The command line has long been the developer’s most trusted tool — minimalistic, powerful, and extensible. Yet, integrating AI assistants directly into terminal workflows has been a challenge, often requiring internet connectivity or switching contexts between coding and chat windows. With Microsoft’s Intelligent Terminal, the command line itself becomes an AI-powered assistant, seamlessly embedded and context-aware.

Version 0.2 of Intelligent Terminal marks a significant leap forward. Most notably, it introduces local model support, enabling AI interactions without relying on the cloud. This keeps your code and data private, reduces latency, and improves reliability. Alongside that, you can now run different AI agents in each terminal tab, providing tailored support for diverse tasks side-by-side. Whether you want GitHub Copilot in one tab and OpenCode in another, your workflow just got a lot more flexible.

In this post, we’ll explore the core new features in Intelligent Terminal 0.2, including the expanded slash command palette, deeper Windows Subsystem for Linux (WSL) integration, and the enhanced Agent Pane. We’ll also examine how local model hosting is configured and why this update fundamentally changes how developers can collaborate with AI in their everyday environments.

Key Technical Observations

• Local Model Hosting via OpenAI API Compatibility
  Intelligent Terminal’s BYOM (Bring Your Own Model) feature allows developers to connect to local servers (e.g., Ollama) that implement the OpenAI API standard. This abstraction makes it easy to integrate any custom or locally hosted model without vendor lock-in.

• Isolated Agents Per Terminal Tab
  The /agent slash command enables assigning a distinct AI agent instance per tab. Each agent maintains its own conversation state and workflow. This design enhances multitasking and task-specific assistance, avoiding intermixing context between different workflows.

• WSL-Aware Agent Execution
  Agents can now run inside Windows Subsystem for Linux distributions. By configuring Intelligent Terminal profiles, agents operate within the same Linux environment where your source code resides, ensuring accurate paths, dependencies, and tools.

• Rich, Interactive Agent Pane UI
  Mouse navigation, Unicode-safe copy, command state animations, and adaptive color schemes improve usability dramatically. The agent's activity bar now indicates token usage and cost, providing transparency into AI consumption.

• Expanded Slash Command Set for Enhanced Control
  From moving the agent pane (/move) to session filtering (/sessions), the intelligent terminal increases user control over their AI assistant environment, making it more flexible and easier to navigate.

• Image Clipboard Integration
  Directly pasting images into the agent pane (Alt+V) enables visual communication channels, such as screenshots or diagrams, enhancing the types of input the assistant can work with—assuming agent image support.

How It Works

Configuring Local Models (BYOM)

To set up a local AI model, open your agent settings and head to the BYOM providers section. Follow these steps:

1. Click Add New provider.
2. Fill in the Base URL endpoint of your local server (for example, a locally running Ollama server).
3. Specify the Model ID recognized by your server.
4. Save your configuration.
5. Select your new provider from the Model dropdown in the Agent Pane.

These steps enable any local or on-prem AI server that communicates over the OpenAI API format to plug into Intelligent Terminal seamlessly. This approach offers a unified interface regardless of whether the model is cloud or local.

Using Multiple Agents with /agent

The /agent slash command lets you assign a dedicated AI agent instance per tab:

/agent Claude

This command instantly switches the current tab’s agent to Claude, isolating its conversation and AI state from other tabs running Copilot or OpenCode. An inline name completer and a picker UI help select allowed agents installed on your machine or enabled by policy.

The core benefit is context separation. Developers can simultaneously engage multiple AI models for different problems—bug fixing, code generation, documentation—without losing state or mixing chat histories.

WSL Integration

To run your agent within a WSL distro, you configure the Intelligent Terminal profile’s settings:

• Choose "Windows-hosted" or "Distro-local WSL" agent type per profile.
• Agents then respect the distro’s environment variables, filesystems, and shell context.
• This avoids mismatches between Windows environment paths and the actual codebase location inside Linux.

{
  "profile": "Ubuntu-20.04",
  "agentExecution": "wsl-local",
  "model": "OpenCode"
}

This integration ensures that agent commands, Autofix suggestions, and diagnostics apply contextually and accurately, reducing environment drift that can plague cross-OS tooling.

Agent Pane Enhancements

The agent pane now supports richer interactivity:

• Scroll with precision, select text by dragging, and use standard keyboard shortcuts like Ctrl+C for Unicode-safe copying.
• Press Up/Down keys to recall up to 50 recent prompts per tab, preserving drafts and multiline input.
• Animated “thinking” states and operation glyphs illuminate running tool calls with visible command paths.
• Adaptive colors match the terminal pane’s background for a consistent look.
• Token usage and cost display at the status bar allow continuous monitoring without leaving the terminal.

Autofix Intelligence

The Autofix feature has been sharpened to detect more failure modes specific to real-world scenarios:

• Errors from Windows PowerShell 5.1 runtime and parser issues.
• Bash prompt cycles and ‘command not found’ situations.
• Environment-awareness to resolve aliases, local scripts, and the current working directory.

Autofix now offers actionable, context-sensitive fixes rather than generic advice, increasing trust and developer efficiency.

Quick Tips & Tricks

1. Add Local Models via BYOM for Privacy & Speed
   Use local OpenAI-compatible servers to keep sensitive data on-device while enjoying AI workflow acceleration.

2. Assign Different Agents Per Tab for Workflow Specialization
   Use /agent to run Copilot in one tab for code completion, OpenCode for refactoring in another, or Claude for documentation—all simultaneously.

3. Leverage WSL Agent Support to Sync Your Dev Environment
   Configure your Intelligent Terminal profile to run agents inside your favorite Linux distros, eliminating environment inconsistencies.

4. Use /move to Adjust Your Agent Pane Layout
   Reposition the agent pane independently per tab without affecting other terminal windows, customizing your workspace ergonomics.

5. Paste Images (Alt+V) for Visual Debugging
   Share screenshots or UI mocks with your agent directly. This is invaluable when text alone cannot describe an issue or design.

6. Keep an Eye on Token Consumption
   Toggle token usage visibility in the agent status bar to monitor cost and optimize AI query efficiency.

Conclusion

Intelligent Terminal 0.2 is a milestone that moves AI assistance in developer workflows from the cloud and one-size-fits-all models toward customizable, private, and environment-aware experiences. Local model hosting combined with per-tab AI agents gives developers new degrees of freedom to tailor AI assistance to their individual tasks and security requirements.

Deep integration into Windows Subsystem for Linux and rich UI improvements solidify Intelligent Terminal as a modern command line reimagined for the AI era. As the team works toward session restore and further enhancements, the Intelligent Terminal promises to evolve into an indispensable, intelligent companion for developers everywhere.

With active community contributions and rapid iteration underway, this is the perfect time to experiment with and influence the future of integrated AI in terminal environments.

References

1. Intelligent Terminal 0.2 is here with local model support | Windows Command Line Blog — Official announcement and detailed release notes by Hamza Usmani