@fabriqa.ai/fabriqaoss

fabriqa-oss

AI-native software development with multi-agent orchestration.

fabriqa-oss implements the AI-Driven Development Lifecycle (AI-DLC) methodology as a set of markdown-based agents that work with your favorite AI coding tools.

Quick Start

Installation

[!NOTE] Do not use npm if you want to always get the latest version. Use the npx command below.

npx @fabriqa.ai/fabriqaoss@latest install

The installer detects your AI coding tools (Claude Code, Cursor, GitHub Copilot) and sets up:

• Agent definitions and skills
• Memory bank structure for context persistence
• Slash commands for easy agent invocation

Initialize Your Project

Open your AI Asisted Tool (Claude Code, Cursor, GitHub Copilot) and run the following commands:

# Start the Master Agent
/fabriqa-master-agent

# Then type:
project-init

This guides you through establishing:

• Tech Stack - Languages, frameworks, databases, infrastructure
• Coding Standards - Formatting, linting, naming, testing strategy
• System Architecture - Architecture style, API design, state management
• UX Guide - Design system, styling, accessibility (optional)
• API Conventions - API style, versioning, response formats (optional)

Create Your First Intent

/fabriqa-inception-agent intent-create

An Intent is your high-level goal:

• "User authentication system"
• "Product catalog with search"
• "Payment processing integration"

The agent will:

• Ask clarifying questions to minimize ambiguity
• Elaborate into user stories and NFRs
• Define system context
• Decompose into loosely-coupled units

Plan and Execute Bolts

# Plan bolts for your stories
/fabriqa-inception-agent bolt-plan

# Execute a bolt
/fabriqa-construction-agent bolt-start

Each bolt goes through validated stages:

• Domain Model - Model business logic using DDD principles
• Technical Design - Apply patterns and make architecture decisions
• ADR Analysis - Document significant decisions (optional)
• Implement - Generate production code
• Test - Verify correctness with automated tests

Human validation happens at each stage gate.

What is AI-DLC?

AI-DLC is a reimagined software development methodology where AI drives the conversation and humans validate. Unlike traditional Agile where iterations span weeks, AI-DLC operates in Bolts - rapid iterations measured in hours or days.

"Traditional development methods were built for human-driven, long-running processes. AI-DLC reimagines the development lifecycle with AI as a central collaborator, enabling rapid cycles measured in hours or days rather than weeks."

AI-DLC vs Traditional Methods

Aspect	Agile/Scrum	AI-DLC
Iteration duration	Weeks (Sprints)	Hours/days (Bolts)
Who drives	Human-driven, AI assists	AI-driven, human-validated
Design techniques	Out of scope	Integrated (DDD, TDD, BDD)
Task decomposition	Manual	AI-powered
Phases	Repeating sprints	Rapid three-phase cycles (Inception → Construction → Operations)
Rituals	Daily standups, retrospectives	Mob Elaboration, Mob Construction

How It Works

fabriqa-oss provides four specialized agents that guide you through the entire development lifecycle:

                    ┌─────────────────┐
                    │  Master Agent   │  Orchestrates & navigates
                    └────────┬────────┘
                             │
        ┌────────────────────┼────────────────────┐
        ▼                    ▼                    ▼
┌───────────────┐   ┌───────────────┐   ┌───────────────┐
│   Inception   │ → │ Construction  │ → │  Operations   │
│     Agent     │   │     Agent     │   │     Agent     │
└───────────────┘   └───────────────┘   └───────────────┘
  Capture intent      Execute bolts      Deploy & monitor
  Define units        Build & test       Verify & scale
  Plan stories        Validate stages

The Three Phases

Phase	Agent	Purpose	Key Outputs
Inception	Inception Agent	Capture intents, elaborate requirements, decompose into units	User stories, NFRs, Unit definitions, Bolt plans
Construction	Construction Agent	Execute bolts through domain design → logical design → code → test	Domain models, Technical designs, Code, Tests
Operations	Operations Agent	Deploy, verify, and monitor	Deployment units, Monitoring, Runbooks

Key Concepts

Intent

A high-level statement of purpose that encapsulates what needs to be achieved - whether a business goal, feature, or technical outcome. It serves as the starting point for AI-driven decomposition.

Unit

A cohesive, self-contained work element derived from an Intent. Units are loosely coupled and can be developed independently. Analogous to a Subdomain (DDD) or Epic (Scrum).

