AI-Native SDLC Orchestration
An open-source, local-first SDLC orchestration platform that turns separate AI coding terminals into a persistent, supervised software-development team.
The Problem
Modern AI development tools operate in isolated, ephemeral sessions. When a session ends, context is lost. Scaling AI in software engineering requires more than code generation—it requires a persistent supervisor capable of managing state, governance, handoffs, and continuity across multiple AI engines.
The Constraints
The system had to be local-first, integrate natively with GitHub workflows, maintain absolute deterministic control over the environment, and operate reliably without locking users into a proprietary cloud ecosystem.
Capabilities Utilized
- ▪SDLC Orchestration
- ▪Local-First Architecture
- ▪Process Automation
- ▪AI Engineering
The Approach
We architected an orchestration layer that sits between the developer, their repository, and their AI tools. It leverages Tmux-backed sessions, searchable memory, and structured project rules so that an accountable human "Project Master" can direct specialized AI "Builders."
The System
TangleClaw natively coordinates Claude Code, Codex, Antigravity, Aider, and OpenClaw via the Medusa switchboard. It provides full transcript search, audit metrics, port collision prevention, and automated startup/wrap workflows—all from a centralized dashboard.
The Outcome
We use TangleClaw daily at Visual Works to build and scale our clients' complex systems. By continuously improving the very tool that helps us build all the other tools, we maintain an accelerating, compound advantage in technical execution.