# One Roof: Orchestrating Multiple Coding Agents for Chorus Coding A macOS mission control center to manage multiple AI coding agents simultaneously. - **Source:** [Hacker News: Show HN](https://news.ycombinator.com) - **Published:** 2026-11-02 - **Topic:** [Software & Engineering](https://brifing.si/c/engineering) - **Original article:** - **On Brifing:** https://brifing.si/s/8563801b-7588-4b0c-b0f3-53b878de66d0 ## Unified Agent Management One Roof serves as a mission control center for developers utilizing multiple AI coding agents like Claude Code, Codex, and Gemini. Instead of juggling fragmented terminal windows, it centralizes all sessions into a single inbox. This allows users to maintain oversight while agents perform specialized tasks like planning, building, and reviewing code. ## The Chorus Coding Concept Chorus coding involves running several AI agents on the same codebase simultaneously, where each agent contributes its specific strengths. One agent might focus on architectural planning, another on implementation, and a third on testing. This collaborative loop ensures that agents check each other's work, significantly reducing the risk of isolated errors. ## System Architecture and Service The application operates via a background service called roofd, which keeps agent sessions active even when the primary interface is closed. It supports various CLI tools and plain shells, grouping them by state such as Active, Planned, or Needs Action. This ensures that long-running processes remain persistent across different user sessions. ## Automated Testing Loops One Roof implements automated loops that assign agents specific goals, such as running tests until they pass or executing tasks at 3 AM. These agents work within isolated git worktrees, ensuring the primary repository remains untouched until the user approves the generated changes. Failed runs are clearly flagged for immediate morning review. ## Resource and Performance Monitoring To prevent system instability, the platform includes 10-minute CPU and memory usage charts for every active session. The roofd service automatically monitors resource consumption, warning users when a session exceeds 1 GB of memory. If a process hits the 2 GB threshold, the system terminates it to prevent freezing the host Mac. ## Standardized Context Layers Consistency is maintained through a four-layer context system: shared truth, entry files, private memory, and the session bridge. By using the roof install command, developers can link a shared folder containing standards and runbooks to every agent. This ensures all agents read the same rules, notes, and architectural guidelines during execution. ## Interactive Decision Inbox When an agent requires human input, the request appears in a centralized inbox with a red border for high-priority items. Users can respond directly through the interface, paste screenshots for agent analysis, or interact via the terminal. This design ensures the human developer remains the final decision-maker for all code modifications. ## Benchmarking and Evaluation The platform includes a draft evaluation tool that allows users to compare different models and agents against public benchmarks or their own repository's fixed bugs. It provides clear scoring ranges and explanations for each result. Users can view estimated costs before starting an evaluation, helping them manage subscription usage across multiple vendors. ## Operational Security and Control One Roof prioritizes user control by never approving changes automatically and keeping all settings local. It is built for macOS 14+ on Apple silicon and is distributed as an open-source MIT-licensed project. By providing a structured command-line kit, it allows developers to lock home notes and maintain immutable, secure coding environments. ## Sources covering this story - https://github.com/gaurav8936/oneroof — --- _Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._