Bolt

The smallest iteration in AI-DLC, designed for rapid implementation. Unlike Sprints (weeks), Bolts are hours to days. Each bolt encapsulates a well-defined scope of work.

Type	Best For	Stages
DDD Construction	Complex business logic, domain modeling	Model → Design → ADR → Implement → Test
TDD Construction	Well-defined interfaces, test-first	Test → Implement → Refactor
BDD Construction	User-facing features, acceptance criteria	Scenario → Implement → Verify
Spike	Research, exploration, unknowns	Explore → Document

Memory Bank

File-based storage for all project artifacts. Maintains context across agent sessions and provides traceability between artifacts.

Standards

Project decisions that inform AI code generation. Standards ensure consistency across all generated code and documentation.

Project Structure

After installation:

.fabriqa/
├── manifest.yaml              # Installation manifest
└── aidlc/                     # AI-DLC flow
    ├── agents/                # Agent definitions
    ├── skills/                # Agent capabilities
    ├── templates/             # Artifact templates
    │   └── standards/         # Standards facilitation guides
    └── memory-bank.yaml       # Memory bank schema

memory-bank/                   # Created after project-init
├── intents/                   # Your captured intents
│   └── {intent-name}/
│       ├── requirements.md
│       ├── system-context.md
│       └── units/
├── bolts/                     # Bolt execution records
├── standards/                 # Project standards
│   ├── tech-stack.md
│   ├── coding-standards.md
│   └── ...
└── operations/                # Deployment context

Agent Commands

Master Agent

/fabriqa-master-agent

Command	Purpose
project-init	Initialize project with standards
analyze-context	View current project state
route-request	Get directed to the right agent
explain-flow	Learn about AI-DLC methodology
answer-question	Get help with any fabriqa question

Inception Agent

/fabriqa-inception-agent

Command	Purpose
intent-create	Create a new intent
intent-list	List all intents
requirements	Elaborate intent requirements
context	Define system context
units	Decompose into units
story-create	Create stories for a unit
bolt-plan	Plan bolts for stories
review	Review inception artifacts

Construction Agent

/fabriqa-construction-agent

Command	Purpose
bolt-start	Start/continue executing a bolt
bolt-status	Check bolt progress
bolt-list	List all bolts
bolt-replan	Replan bolts if needed

Operations Agent

/fabriqa-operations-agent

Command	Purpose
build	Build the project
deploy	Deploy to environment
verify	Verify deployment
monitor	Set up monitoring

Why fabriqa-oss?

AI-Native, Not AI-Retrofitted

Built from the ground up for AI-driven development. AI-DLC is a reimagination based on first principles, not a retrofit of existing methods.

Human Oversight as Loss Function

Validation at each stage catches errors early before they cascade downstream. Each validation transforms artifacts into rich context for subsequent stages.

Design Techniques Built-In

DDD, TDD, and BDD are integral to the methodology - not optional add-ons. This addresses the "whitespace" in Agile that has led to quality issues.

Tool Agnostic

Works with Claude Code, Cursor, GitHub Copilot, and other AI coding assistants. Markdown-based agents work anywhere.

Context Persistence

Memory bank ensures AI agents have full project context across sessions. All artifacts are linked for backward and forward traceability.

Supported Tools

Tool	Status	Installation
Claude Code	Full support	Slash commands in .claude/commands/
Cursor	Full support	Rules in .cursor/rules/ (.mdc format)
GitHub Copilot	Full support	Agents in .github/agents/ (.agent.md format)
Google Antigravity	Full support	Agents in .agent/agents/

FAQ

Q: Agents don't seem to remember previous context? Each agent invocation starts fresh. Agents read context from the Memory Bank at startup. Ensure artifacts are saved after each step.

Q: How do I reset project state? Clear the memory-bank/ directory to reset all artifacts. To remove fabriqa-oss entirely, delete the .fabriqa/ directory and tool-specific command files.

Q: Can I use fabriqa-oss with existing Agile workflows? AI-DLC is designed as a reimagination, not a retrofit. However, familiar concepts (user stories, acceptance criteria) are retained to ease transition.

Q: What project types is this suited for? fabriqa-oss is designed for building complex systems that demand architectural complexity, trade-off management, and scalability. Simpler systems may be better suited for low-code/no-code approaches.

Resources

• AI-DLC Specification (AWS)
• fabriqa.ai

License

MIT License - see LICENSE for details.

Built with AWS' AI-DLC methodology by the fabriqa team.