pdlc-autopilot

You can orchestrate end-to-end SDLC workflows by coordinating Director, Actor, and Critic roles to manage requirements, design, tasks, implementation, and validation. This reduces manual overhead and ensures traceability across the entire product development lifecycle.

AI-driven batched workflow execution groups work by file, assigns actors to each group, and runs parallel validation. This Director/Actor/Critic pattern ensures efficient processing and dual-perspective quality validation across multiple development tasks simultaneously.

Yes, you can resume feature development workflows after interruptions because the system persists workflow state in a spec.json file. This stateful recovery mechanism allows autonomous progression and supports continuing work across batched tasks seamlessly.

The SDLC orchestration loop auto-generates missing artifacts such as requirements, design documents, and task lists. It then applies dual-perspective validation to ensure these auto-generated artifacts meet quality standards before proceeding.

The best way to start an autonomous SDLC loop for implementing specs is to trigger the workflow with a simple intent command like saying "SDLC". This initiates the centralized orchestration layer to handle the end-to-end feature development process.

Centralized SDLC orchestration reduces drift by applying structured Director, Actor, and Critic roles to coordinate requirements and validation. It ensures traceability and automates artifact generation, minimizing manual overhead and keeping development aligned with original specs.