Extension: design your own agent team

The core exercise is complete

If you completed step 8, you have finished the core exercise. This step is an extension to begin if time remains or try after the workshop. You do not need to complete a second team during the scheduled session.

A. Design your own agent team

Choose a safe example task based on an assignment, project or personal interest. Do not use personal or confidential information. Briefly answer these four questions in your own notes:

1. Goal: What output do you want to create?
2. Roles: Which tasks could you assign to separate specialists?
3. Handoffs: What information and results does the next specialist need?
4. Checks: How will you check the output against your requirements and evidence?

For example, a presentation team could summarize supplied material → draft a presentation outline → check evidence and omissions. The goal is not to replace only the hotel review input, but to redesign the roles, instructions and handoffs for a new goal.

B. Build it if time remains

If your design is ready and time remains, create a new workflow in Sim and try it. Otherwise, continue after the workshop.

1. Create a new workflow and a Start input.
2. Add two or three Agents for the roles you need.
3. Put each role and its rules in System, and its input and request in User.
4. Connect the roles in the order your task needs. Reference an earlier Agent’s content in User when its result must be passed on.
5. Run once and check whether each role and the final result support your goal.

You do not need to copy today’s parallel-and-combine structure. A sequential structure may suit another task, and a simple task may need only one AI. Running the workflow again requires working service accounts and API access.

C. Develop human know-how into guidance agents can use

The short prompts in this workshop are only a starting point. In real work, people already have useful knowledge and experience: what to check, how to judge a situation, when to escalate it and how to communicate. Knowledge that is gained through experience but is difficult to express is often called tacit knowledge.

Knowledge management describes expressing tacit knowledge in a shareable form as externalization. Here, that means organizing people’s know-how as guidance an agent can use, rather than simply turning it into numbers or automatically training a model.

You can gradually make that know-how explicit and give the relevant parts to each role:

• organize expert knowledge as instructions, examples, checklists or reference documents;
• give each agent only the information relevant to its responsibility;
• review the results with experienced staff; and
• refine the instructions and materials over time.

For example, a hotel can document what staff check first during a delay, when a case should be escalated, what must not be promised without approval and examples of an appropriate guest reply.

More advanced tools may preserve this context through memory, knowledge sources or tool-specific instruction files. This usually improves the agent’s instructions and context; it does not automatically retrain the underlying AI model.

Use reviewed information and exclude personal or confidential customer data. The goal is to make each role reflect the way your team works while keeping people responsible for the final result.

Further reading: Nonaka (1994), A Dynamic Theory of Organizational Knowledge Creation · Hallin & Marnburg (2008), Knowledge management in the hospitality industry

You can continue experimenting in Sim or implement the structure with another tool. Other tools may require you to rebuild the roles, inputs and connections for their environment.

What matters is dividing roles, passing results and refining instructions to support your own work, rather than mastering a particular service. For a simple task that does not need separate roles, starting with one AI is fine. Review the final result yourself before using it, and follow your course’s AI-use guidelines for assignments.

Questions after the session

For questions about the workshop materials or exercise, message Soohyun Kim on LinkedIn.