Aidlc: Adaptive workflow steering rules for AI coding agents (github.com)

AI-DLC (AI-Driven Development Life Cycle) has emerged as a groundbreaking framework that transforms AI coding assistants into structured, verifiable software delivery workflows. The system integrates seamlessly with multiple platforms, including Claude Code, Kiro CLI, and GitHub Copilot, and features a core that operates independently of any specific harness. Users can begin the installation process through straightforward commands, ensuring a smooth setup across various operating systems without the need for external dependencies like Bun or Node.js. The significance of AI-DLC lies in its ability to enhance AI coding by maintaining context and coherence throughout the entire software development lifecycle. By implementing adaptive workflow steering rules, AI-DLC manages a substantial audit trail—covering 5 phases and 33 stages—from initialization to operation, thereby fostering accountability and collaboration among AI agents. Moreover, it supports multiple workflow profiles tailored for different development tasks, incorporating human approval gates and reviewed outputs. As generative AI remains prone to errors, the system emphasizes the importance of oversight, making it a vital tool for ensuring reliable and effective AI integration in software development processes.