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12-Week University Curriculum

A complete semester-length course syllabus for teaching the FCC Agent Team Framework. Designed for upper-division undergraduate or graduate-level courses in software engineering, AI systems, or collaborative computing.

Course Information

  • Title: Agent-Oriented Software Engineering with FCC
  • Level: Upper-division undergraduate / Graduate
  • Prerequisites: Python programming, basic design patterns, Git
  • Format: 2 lectures (50 min) + 1 lab (110 min) per week
  • Textbook: FCC Guidebook (docs/guidebook/), supplemented by Book Series (docs/books/)

Grading Weights

Component Weight Description
Lab Exercises 25% Weekly hands-on labs (Labs 1-9)
Midterm Project 20% Custom persona + workflow design
Homework Assignments 15% Weekly reading responses and coding tasks
Class Participation 10% Discussion, peer review, presentations
Final Capstone 30% Full FCC deployment project (Lab 10)

Week 1-2: FCC Fundamentals

Learning Objectives

  • Explain the Find-Create-Critique cycle and its purpose
  • Install and configure the FCC framework
  • Navigate the project structure and data layer
  • Load and query the persona registry

Lectures

  • Week 1, Lecture 1: Introduction to agent-oriented software engineering
  • Week 1, Lecture 2: The FCC cycle -- Find, Create, Critique
  • Week 2, Lecture 1: Project structure and Python packaging
  • Week 2, Lecture 2: Data layer -- YAML, JSON schemas, resource resolution

Readings

  • Guidebook Ch. 1: Introduction
  • Book 1 Ch. 1: What is FCC?
  • Book 1 Ch. 7: Getting Started

Lab

  • Week 1 Lab: Install FCC, run first persona query (Lab 1)
  • Week 2 Lab: Run mock simulation, inspect trace output (Lab 2)

Notebooks

  • 01_fcc_fundamentals.ipynb
  • 02_workflow_basics.ipynb

Assignment

Write a 1-page reflection: How does the FCC cycle compare to other software development lifecycles you have studied?

Week 3-4: Personas and R.I.S.C.E.A.R.

Learning Objectives

  • Describe all 10 components of the R.I.S.C.E.A.R. specification
  • Navigate the persona registry by category
  • Understand persona dimensions (56 dimensions, 9 categories)
  • Explain the discernment matrix and design target factors

Lectures

  • Week 3, Lecture 1: R.I.S.C.E.A.R. specification deep dive
  • Week 3, Lecture 2: Persona categories and the 102-persona catalog
  • Week 4, Lecture 1: Persona dimensions -- behavioral, cultural, professional
  • Week 4, Lecture 2: Discernment matrix and design target factors

Readings

  • Guidebook Ch. 3: R.I.S.C.E.A.R. Specification
  • Guidebook Ch. 4: Persona Dimensions
  • Book 1 Ch. 2: Persona Mental Model

Lab

  • Week 3 Lab: Explore personas interactively (Notebook 03)
  • Week 4 Lab: Analyze dimension profiles for 5 personas

Notebooks

  • 03_persona_exploration.ipynb

Streamlit Apps

  • learn_personas.py
  • persona_explorer.py

Assignment

Select 3 personas from different categories. Compare their R.I.S.C.E.A.R. specs and dimension profiles. Write a 2-page analysis of how these differences affect their behavior in the FCC cycle.

Week 5-6: Workflows and Actions

Learning Objectives

  • Describe the 7 workflow graph variants and when to use each
  • Execute workflow actions through the action engine
  • Understand the 6 action types and 312 action definitions
  • Design custom workflow graphs

Lectures

  • Week 5, Lecture 1: Workflow graphs -- nodes, edges, traversal
  • Week 5, Lecture 2: The 7 graph variants (5-node to 55-node)
  • Week 6, Lecture 1: Action engine -- types, execution, results
  • Week 6, Lecture 2: Custom workflow graph design

Readings

  • Guidebook Ch. 5: Workflow System
  • Book 1 Ch. 3: Workflow Thinking
  • Book 2 Ch. 3: Workflow Design

Lab

  • Week 5 Lab: Explore workflow graphs (Lab 3)
  • Week 6 Lab: Design a custom 8-node workflow graph

Notebooks

  • 07_action_engine.ipynb

Assignment

Design a custom workflow graph for a domain of your choice (e.g., scientific paper writing, code review, product design). Include at least 6 nodes across all 3 FCC phases. Submit the graph definition as JSON and a 1-page design rationale.

