architectures that involve intelligent escalation, dynamic task allocation, and cognitive transparency, as well as correction and safety controls.
Instructor
Who teaches this course?
Thomas Erl is a LinkedIn Top Voice, best-selling author, and AI and digital technology education specialist at Arcitura. Thomas has authored or coauthored 15 books, and has published articles and interviews in publications like CEO World, The Wall Street Journal, and Forbes.
Objectives
What will I be able to do by the end of this course?
Analyze foundational collaborative design patterns for human-agent interactions.
Apply intelligent escalation and routing patterns to optimize task delegation.
Evaluate cognitive transparency and trust factors for effective AI-human collaboration.
Implement correction and safety design patterns to improve AI system reliability.
Audience
Who is this course for?
AI/ML engineers
Cloud architects
System designers in tech companies
Researchers in AI and machine learning
Prerequisites
What do I need to know before taking this course?
Basic knowledge of AI systems and cloud environments
Familiarity with human-agent interaction dynamics
Understanding of AI architecture principles
As autonomous AI systems are becoming a greater part of business operations and work environments, it’s becoming increasingly important to understand how these systems need to be designed to collaborate with humans. Often, the more responsibility agentic AI systems are given, the more human involvement and oversight become necessary. In this new course, LinkedIn Top Voice and best-selling author Thomas Erl explains the common roles that need to be established for humans and AI agents to successfully work together. This course basically explores a number of specialized implementations of the human-in-the-loop concept, whereby AI systems are designed specifically for both humans and AI agents to carry out different parts of an overall workflow. The design patterns covered range from foundational collaborative designs, to system architectures that involve intelligent escalation, dynamic task allocation, and cognitive transparency, as well as correction and safety controls.
Instructor
Who teaches this course?
Thomas Erl is a LinkedIn Top Voice, best-selling author, and AI and digital technology education specialist at Arcitura. Thomas has authored or coauthored 15 books, and has published articles and interviews in publications like CEO World, The Wall Street Journal, and Forbes.
Objectives
What will I be able to do by the end of this course?
Analyze foundational collaborative design patterns for human-agent interactions.
Apply intelligent escalation and routing patterns to optimize task delegation.
Evaluate cognitive transparency and trust factors for effective AI-human collaboration.
Implement correction and safety design patterns to improve AI system reliability.
Audience
Who is this course for?
AI/ML engineers
Cloud architects
System designers in tech companies
Researchers in AI and machine learning
Prerequisites
What do I need to know before taking this course?
Basic knowledge of AI systems and cloud environments
Familiarity with human-agent interaction dynamics
Understanding of AI architecture principles
Concepts
Introduction
- Introduction
- What you need to know
- Agent-environment interaction loop
- Human-agent communication
Collaborative Foundation Design Patterns
- Collaborative foundation design patterns
- Mixed-initiative handover
- Agent role classification
Intelligent Escalation and Routing Design Patterns
- Intelligent escalation and routing design Patterns
- Knowledge limit reporting
- Dynamic task allocation
Cognitive Transparency and Trust Design Patterns
- Interactive probing
- Parallel explainer agent
- Cognitive transparency and trust design Patterns
Correction and Safety Design Patterns
- Correction and safety design patterns
- Staged execution
- Reversible action
- Correction and refinement loop
Conclusion
- Next steps