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Meet the Club's AI Agent Roster

Run the Meet the Club's AI Agent Roster MicroSim fullscreen

About This MicroSim

The umbrella idea at the centre is the useful one: matching a task to the agent type built for it, rather than one tool trying to do everything.

Six spokes, six distinct jobs. A planning agent drafts a sequence toward a goal. A communication agent drafts a reply from the club's own policies. A registration agent applies the ratio cap and waitlist rules. A scheduling agent cross-references availability against venue hours. A reminder agent writes something specific to one family and moment. A mentor coaching agent draws on aggregated patterns.

That last one carries the constraint worth reading aloud: it works from anonymized, aggregated patterns, never from one identified student's record. The distinction is not a technical detail -- it is the difference between "the debugging badge is a bottleneck for this cohort" and a profile of a named child.

Click each spoke and the club task and example are concrete enough to test against a real week's work.

How to Use

  • Click any agent to see the task it handles and an example.
  • The hub is the idea the six share; the spokes are the specialisations.
  • Drag a node to reposition it; the hub stays pinned. Reset restores the layout.

Lesson Plan

Bloom level: Understand (L2) -- classify

Learning objective: Given a club task, the learner classifies which of the six AI agent types is the right match for it.

Before the sim (5 min). List five things the club did by hand last month. Keep the list.

With the sim (10 min). Click through all six. Then classify each item from the warm-up list, and note the ones that fit no agent -- those are the tasks that still need a person.

After the sim (15 min). Pick the single agent type that would save the club the most hours and write down what it would need access to in order to work.

Check for understanding. Ask: "You want to know which student is falling behind. Which agent?" None of them, as specified -- the coaching agent works on cohort patterns, not individuals. Noticing that the roster deliberately has no agent for that question is the classification this objective wants.

Embedding This MicroSim

Paste this into any page of the book, adjusting the relative path to docs/sims/ for the page's depth:

<iframe src="../../sims/ai-agent-roster-network/main.html" width="100%" height="702" scrolling="no"></iframe>

Specification

The full specification below is extracted from Chapter 32: AI Agents for Registration, Scheduling, and Communication.

Type: graph-model
**sim-id:** ai-agent-roster-network<br/>
**Library:** vis-network<br/>
**Status:** Specified
**Template:** https://github.com/dmccreary/ai-strategy-for-education/tree/main/docs/sims/ai-concept-hierarchy

Purpose: Show the six specific AI agent types as a network around the umbrella idea of leveraging AI agents, so a learner can click any agent type and see the club task it handles and a one-line example.

Bloom Taxonomy: Understand (L2)
Bloom Taxonomy Verb: classify

Learning objective: Given a club task, the learner classifies which of the six AI agent types is the right match for it.

Node types:
1. Center node "Leveraging AI Agents" (gray hexagon) -- click reveals "Matching a task to the agent type built for it, rather than one tool trying to do everything."
2. Planning AI Agent (blue circle) -- click reveals "Drafts a sequence of dates or steps toward a goal, respecting stated constraints. Example: a proposed semester calendar."
3. Communication AI Agent (green circle) -- click reveals "Drafts a reply or announcement pulling from the club's own policies. Example: a make-up-policy email reply."
4. Registration AI Agent (amber circle) -- click reveals "Processes new sign-ups against the club's ratio cap and waitlist rules. Example: moving a family off the waitlist."
5. Scheduling AI Agent (purple circle) -- click reveals "Cross-references mentor availability against venue hours. Example: proposing which of three dates has full mentor coverage."
6. Reminder AI Agent (red circle) -- click reveals "Drafts a reminder tailored to the specific family and moment, beyond a fixed timer. Example: mentioning a badge a student is one session from finishing."
7. Mentor Coaching AI Agent (teal circle) -- click reveals "Drafts coaching suggestions from aggregated, anonymized patterns, never from one identified student's record. Example: flagging a badge that's become a bottleneck for a whole cohort."

Edges: One edge from the center node to each of the six agent-type nodes, unlabeled (the hub-and-spoke layout itself communicates that all six are varieties of the same underlying idea).

Interactive features:
- Hover any node to preview its one-line job description
- Click any node to highlight it and open a side-panel infobox with its full description and example
- Zoom with the mouse wheel, pan by dragging the background

Visual styling: Center node larger and gray; six spoke nodes evenly sized, each a distinct accent color; uniform edge style

Legend: Node color key matching the six agent types plus the center "umbrella" node

Implementation: vis-network JavaScript library, hierarchical or force-directed hub layout, canvas size 800x450px.

References