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Architect: A Terminal Grid Built for AI Multi-Agent Programming Workflows

Architect is a terminal application tailored for AI multi-agent programming workflows. It employs a grid view to manage multiple AI coding assistants simultaneously, offering features like status-aware highlighting, session persistence, and dynamic grid layout. It addresses the context switching and visibility problems that traditional terminals encounter when dealing with multiple Claude Code, Codex, or Gemini instances.

terminalAImulti-agentClaude CodeCodexGeminiworkflowgridmacOSZig
Published 2026-05-29 04:45Recent activity 2026-05-29 04:50Estimated read 6 min
Architect: A Terminal Grid Built for AI Multi-Agent Programming Workflows
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Section 01

Architect: A Terminal Grid for AI Multi-Agent Programming Workflows

Architect is a terminal application designed specifically for AI multi-agent programming workflows, created by forketyfork and hosted on GitHub. It addresses the limitations of traditional terminals in managing multiple AI coding assistants (like Claude Code, Codex, Gemini) by offering a grid view for simultaneous management, status-aware highlighting to prompt user attention, session persistence, and dynamic grid layout. This tool supports macOS and is developed using Zig language, aiming to reduce context switching and improve visibility in multi-agent scenarios.

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Section 02

Background & Pain Points of Traditional Terminals in AI Multi-Agent Scenarios

With the popularity of AI coding assistants, developers often run multiple AI agents in parallel. However, traditional terminals face key issues:

  1. Idle waiting: AI agents may wait for user input but get overlooked, leading to inefficiency.
  2. High context switch cost: Switching between tmux panes or tabs breaks focus and increases cognitive load.
  3. Lack of global visibility: Users can't see all running agents' status at a glance, needing to check each session individually.
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Section 03

Architect's Core Solutions to Terminal Limitations

Architect solves these problems through:

  • Grid View: Displays multiple terminal sessions in a grid, allowing seamless switch between grid and full-screen views.
  • Status-Aware Highlighting: Highlights cells when an AI agent needs attention (e.g., waiting for input, task completion).
  • Session Persistence: Saves session IDs on exit and restores them on next launch, suitable for long-running tasks.
  • Dynamic Grid: Starts with full-screen single terminal; users add cells via ⌘N, and grid adjusts automatically when closing terminals.
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Section 04

Technical Implementation of Architect

Architect is built with:

  • ghostty-vt: High-performance terminal simulation engine for accurate behavior and rendering.
  • SDL3: For cross-platform graphics rendering with smooth animations (grid resizing/rearranging).
  • Zig: A systems language known for performance, memory safety, and compile-time features, ideal for low-level tooling.
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Section 05

Key Features & Installation Guide for Architect

Key Features:

  • Worktree Picker (⌘T): Switch Git worktrees quickly.
  • Recent Folders (⌘O): Access recent directories with search and shortcuts.
  • Diff Review Comments: Add inline comments to code diffs and send to AI agents.
  • Story Viewer: Render PR story files with code diffs.
  • MCP Session: Generate sessions via architect-mcp command.
  • Reader Mode (⌘R): Markdown reader for terminal history.

Installation:

  • Prebuilt binaries for macOS (Apple Silicon/Intel) via curl.
  • Homebrew: Tap the repo and install.
  • Source build: Use nix and just commands.
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Section 06

Configuration & Related Tool Ecosystem

Configuration:

  • Hooks for AI agents: architect hook claude/codex/gemini.
  • Config files: ~/.config/architect/config.toml (user preferences) and persistence.toml (runtime state).

Related Tools:

  • Stepcat: Multi-step agent orchestration.
  • Marx: Parallel PR review with Claude/Codex/Gemini.
  • Claude Nein: macOS menu bar app for Claude Code monitoring.
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Section 07

Practical Significance & Future of Architect

Architect represents the evolution of terminal tools for AI-assisted development. It not only solves current pain points (context switching, visibility) but also integrates with AI workflows via session persistence and code review features. As AI agents become more capable, tools like Architect will play a crucial role in enabling efficient multi-agent collaboration, providing a reference for future AI development environments.