Version: 0.1.0-beta.1 Author: Mohammad Maheri
The AI-* PDLC Family is part of AIFLC (AI Full Life Cycle) — a suite of injectable workflow packages that guide AI coding assistants through professional software delivery — from idea through architecture, workspace setup, governance, and test accountability.
Each package is a set of markdown files you drop into your IDE workspace. The AI reads them and gains structured expertise: it knows what to ask, what to produce, and when to hand off to the next package in the chain. No plugins, no APIs, no vendor lock-in.
Think of it as: Professional process knowledge, packaged so an AI assistant can execute it with human oversight at every gate.
╔════════════════ PORTFOLIO LAYER · scope = MANY projects ════════════════╗
(optional)
AI-ILC ⇢ AI-PILC ⇢ AI-PPM
Decide it Initiate it Govern it (portfolio of N projects)
╚═════════════════════════════════╤═══════════════════════════════════════╝
│
AI-FLO Route it — package-to-package
│ flow on the edge between layers
╔════════════════ PROJECT LAYER · scope = ONE project ════════════════════╗
AI-POLC ──► AI-UXD ──► AI-ADLC ──► AI-DWG ──► AI-DLC v1 (build) ¹
Own it Design UX Design it Prepare it ▲
│
AI-POLC ⇄ AI-DLC v1 (back-and-forth)┘
AI-DLC v1 ⇢ AI-UXD+AI-POLC (feedback)
AI-GCE + AI-TGE ──── alongside AI-DLC v1 (continuous quality) ────►
Guard it Test it
╚═════════════════════════════════════════════════════════════════════════╝
¹ AI-DLC v1 = Amazon's open-source build lifecycle (not ours; we feed it).
| Layer | Package | Type | What It Does |
|---|---|---|---|
| Portfolio | AI-ILC | Interactive workflow | Evaluate raw ideas → Approved Idea Brief |
| Portfolio | AI-PILC | Interactive workflow | Raw requirement → Project Initiation Package (PIP) |
| Portfolio | AI-PPM | Adaptive portfolio engine | Multiple PIPs → Portfolio governance & prioritization |
| Edge | AI-FLO | Router / orchestration engine | Package-to-package flow orchestration |
| Project | AI-ADLC | Interactive workflow | Requirements → Architecture Package (AP) |
| Project | AI-UXD | Interactive workflow | PIP/AP → UX Design Package (personas, flows, design system) |
| Project | AI-POLC | Interactive workflow | PIP/AP → Product Backlog Package (PBP) |
| Project | AI-DWG | One-time generator | AP + PBP + UXP → Ready-to-code workspace |
| Project | AI-GCE | Adaptive governance engine | Workspace → Compliance enforcement layer |
| Project | AI-TGE | Test governance engine | Workspace → Test strategy, register, coverage tracking |
AI-DLC v1 (awslabs/aidlc-workflows) is NOT part of this suite — it's Amazon's open-source build lifecycle. Our chain produces the workspace AI-DLC v1 consumes.
AI-DFE (Data Fabric Engine) is a family-scoped companion — it gathers data from all packages and distributes structured JSON for dashboards and status roll-ups. It runs alongside the chain rather than as a linear step, so it is not shown as a chain row above.
- New project from scratch? Start with AI-PILC (project initiation)
- Have requirements, need architecture? Start with AI-ADLC
- Have architecture, need a workspace? Start with AI-DWG
- Have an idea to evaluate? Start with AI-ILC
- Managing multiple projects? Start with AI-PPM
Use the interactive installer to pick packages and have them placed in the right location for your platform:
# Windows
.\installer\install.ps1
# macOS / Linux
./installer/install.shOr install manually — packages are independently installable. You decide how many to run:
- Solo — install a single package on its own. Each one is fully self-contained and produces complete, professional output without any other package present.
- Selective family — install any subset that fits your work. The chain is modular, so combinations like
AI-PILC + AI-ADLC,AI-ADLC + AI-DWG, orAI-GCE + AI-TGEwork without requiring the packages in between. When a package detects a sibling's output markers, it enriches its own work with that context; when it doesn't, it runs standalone. - Full family — install the whole chain for end-to-end coverage from idea to test accountability.
Install each package one at a time — adding a package never requires reinstalling the others.
Compatibility is per package, not suite-wide. Every package ships its own setup/INSTALL.md with platform-specific setup, so you can run different packages on different assistants in the same workspace if you want. Supported targets per package:
- Kiro (VS Code-based)
- Amazon Q Developer
- Cursor
- Claude Code
- Cline (VS Code extension)
- GitHub Copilot (
⚠️ partial — workspace-level instructions only)
Each INSTALL.md documents the exact destination paths for that platform. The general pattern is the same everywhere: place the package's *-rules/core-workflow.md where your AI reads always-loaded steering, and place the *-rule-details/ folder where the workflow can resolve it on demand. See the Compatibility table below for the full matrix.
