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Orientation and Foundations

Course Overview and Goals for BMAD-METHOD

1. Foreword: The Vision of BMad

1.1 The Challenge of Al in Development

1.2 Introducing the BMad Method: A New Paradigm

1.3 Core Principles of the BMad Ecosystem

Architecture and Orchestration

2. Chapter 1: The BMad Architecture - A Symphony of Intelligence

2.1 Overview: Orchestrator, Agents, Workflows, and Tasks

2.2 The Central Nervous System: `team-bundle` XML Structure

2.3 Modular Design: Why Files and IDs Matter

3. Chapter 2: The BMad Orchestrator - The Maestro of the Method

3.1 Role and Activation: Setting the Stage

3.2 Universal Handlers: The Language of Action

3.3 Orchestrator-Specific Commands

3.4 Core Rules and Persona: Maintaining Coherence

Agents, Workflows, and Execution

4. Chapter 3: The Specialized Agents - The Expert Collective

4.1 Mary: The Business Analyst

4.2 John: The Product Manager

4.3 Winston: The Architect

4.4 Sally: The UX Designer

4.5 Bob: The Scrum Master

5. Chapter 4: The Workflow Execution Engine - Precision and Guidance

5.1 The Heart of Automation:

5.2 llm Mandates: The Al's Operating Instructions

5.3 WORKFLOW–RULES : Ensuring Structured Progress

5.4 The flow : Step-by-Step Logic

5.5 Execution Modes: Tailoring Interaction (normal vs. #yolo)

5.6 Supported Tags and Conditional Execution Patterns

Methods for Elicitation, Planning, and Solutioning

6. Chapter 5: Advanced Elicitation - Deepening Insights

6.1 `bmad/core/tasks/adv-elicit.xml`:The Dynamic Interaction Layer

6.2 Method Registry: `bmad/core/tasks/adv-elicit-methods.csv`

6.3 Logic and Rationale: Context-Aware Probing

6.4 Iterative Enhancement and User Control

7. Chapter 6: The Planning Phase - Defining the Product

7.1 brainstorm-project (Mary)

7.2 product-brief (Mary)

7.3 research (Mary)

7.4 create-prd (John)

7.5 create-epics-and-stories (John)

8. Chapter 7: The Solutioning Phase - Engineering the Blueprint

8.1 create-architecture (Winston)

8.2 create-ux-design (Sally)

