ClosedLoop.ai

Documentation

The full reference for ClosedLoop.ai — the spec-driven, AI-first delivery platform that closes the loop on your SDLC.

Welcome to the ClosedLoop.ai documentation hub.

ClosedLoop.ai is a platform for team-based agentic software development. It combines a browser-based control plane, a desktop execution client, and a suite of Claude Code plugins into a single system that turns scoped intent into shipped code through repeatable, artifact-bound loops.

This documentation is organized so both humans and AI agents can use it as ground truth:

  • Getting started — the fastest path from install to a first completed loop.
  • Mechanisms — how the control plane, desktop gateway, runtime, loops, judges, and self-learning actually work.
  • Concepts — the mental models behind the product and the philosophy of spec-driven AI-first delivery.
  • Workflows — the delivery paths from PRD to PR, including parallel features, code review, and cross-repo coordination.
  • Resources — troubleshooting, FAQs, reference tables, comparisons, and templates.
  • Glossary — precise, reusable definitions of every first-class concept.

Start here

What ships with ClosedLoop.ai

SurfaceWhat it does
Web app (control plane)Defines work, stores artifacts, coordinates teams, launches loops, surfaces approvals, renders activity.
Desktop clientElectron app that exposes a signed localhost HTTP gateway and a cloud relay so the control plane can safely drive local git, filesystem, code review, and AI coding sessions.
Claude Code pluginsSix installable plugins — bootstrap, code, code-review, judges, platform, self-learning — that ship the multi-agent orchestration used by loops.
RuntimeThe execution layer (your machine plus cloud-assisted orchestration) that runs loops inside a sandbox and returns reviewable output.
ArtifactsPRDs, implementation plans, critic reviews, judge reports, code maps, learnings, and code review findings — stored per-session and per-org.

Why ClosedLoop.ai exists

LLMs are extraordinary at generating content. They are unreliable at being repeatably correct.

ClosedLoop.ai closes that gap by attaching every loop to a durable artifact, gating every phase with deterministic validation, and grading every output with LLM-as-judge evaluators that score against the original intent.

The result is a system where tickets are the work (not just tracking the work that's done elsewhere), context is captured, the progress of work across a team is immediately visible to everyone, and sprints of scope can land in a few PRs with minimal revisions.

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