SquansQ – I Built a Multi-Agent AI Dev Platform to Stop Juggling Claude Code Windows

If you’ve spent any serious time building with AI coding tools, you’ve probably hit the same wall I did.
You open Claude Code to tackle a task. Then you realise you need something running in parallel — so you open another window. Then another. Before long you’ve got four or five terminals going, no real picture of which agent is doing what, and you’re spending more mental energy managing the chaos than actually shipping code.
That friction is what drove me to build SquansQ — a browser-based, multi-agent development orchestration platform that gives you a single command center for all your AI coding agents.
In this post I’ll walk you through what it is, why I built it, what’s under the hood, and where it’s going.

The Problem: Claude Code Is Brilliant — But It’s Single-Threaded
Claude Code is genuinely impressive for development. But the moment you try to scale beyond one task, the workflow breaks down fast.
There’s no built-in way to run multiple agents in parallel and keep track of them. You end up doing what I did — juggling multiple terminal windows, losing context, manually switching between projects, and constantly asking yourself “which window was handling the auth refactor again?”
The same issue exists with other AI dev tools like Loveable. They’re powerful in isolation, but the moment you want to coordinate work across multiple threads or projects simultaneously, you’re stuck.
What I wanted was something closer to how a real engineering team works — multiple people (or in this case, agents) working on different things at the same time, with one person keeping a view of the whole board.

The Solution: SquansQ
SquansQ is a browser-based multi-agent orchestration platform built on top of Claude Code. The core idea is simple: give yourself one interface to spin up, manage, monitor, and coordinate multiple AI coding agents — all running in parallel, each isolated in their own environment.
Instead of being bottlenecked by a single terminal and a single thread of thought, you distribute the work across a team of agents and keep control of the bigger picture from one dashboard.
Here’s what that looks like in practice.

Key Features
Multiple Workspaces and Projects
Within SquansQ you can create multiple workspaces, and within each workspace you can have multiple projects. Each project gets its own Claude Code agent running in an isolated git worktree — meaning agents don’t step on each other’s code.
Flipping between workspaces is instant, and each one shows you the live Claude Code session for that project.
The Root Agent — Your Orchestrator
At the top of the system sits the Root Agent: an orchestrator powered by its own MCP tools that handles planning and dispatching work to individual worker agents.
The Root Agent follows a five-step workflow:

Orient — assess the current state of all active projects
Plan — structure work into Release Trains and Atomic Tasks
Dispatch — spawn WorkerBee agents to handle each task
Monitor — track progress in real time via post-commit hooks
Complete — land finished trains and summarise outcomes

This means you can hand the Root Agent a high-level goal and let it figure out how to break it down and assign it — rather than manually managing every sub-task yourself.
WorkerBees: Isolated Claude Code Agents
Each WorkerBee is an individual Claude Code agent running in its own isolated git worktree, with its own branch and config directory. They’re completely independent of each other, which means you can run as many as you need without conflicts.
Release Trains and Atomic Tasks
Work is structured into two levels:

Release Trains are feature-area units of work. They come with a description that becomes the agent’s briefing document.
Atomic Tasks are the discrete, deliverable-level items within a Release Train — tracked on the Kanban board.

This structure gives you a clear hierarchy from high-level goal all the way down to individual agent output.
Native Kanban Board
Every task across every project lands on a built-in Kanban board. Columns for open, in progress, in review, and done — so you always have a birds-eye view of what’s actually happening, no matter how many agents are running.
When you context-switch between projects (and you will), the Kanban keeps you grounded.
Live Terminals and the Console Panel
Each agent gets a live terminal powered by xterm.js, with configurable pane layouts. You can watch what your agents are doing in real time.
There’s also a console panel — a browser-based command interface for running commands directly, without needing to drop into a terminal. Handy when you want to stay in the UI.
The sq CLI
For those who prefer the command line, SquansQ ships with a full sq CLI that gives you complete control from your terminal. You can list agents, kill agents, dispatch tasks, and more — all without touching the browser.
Real-Time Metrics and Event Streaming
The dashboard streams live events from all your agents — what they’re doing, what hooks have fired, and what’s changed. Token tracking is in place, and cost tracking is on the roadmap (right now it’s genuinely hard to pull Claude Code cost data directly, which is something I’m working on).
GitHub PR Support
WorkerBees can create GitHub PRs directly from their worktrees, which means the output of each agent can flow naturally into your existing review process.

Under the Hood: The Tech Stack
For anyone curious about what’s powering it:
LayerTechnologyServerNode.js, Express, TypeScriptClientReact, Vite, ZustandDatabaseSQLite via libsqlReal-timeWebSocketsTerminalsxterm.jsAgent ManagementClaude Code CLI (PTY processes)OrchestrationHTTP JSON-RPC 2.0 MCP server
Agents run as PTY processes managed by the Claude Code CLI, which is what gives you the live terminal output. The real-time dashboard is WebSocket-powered, so everything updates as it happens.

Getting Started
SquansQ supports three installation paths depending on your setup:
Local development via npm
npm install
npm run dev
Docker container
docker pull squansq/squansq
docker run squansq/squansq
Docker Compose
docker-compose up
The sq CLI can be installed globally via npm or run directly. Full setup instructions are in the GitHub repo.

What’s Still in Progress
I want to be straight about where things are. SquansQ is a working, usable platform — but it’s actively evolving.
A few things I’m still working on:

Cost tracking — token usage is visible but getting accurate cost data directly from Claude Code is tricky. This is a known gap.
Gemini integration — I want to add Gemini alongside Claude so you can choose your model per agent or per project.
Idle agent handling — occasionally a dispatched agent goes idle unexpectedly. I’m debugging the root cause.
UI polish — it’s functional, but there’s room to refine the layouts and flows.

The goal was to get something real in front of people early and build from there. If you’re using it and hit issues or have ideas, I want to hear about it.

Why This Changes How I Work
The biggest shift isn’t any single feature — it’s the overall mental model.
Before SquansQ, I had one agent, one thread, one bottleneck. My pace was limited by how fast a single Claude Code session could move.
Now I can hand off a set of tasks, let multiple agents work in parallel, and check back in via the Kanban or the dashboard. I’m spending more time thinking about architecture and direction, and less time babysitting terminals.
It’s still early, but even in this form it’s meaningfully changed how productive I feel on large builds.

Try It / Follow Along
SquansQ is open source under the MIT license.
🔗 GitHub: https://github.com/tarvitave/squansq-releases
I’ll be posting updates here and on YouTube as the platform evolves — new features, demos, and honest walkthroughs of what’s working and what isn’t. If you’re building with AI coding agents and running into the same coordination pain, give it a look.
And if you’ve built something similar, or have ideas for where this should go — drop a comment. I’m genuinely interested in how other people are solving this.

Colin Wynd builds AI-powered developer tools and writes about the process.