Knowledge, Validation, and Lifecycle Operations

9. Chapter 8: The BMad Knowledge Base - Data for Decisions

9.1 decision-catalog.yaml: Guiding Architectural Choices

9.2 architecture-patterns.yaml: Mapping Requirements to Solutions

9.3 pattern-categories.csv : Classifying Consistency Rules

9.4 brain-methods.csv : A Toolkit for Creative Ideation

9.5 project-types.csv & domain-complexity.csv : Contextualizing Workflows

10. Chapter 9: Validation and Quality Assurance - The Integrity Check

10.1 The Role of checklist.md Files

10.2 Workflow Readiness and Status Tracking

10.3 Post-Generation Validation: Ensuring Compliance and Completeness

10.4 Rationale: Building Trust and Reducing Rework

11. Conclusion: The Future of Collaborative Al in Development

11.1 Synergies and Scalability

11.2 The Evolution of the BMad Method

11.3 The Human-Al Partnership Reinforced

Quizzes and Assessment

Quiz: Core Principles and Architecture

Quiz: Orchestrator Roles and Commands

Quiz: Agents and Collaboration Patterns

Quiz: Workflow Execution and Controls

Quiz: Knowledge Base and Validation

Final Survey

Course Feedback and Adoption Intent Survey

BMAD-METHOD Foundations, Ethics, Communication, and End-to-End Implementation is a practitioner-focused course that shows you how to plan, design, and run AI-enabled product development with rigor. You’ll learn the BMAD architecture—an orchestrator coordinating specialized agents through governed workflows—and see how data, commands, and artifacts move reliably across the system. The program blends ethics, governance, and practical delivery: from advanced elicitation and product definition to architecture and UX solutioning, workflow execution, validation, and lifecycle operations. You’ll work with concrete assets such as team-bundle XML, decision catalogs, architecture patterns, workflow rules, and checklists to ensure traceability, quality, and reproducibility. Whether you’re modernizing processes or scaling AI collaboration, you’ll gain a shared language for cross-functional teams, clear guardrails for LLM use, and methods to reduce rework while accelerating outcomes. By the end, you’ll be able to activate an orchestrator with a consistent persona, guide expert agents, tailor execution modes to risk, and connect decisions to evidence. This is the blueprint for trustworthy, enterprise-ready AI development.

BMAD-METHOD Foundations, Ethics, Communication, and End-to-End Implementation

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            <p>BMAD-METHOD Foundations, Ethics, Communication, and End-to-End Implementation equips practitioners to build AI-enabled products with rigor, clarity, and confidence. The course begins by positioning the BMAD-METHOD within modern AI-driven development, defining the scope, prerequisites, and success criteria so you understand how each module maps to stakeholder outcomes and tangible deliverables. It surfaces the real challenges of AI in development—ambiguity, bias, governance, and risk—then introduces the BMAD concepts, terminology, and mental models that resolve them. You will learn the core principles guiding the BMAD ecosystem—how an orchestrator coordinates specialized agents through structured workflows and tasks—and how these principles translate into better decisions for business, product, design, engineering, and delivery leaders.</p>
<p>From there, the journey moves into architecture and orchestration. You will examine the end-to-end system—tracing data, commands, and artifacts across orchestrator, agents, workflows, and tasks—to establish interfaces and boundaries for reliability and scale. A central emphasis is the team-bundle XML structure: its schema, identifiers, and configuration strategy, including versioning, reuse, and governance. You will see why modular design, file structures, and stable IDs underpin maintainability, auditability, traceability, and change control, and how orchestrator responsibilities, lifecycle, universal handlers, and command guardrails deliver execution guarantees, security, and coherent persona behavior.</p>
<p>The course then explores agents, workflows, and execution in depth. Meet the expert collective—Mary (Business Analyst), John (Product Manager), Winston (Architect), Sally (UX Designer), and Bob (Scrum Master)—and learn their collaboration protocols, handoffs, and artifact contracts. You will master the workflow execution engine’s lifecycle, modes, and controls: task graphs, state machines, retries, observability, and runbooks. The program details LLM mandates (instruction schemas, prompts, safety controls, and prompt versioning), workflow rules (preconditions, postconditions, gating checks, exceptions), flow logic (branching and human-in-the-loop checkpoints), execution modes (normal vs. #yolo with explicit risk trade-offs), and supported tags for conditional execution and templated reuse.</p>
<p>Methods for elicitation, planning, and solutioning provide the connective tissue for high-quality outcomes. Advanced elicitation methods reduce ambiguity and bias through context-aware probing and iterative user control, implemented via the adv-elicit XML task contract and a governed method registry. Planning modules translate insights into a product brief, research synthesis, PRD, and a well-structured backlog with clear KPIs, acceptance criteria, and dependency management. Solutioning modules guide the transition from requirements to architecture and UX design, using decision records, patterns, nonfunctional verification, accessibility, and usability validation to navigate trade-offs across quality attributes.</p>
<p>Finally, knowledge, validation, and lifecycle operations ensure integrity at scale. A reusable knowledge base—decision catalogs, architecture patterns, pattern categories, ideation toolkits, and project/domain taxonomies—connects decisions to evidence while accelerating consistency. Validation spans checklists, readiness criteria, dashboards, and post-generation verification with human review, all tied to a rationale that builds trust, reduces rework, and supports governance. The course concludes with forward-looking strategies for enterprise composition, growth roadmapping, standards and community evolution, and the ethical, inclusive communication practices that reinforce a durable human–AI partnership. Quizzes throughout and a final survey help cement understanding and guide adoption in your organization.</p>
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