Commands.com: The Multi-Agent Workspace
Enable Claude, GPT-4, and Gemini to build software together
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David Tannenbaum

Commands.com: The Multi-Agent Workspace - Enable Claude, GPT-4, and Gemini to build software together

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Commands.com is a native desktop workspace for multi-agent AI orchestration. Enable Claude, GPT-4, and Gemini to build software together. Create visual pipelines that move from exploration to production code using AI consensus and peer review. Featuring clean context handoffs, live execution graphs, and human-in-the-loop approval gates, Commands transforms isolated LLMs into a unified engineering team. Stop copy-pasting between browser tabs and command your AI workforce today.

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David Tannenbaum
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Hi Product Hunt! 👋 I'm David, the creator of Commands.com. Over the last year of building software, my workflow devolved into a chaotic mess of browser tabs. I’d use Claude for code implementation, Gemini for brainstorming, and GPT for auditing. The models were incredible, but I was the bottleneck—spending half my day just copy-pasting context and prompts between different windows. I realized that single-prompting just wasn't cutting it for building full, robust applications. I needed these models to actually talk to each other. So, I built a native desktop app to fix it. Commands.com Agent Workspace is a visual workspace that lets you orchestrate different LLMs to work together as a unified development team. Instead of treating AI as a simple chatbot, Commands lets you build automated product pipelines: 🧠 Multi-Agent Collaboration: Put Claude, GPT, and Gemini in a "Room" together. They can each build their own prototype of a feature, review each other's code, and use consensus to output a superior final spec. ⛓️ Visual Pipelines: Chain your workflow into distinct stages (e.g., Explore -> Prototype -> Spec -> Implementation -> Review) with clean context handoffs between each stage so the models stay focused. 🛑 Human-in-the-Loop: Built-in approval gates mean you can review the architecture and steer the direction before the agents burn through your token budget writing production code. 📊 Deep Observability: A live execution graph lets you watch exactly which node is running and track the actual conversations between the models in real-time. We are opening up our private beta today. I built this to scratch my own itch as a developer, but I'm incredibly excited to see what kind of multi-agent workflows this community can come up with. I’ll be hanging out in the comments all day! I would love to hear your feedback, answer any questions about the architecture under the hood, or just chat about the future of multi-agent orchestration. Cheers, David