---
title: "ai-dlc"
description: "End-to-end AI-Driven Development Lifecycle workflow: Inception, Construction, Integration, and fast-path bug fixes, with human approval gates at every stage."
canonical: https://agentpluginsdirectory.com/plugins/ai-dlc
last-updated: 2026-09-23
---

# ai-dlc
End-to-end AI-Driven Development Lifecycle workflow: Inception, Construction, Integration, and fast-path bug fixes, with human approval gates at every stage.
- Slug: ai-dlc
- Publisher: Praveen Singh
- Repository: https://github.com/PraveenKS30/ai-dlc
- Manifest: plugin.json
- Version: 1.1.0
- License: UNLICENSED
- Category (editorial): productivity
- Skills: 8 (ai-dlc-config, ai-dlc-construction, ai-dlc-fix, ai-dlc-inception, ai-dlc-integrate, ai-dlc-methodology, ai-dlc-status, ai-dlc-workspace-setup)
- MCP servers: 0
- Stars: 0
- Repository created: 2026-08-09
- Repository last pushed: 2026-08-09
- Publisher type: User
- Listing: https://agentpluginsdirectory.com/plugins/ai-dlc
- Schema: https://agent-plugins.org/schemas/1.0.0/plugin.schema.json

## What ai-dlc does, in the publisher's words

Run the AI-Driven Development Lifecycle methodology end to end with your AI coding agent, plan before you build, keep a human approving every stage, and leave a traceable trail of why each decision was made.

This is an Agent Plugins v1.0.0 package. Install it into a compatible client and your agent gains eight skills covering the full lifecycle from a one-paragraph idea to merged, tested code.

Without a methodology, an AI agent given "build me a booking service" will start writing files immediately, make a dozen architectural decisions you never saw, and leave you reviewing a large diff after the fact.

From the project README, punctuation lightly normalized. Full text: https://raw.githubusercontent.com/PraveenKS30/ai-dlc/HEAD/README.md

## Skills

- ai-dlc-config: Configure AI-DLC workflow behavior, depth levels, approval gates, and agent preferences. Use when the user wants to view or change how the workflow behaves for this project.
- ai-dlc-construction: Execute the AI-DLC Construction phase with functional design and code generation for each unit of work. Use once Inception is complete and Units of Work are approved, to design and implement one specific Unit.
- ai-dlc-fix: Fast-path bug fix workflow with TDD-first approach for well-understood bugs that do not need the full inception-construction pipeline. Use for bug fixes and small, well-scoped enhancements on an existing project.
- ai-dlc-inception: Execute the AI-DLC Inception phase to plan and architect a software project with requirements gathering, workflow planning, and application design. Use when starting a new project or a significant new feature, before any code is written.
- ai-dlc-integrate: Verify and integrate completed Units of Work, readiness checks before a pull request, cross-Unit interface drift review, dependency-ordered merging, and a full integration build and test pass once all Units are merged. Use when a Unit is code-complete, when reviewing a Unit's PR, or when closing o…
- ai-dlc-methodology: Comprehensive reference for the AI-Driven Development Lifecycle methodology, a post-Agile framework combining systematic planning with AI-augmented execution. Use when the user asks what AI-DLC is, how it compares to Agile, or which stage/skill to use next.
- ai-dlc-status: Check AI-DLC workflow status, current phase, stage progress, and pending approvals. Use when the user asks what state the project is in, what's next, or what is still waiting on approval.
- ai-dlc-workspace-setup: Set up a multi-repo development workspace from a project one-pager document, then launch AI-DLC. Use when starting a project that spans more than one repository and you have a one-pager describing it.

Descriptions come from the frontmatter of each SKILL.md, punctuation lightly normalized.