Week 7-8: Event Bus and Collaboration

Learning Objectives

  • Explain the event bus architecture and its 81 event types
  • Implement event subscribers with filtering
  • Manage collaboration sessions with scoring and gates
  • Use the observability layer for tracing and metrics

Lectures

  • Week 7, Lecture 1: Event bus -- pub/sub, filtering, serialization
  • Week 7, Lecture 2: Event types by category, replay patterns
  • Week 8, Lecture 1: Collaboration engine -- sessions, turns, gates
  • Week 8, Lecture 2: Observability -- tracing, metrics, exporters

Readings

  • Guidebook Ch. 7: Event Bus and Observability
  • Guidebook Ch. 8: Collaboration Engine
  • Book 2 Ch. 6: Event Bus Observability
  • Book 2 Ch. 7: Collaboration Sessions

Lab

  • Week 7 Lab: Event bus integration (Lab 6)
  • Week 8 Lab: Build a collaboration session (Lab 7)

Notebooks

  • 05_event_bus_observability.ipynb
  • 06_collaboration_engine.ipynb

Streamlit Apps

  • collaboration_dashboard.py
  • simulation_replay.py

Assignment

Build an event-driven monitoring system that subscribes to simulation events, records metrics, and displays a summary dashboard. Submit code and a screenshot of your dashboard output.

Week 9-10: Governance and Plugins

Learning Objectives

  • Describe the 3-tier constitution system (hard-stop, mandatory, preferred)
  • Use quality gates for compliance checking
  • Build custom plugins (10 plugin types)
  • Understand plugin dependency resolution and lifecycle

Lectures

  • Week 9, Lecture 1: Governance -- tags, quality gates, compliance
  • Week 9, Lecture 2: Constitution registry -- per-persona rules
  • Week 10, Lecture 1: Plugin architecture -- 10 types, registration
  • Week 10, Lecture 2: Plugin lifecycle, dependency resolution, cross-plugin orchestration

Readings

  • Guidebook Ch. 9: Governance
  • Guidebook Ch. 6: Plugin Architecture
  • Book 1 Ch. 4: Quality and Governance
  • Book 2 Ch. 5: Plugin Development

Lab

  • Week 9 Lab: Governance audit exercise (based on Lab 5)
  • Week 10 Lab: Build a custom plugin (Lab 5)

Notebooks

  • 08_governance_constitutions.ipynb
  • 04_plugin_system.ipynb

Streamlit Apps

  • learn_plugins.py

Midterm Project Due (End of Week 10)

Design and implement a custom persona with full R.I.S.C.E.A.R. spec, dimension profile, and a workflow that uses your persona. Include a plugin that integrates with the event bus. Present in a 10-minute class demonstration.

Week 11: Knowledge Federation

Learning Objectives

  • Build and query knowledge graphs (9 node types, 9 edge types)
  • Set up semantic search with embedding providers
  • Configure RAG pipelines with different chunking strategies
  • Understand cross-project federation and namespace resolution

Lectures

  • Week 11, Lecture 1: Knowledge graphs and semantic search
  • Week 11, Lecture 2: RAG pipelines and federation

Readings

  • Guidebook Ch. 17: Knowledge Federation
  • Book 3 Ch. 1-4: Semantic Search, Knowledge Graphs, RAG, Federation

Lab

  • Week 11 Lab: Knowledge graph construction and RAG setup (Labs 8-9)

Notebooks

  • 15_semantic_search.ipynb
  • 16_knowledge_graphs.ipynb

Streamlit Apps

  • kg_explorer.py
  • federated_dashboard.py

Assignment

Build a knowledge graph from your midterm project's personas and workflows. Export it in at least 2 serialization formats. Write a 1-page analysis of the graph structure.

Week 12: Final Project (Capstone)

Learning Objectives

  • Integrate all FCC components into a cohesive deployment
  • Demonstrate end-to-end workflow from scenario to knowledge graph
  • Present findings and design decisions to peers

Lectures

  • Week 12, Lecture 1: Capstone project work session
  • Week 12, Lecture 2: Final presentations (Part 1)

Lab

  • Week 12 Lab: Capstone work session + presentations (Lab 10)

Capstone Requirements

The capstone project must include:

  1. Custom personas (minimum 3) with full R.I.S.C.E.A.R. specs
  2. Custom workflow graph (minimum 8 nodes)
  3. At least 1 custom plugin
  4. Event bus integration with at least 5 event types
  5. Collaboration session with scoring and approval gates
  6. Knowledge graph with at least 3 node types
  7. Documentation generated via docs-as-code
  8. Presentation (15 minutes) covering design decisions and lessons learned

Grading Rubric

Criterion Points Description
Technical completeness 30 All 7 required components implemented
Design quality 25 Clean architecture, proper patterns
Documentation 15 Generated docs, clear README
Presentation 15 Clear communication, demo quality
Innovation 15 Creative use of framework features

Supplementary Materials