Skip to content

Educator Learning Path

A structured path for teachers, professors, and training leads who want to use the FCC framework as a teaching instrument for AI agent orchestration, persona-based design, or software engineering courses. This path emphasizes curriculum mapping, assessment rubrics, lab exercises, and the guidebook.

Estimated time: 10--14 hours (path materials), plus preparation time for your specific curriculum

Prerequisites: Familiarity with course design. Python 3.10+ for running demos (students will need the same). No deep ML or DevOps knowledge required.

Quick-Start Checklist

# Activity Resource Time
1 Read the conceptual introduction What is FCC? 10 min
2 Install FCC and run the Quickstart Quickstart 15 min
3 Read the full Guidebook Table of Contents Guidebook Index 10 min
4 Study the Collaboration chapter Ch. 8: Collaboration Engine 30 min
5 Study the Assessment chapter Ch. 13: Assessments 60 min
6 Review all 10 lab exercises Ch. 12: Hands-On Labs 45 min
7 Review the assessment rubrics data file assessment_rubrics.yaml 20 min
8 Browse the curriculum mapping data curriculum_mapping.yaml 20 min
9 Run the educational Streamlit apps learn_personas.py, learn_workflows.py, learn_plugins.py 30 min
10 Read the For Educators guide For Educators 30 min

Key Personas for Classroom Use

When teaching FCC, start with a small set of personas that clearly illustrate the Find-Create-Critique cycle before expanding to the full catalog.

Starter Set (5 personas)

ID Name Phase Teaching Purpose
RC Research Crafter Find Demonstrates structured information gathering
BC Blueprint Crafter Create Shows how research becomes design
DE Documentation Evangelist Critique Illustrates quality review and feedback loops
CO Collaboration Orchestrator All Models cross-team coordination
RCHM Research Crafter Champion Orchestration Introduces the champion pattern

Expansion Set (for advanced courses)

ID Name Why It Matters
GCA Governance Compliance Auditor Teaches governance and compliance concepts
DGS Data Governance Specialist Demonstrates data integrity concerns
ESC Experiment Scientist Shows scientific method in ML workflows
AEA AI Ethics Assessor Introduces responsible AI concepts

Curriculum Mapping

12-Week University Course

Week Topic Guidebook Notebook Lab Assessment
1 Introduction to Agent Frameworks Ch. 1 01 -- Pre-assessment
2 R.I.S.C.E.A.R. Specification Ch. 3 01 Lab 1 --
3 Persona Dimensions Ch. 4 03 -- Quiz 1
4 Workflow System Ch. 5 02 Lab 2 --
5 Plugin Architecture Ch. 6 04 Lab 4 --
6 Midterm Review Ch. 1--6 -- -- Midterm
7 Event Bus and Observability Ch. 7 05 Lab 5 --
8 Collaboration Engine Ch. 8 06 Lab 6 Quiz 2
9 Governance and Constitutions Ch. 9 08 Lab 7 --
10 Cross-Project Integration Ch. 10 11 Lab 8 --
11 Capstone Work Session Ch. 12 12 Lab 10 --
12 Capstone Presentations -- -- -- Final

2-Day Intensive Workshop

Day 1 (8 hours):

Time Topic Resource
09:00--10:00 FCC Overview and Installation Ch. 1, Quickstart
10:00--11:30 R.I.S.C.E.A.R. and Persona Dimensions Ch. 3--4, Notebook 03
11:30--12:30 Hands-on: Create a Custom Persona Lab 1
13:30--14:30 Workflow System Ch. 5, Notebook 02
14:30--15:30 Hands-on: Build a Custom Scenario Lab 2
15:30--17:00 Plugin System and Event Bus Ch. 6--7, Notebook 04--05

Day 2 (8 hours):

Time Topic Resource
09:00--10:00 Collaboration Engine Ch. 8, Notebook 06
10:00--11:00 Governance and Quality Gates Ch. 9, Notebook 08
11:00--12:30 Hands-on: Governance Lab Lab 7
13:30--15:00 Cross-Project Integration Ch. 10, Notebook 11
15:00--17:00 Mini-Capstone: Design a Persona Team Lab 10 (condensed)

Assessment Resources

The FCC framework provides structured assessment materials that you can adapt for grading.

Available Rubrics

The assessment_rubrics.yaml file defines scoring criteria for:

  • Persona design quality (R.I.S.C.E.A.R. completeness, dimension coverage)
  • Workflow graph correctness (node connectivity, phase transitions)
  • Plugin implementation (ABC compliance, test coverage)
  • Capstone project evaluation (integration depth, documentation quality)

Collaboration Engine for Group Work

Use the CollaborationEngine to structure group assignments:

from fcc.collaboration.engine import CollaborationEngine
from fcc.collaboration.scoring import ScoringEngine

engine = CollaborationEngine()
session = engine.create_session(
    participants=["student_1", "student_2", "student_3"],
    personas=["RC", "BC", "DE"],
    scenario_id="GEN-001"
)

Students take turns inhabiting different personas, and the scoring engine evaluates deliverable quality at each phase transition.

Application Classroom Use
learn_personas.py Live demo of persona catalog -- project on screen during lectures
learn_workflows.py Visualize workflow graphs to explain phase transitions
learn_plugins.py Show the plugin ecosystem during the plugin architecture lecture
learn_object_model.py Demonstrate the object model abstraction layer

Tips for Teaching with FCC

  1. Start concrete. Run fcc simulate --scenario GEN-001 live in the first session. Students should see output before they read theory.
  2. Use the Streamlit apps as visual aids. They are more engaging than slides for explaining persona relationships and workflow graphs.
  3. Assign personas to students. Have each student "inhabit" a persona for a group exercise. This builds intuition for the R.I.S.C.E.A.R. model.
  4. Labs are progressive. Labs 1--3 are beginner, 4--6 intermediate, 7--9 advanced, and 10 is the capstone. Assign them in order.
  5. Use the event bus for live demos. Subscribe to events and project the console output during a simulation to show real-time agent interactions.

Connections to Other Paths

Further Reading