Open your IDE chat and tell the AI to use the package:
Using AI-PILC, help me initiate this project from my requirements
The AI reads the package's core workflow, adopts the appropriate professional role, and guides you through each stage with gates for your approval.
If you are injecting packages into an existing project (brownfield), please take the following precautions:
- Back up first. Commit all work to version control or take a snapshot before injection.
- Use a test branch. Try the package in an isolated branch before applying to your main codebase.
- Review output structure. Each package documents what it generates — check for conflicts with your existing files and folders.
- No warranty. This software is provided "AS IS" under Apache 2.0. The author accepts no liability for overwritten files, broken pipelines, lost data, or any other damage resulting from integration into existing environments. You are solely responsible for determining appropriateness.
See LICENSE and NOTICE for full liability and warranty disclaimer details.
- Human-in-the-loop. Every stage has an approval gate. The AI proposes; you decide.
- Injectable. Drop files into any workspace. No plugins, no lock-in.
- Professional quality. Each package embeds domain expertise (PMO, CTO, DevOps, QA). Output reads as if produced by a senior professional.
- Chain-aware. Packages can hand off to each other via state markers. But each works standalone too.
- Platform-agnostic. Works with any AI coding assistant that reads workspace files.
- Adaptive depth. Three tiers (Minimal / Standard / Comprehensive) adapt to project complexity.
- Generic. Zero project-specific content. Works for any project, any domain, any technology.
ai-family/
├── README.md ← You are here
├── LICENSE ← Apache 2.0
├── NOTICE ← Attribution requirement
├── CONTRIBUTING.md ← How to contribute
├── SECURITY.md ← Vulnerability reporting
│
├── ai-ilc/ ← Idea evaluation workflow
├── ai-pilc/ ← Project initiation workflow
├── ai-adlc/ ← Architecture design workflow
├── ai-uxd/ ← UX design workflow
├── ai-polc/ ← Product ownership workflow
├── ai-dwg/ ← Workspace generator
├── ai-ppm/ ← Portfolio management engine
├── ai-flo/ ← Flow router engine
├── ai-gce/ ← Governance compliance engine
├── ai-tge/ ← Test governance engine
├── ai-dfe/ ← Data fabric engine (family-scoped companion)
│
├── installer/ ← Interactive package installer (PowerShell + Bash)
├── contracts/ ← Cross-package conventions & contracts
├── narrative/ ← Whitepapers and HOW documents
└── knowledge_docs/ ← Design patterns and reference material
Full chain (maximum value): AI-ILC → AI-PILC → AI-POLC → AI-UXD → AI-ADLC → AI-DWG → AI-GCE + AI-TGE → AI-DLC v1 (build)
Standalone (each package works independently):
- AI-PILC alone produces a professional Project Initiation Package
- AI-ADLC alone produces a complete Architecture Package
- AI-DWG alone generates a workspace from any architecture document
- AI-GCE alone derives governance for any existing workspace
- AI-TGE alone assesses test coverage against architectural commitments
When used in the chain, each package detects its predecessor's output markers and enriches its own work with that context. When used standalone, it gracefully handles missing predecessors.
| Platform | Supported | Install Guide |
|---|---|---|
| Kiro | ✅ | Each package's setup/INSTALL.md |
| Amazon Q Developer | ✅ | Each package's setup/INSTALL.md |
| Cursor | ✅ | Each package's setup/INSTALL.md |
| Cline | ✅ | Each package's setup/INSTALL.md |
| Claude Code | ✅ | Each package's setup/INSTALL.md |
| GitHub Copilot | Each package's setup/INSTALL.md (workspace-level instructions only) |
|
| Any other platform | ✅ | Universal Setup section in each INSTALL.md |
Compatibility is per package — every package ships the same platform coverage. For unlisted IDEs, follow the Universal Setup steps: place
core-workflow.mdwhere your AI reads always-loaded steering and*-rule-details/where the workflow can resolve it.
See CONTRIBUTING.md for guidelines and our Contributor License Agreement.
To report a vulnerability, see SECURITY.md.
Apache License 2.0 with Attribution Addendum
Free to use for personal, commercial, educational, and organizational purposes. Modify and distribute freely. One requirement:
Any distributed product substantially based on this work must include: "Built on AIFLC by Mohammad Maheri — LinkedIn"
See LICENSE and NOTICE for full terms.
Copyright: © 2026 Mohammad Maheri
Part of AIFLC — AI Full Life Cycle · The AI- PDLC Family · See the AIFLC Roadmap*