AI tools are moving beyond simple chat interfaces. New agent-based environments can plan, generate, critique, revise and organize complex work across multiple steps, creating new possibilities for how educators design and maintain course materials.

This webinar explores how instructors can use AI agents as collaborative instructional design partners to develop lesson plans, case studies, assessment banks, simulations, learning activities and other resources. Rather than asking a chatbot for a finished product, participants will see how structured workflows can divide a task among different AI roles, such as researcher, writer, critic and reviewer, and progressively refine materials against learning outcomes, course context and instructor requirements.

The session focuses on practical approaches that educators can adapt to their own disciplines using emerging tools such as Cursor, Antigravity and other agent-based AI environments. It also considers where human judgment remains essential, including verifying content, maintaining academic standards, protecting sensitive information and deciding when AI-generated material is appropriate for teaching.

Participants in this webinar will leave with a repeatable approach for moving from an instructional need to a reviewed and usable course resource, while keeping the educator in control of the process.

Key takeaways

• A practical workflow for AI-assisted course development that moves from learning outcomes and requirements through generation, critique, revision and final review.
  
• Ways to use multiple AI agents or roles to help create lesson plans, cases, assessments, simulations and other learning resources rather than relying on a single prompt and response.
  
• Strategies for improving quality and alignment by having AI evaluate materials against learning objectives, rubrics, disciplinary context and instructor-defined criteria.
  
• Guidance on where human oversight matters most, including factual verification, academic integrity, privacy, bias, accessibility and decisions about appropriate use.
  
• A framework for experimenting with emerging AI development environments that is not dependent on any one platform and can evolve as the technology changes.