Comparison: 2026 AI CLI Landscape

The terminal has become the center of AI-assisted development. Every major tool has shipped multi-agent capabilities. Here’s where PTY-for-AI sits in the landscape.

Feature Matrix

	Claude Teams	Codex Plugin	claude-squad	Warp	PTY-for-AI
Multi-agent	✅ tmux/in-process	❌ single call	✅ tmux	✅ panels	✅ headless PTY
Cross-LLM	❌ Claude only	❌ Codex→Claude	✅ any CLI	✅ UI picker	✅ any CLI
Headless	❌ needs terminal	❌	❌ needs tmux	❌ needs Warp	✅ daemon
Daemon	❌ session-scoped	❌	❌	❌	✅ launchd/systemd
Cross-machine	❌	❌	❌	❌	✅ gateway + P2P
Remote upgrade	❌	❌	❌	❌	✅
Sandbox	✅ built-in	✅ Landlock/Seatbelt	❌	❌	✅ plugin
Worktree isolation	✅ built-in	❌	✅ git worktree	❌	✅ plugin
Session persistence	❌ dies with terminal	❌	❌ dies with tmux	❌	✅ survives reboot
Cost routing	model only	❌	❌	model only	✅ LLM-level
Provider failover	❌	❌	❌	❌	✅
Offline / local LLM	❌	❌	✅	❌	✅
Plugin system	✅ rich	✅	❌	❌	✅ SessionPlugin
Declarative config	❌	❌	❌	❌	✅ connector.json
Meeting/mesh topologies	❌	❌	❌	❌	✅ connector.json
Recursive agent trees	❌	❌	❌	❌	✅ agents spawn sub-teams

Architecture Comparison

Layer 4: Plugin      codex-plugin-cc (guest in someone's house)
Layer 3: App         Claude / Codex / Gemini / Aider (each house)
Layer 2: Terminal    Warp / tmux / iTerm2 (neighborhood)
Layer 1: OS          macOS / Linux (the land)

PTY-for-AI:
Layer 1.5: Daemon    Between OS and apps
                     Controls terminals, not lives inside them
                     Controls apps, not lives inside them

No other tool occupies Layer 1.5.

The Scaling Problem

Plugin Approach (N² integrations)

tools: Claude ↔ Codex, Claude ↔ Gemini, Codex ↔ Gemini = 3 plugins
tools: 10 plugins
tools: 45 plugins

Each plugin is a custom integration with its own protocol.

PTY Approach (N integrations)

tools: Claude → PTY, Codex → PTY, Gemini → PTY = 3 connections
tools: 5 connections
tools: 10 connections

One interface. Any CLI that runs in a terminal connects the same way.

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AI-CLIs

Comparison: 2026 AI CLI Landscape

Comparison: 2026 AI CLI Landscape

Feature Matrix

Architecture Comparison

The Scaling Problem

Plugin Approach (N² integrations)

PTY Approach (N integrations)

​Comparison: 2026 AI CLI Landscape

​Feature Matrix

​Architecture Comparison

​The Scaling Problem

​Plugin Approach (N² integrations)

​PTY Approach (N integrations)

Comparison: 2026 AI CLI Landscape

Feature Matrix

Architecture Comparison

The Scaling Problem

Plugin Approach (N² integrations)

PTY Approach (N integrations)