specs.md - ai-dlc spec driven development framework
This is a living engineering reference for architects, engineers, platform teams, and technical leaders. It brings together the decisions and habits that make cloud-native systems resilient, observable, secure, and easier to evolve.
AI-DLC (AI-Driven Development Life Cycle) claude code plugin
AIDLC × AgenticOps — plugin marketplace that extends Claude Code and Kiro with agentic operations for the AWS AI-Driven Development Lifecycle (Inception → Construction → Operations).
Prompts for AI-Driven Development Lifecycle (AI-DLC v1)／AI-DLC（v1）プロセスのためのプロンプトです
A lightweight, framework-agnostic persistent memory graph for AI coding assistants.
The AI software factory for your team: specs go in, reviewed and tested pull requests come out. An assembly line of agents (research → specify → plan → tasks → implement → review → verify → deliver) with human gates, on GitHub Spec Kit and the Pi Coding Agent SDK, following AIDLC. GitHub/Jira/Confluence/Linear/Slack integrations.
Sample code: a live, read-only browser dashboard for AI-DLC v2 runs. Shows stage and unit-of-work progress, active agents, approval gates waiting on you, stalls and errors, and a timeline of agent work versus human review. Reads the files AI-DLC already writes. Python standard library only, runs locally
Injectable workflow packages that guide AI coding agents through professional software delivery — 11 packages from idea to test accountability.
Delivery visibility for PMs and delivery managers in AI-driven development (AI-DLC) — a read-only skill that finds where work waits on human decisions, with consent-gated nudges.
AI-DLC (AI-Driven Development Life Cycle) claude code plugin v2
Claude Code marketplace plugin for AI-DLC (AI-Driven Development Life Cycle) — adaptive software development workflow with structured requirements, design, code generation, and testing
Spec-driven AI development lifecycle for Claude Code — spec-kit + AI-DLC fused, with hook-enforced human-approval gates. Installable plugin + marketplace.
A living, queryable knowledge graph on the AI-native software product development lifecycle (AIDLC) — 12 lifecycle phases, the AI-native foundation, credibility-flagged case evidence, and industry JD signals. Built to be read by agents (Claude Code) and humans (Obsidian).
Experimental fork of awslabs/aidlc-workflows — adds Host Capability Layer + Project Mode Layer for cross-IDE portability (Claude Code / Kiro / Amazon Q / Cursor / Cline / Copilot).
Local-first AIDLC evidence compiler for portable, verifiable AI system release passports.
The operator's manual for AI-supported software development. Tool-agnostic. Governance-first. Measured per squad.
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