Introduction to the GitHub Copilot app

Imagine managing your entire agent-driven development workflow without ever leaving a single desktop window. By providing a unified environment, the GitHub Copilot app lets developers direct AI agents across parallel workstreams, handle GitHub issues, and manage the full pull request lifecycle. Ultimately, this eliminates the constant context-switching between terminals, IDEs, and browser tabs.

The GitHub Copilot app is a desktop application purpose-built for agent-driven development. Built squarely on the GitHub Copilot CLI, this native integration ensures that repositories, branches, and CI pipelines function without additional setup. Whether you code on macOS, Linux, or Windows, the software is officially supported across all three operating systems.

At Microsoft Build 2026, GitHub introduced new tools and updates to help agents work the way developers already work. The necessity for a dedicated control center stems from the rapidly accelerating pace of software creation.

On GitHub alone, commits have nearly doubled year over year, crossing 1.4 billion per month. Alongside this massive growth in code volume, developers are triggering over 2 billion GitHub Actions minutes a week.

By centralizing agent activity, organizations are seeing massive efficiency gains. For instance, Grupo Boticário increased developer productivity by 94% using Copilot.

The app acts as a single "My Work" view, allowing users to see work in motion across connected repositories, active sessions, and background automations. This allows developers to easily transition from prompt to plan, or from issue to pull request, seamlessly.

Key features and workflow capabilities

Parallel workspaces and session modes

Instead of bottlenecking tasks, developers can run multiple isolated agent sessions simultaneously. Because each session operates with a dedicated git worktree and branch, your workstreams stay cleanly separated. When initiating a new agent session, you even have the option to run it in a cloud-based sandbox hosted by GitHub, a feature currently in public preview.

Alternatively, developers can utilize local sandboxing, where Copilot runs in an isolated environment directly on the machine. This restricts access to filesystems and network connectivity for enhanced security.

To suit different development styles, the app offers three primary session modes:

• Interactive: A collaborative mode for tighter steering.
• Plan: Agents create plans that the user must approve.
• Autopilot: A fully autonomous mode.

Depending on your needs, you can select from multiple LLMs, including models from your own providers via a bring your own key (BYOK) approach. Third-party agents like Claude by Anthropic and OpenAI Codex are fully supported to handle execution. You can also adjust the reasoning effort for individual sessions on the fly to match task complexity.

GitHub integration and customizations

Seamlessly tying into your existing workflows, the interface empowers developers to browse issues, start sessions directly from them, and manage pull requests. Everything from reviewing changes and checking CI results to searching across repositories happens directly within the app.

To keep pull requests moving, the Agent Merge feature monitors CI, tracks required reviewers, and addresses failing checks. It then waits for all conditions to be satisfied before successfully merging.

For advanced use cases, the platform supports MCP servers, agent skills, and global instructions. You can connect Copilot to workflows in Jira, Azure Boards, Linear, or Raycast, allowing full planning context to travel with the agent. You can also assign tasks to Copilot directly from Slack or Teams.

Beyond the dedicated app, Copilot is available on a wide variety of platforms, including Visual Studio, Visual Studio Code, Xcode, JetBrains, Neovim, and Eclipse IDE.

Rather than repeating setup steps, you can save recurring agent tasks to run on demand or on a schedule. To further boost collaborative efforts between people and agents, custom interfaces called Canvases are also available. A canvas might display a plan, pull request, browser session, terminal, or deployment dashboard. Agents update the canvas as they work, and developers can edit or approve the output on the same surface.

When exploring alternatives to the GitHub Copilot app, developers often compare feature sets surrounding autonomous agent management and repository integration.

GitHub Copilot app pricing and policies

The desktop application is available across all Copilot plans. For those on Copilot Business and Copilot Enterprise tiers, the specific GitHub Copilot app policy must remain enabled to grant access. Fortunately, this policy is enabled by default and operates entirely separately from the standard Copilot CLI policy.

Pricing spans several tiers to accommodate different usage levels:

• Free: Costs $0 per user/month and requires no credit card. It offers 2,000 completions per month, community support, the Copilot CLI, and access to Haiku 4.5 and GPT-5 mini.
• Pro: Costs $10 per user/month. It provides unlimited code completion, access to Cloud agent and code review, 3rd party agent access, and $15 in monthly total credits.
• Pro+: Costs $39 per user/month, offering 4x more included usage than Pro. It features premium models like Opus, audit logs, and $70 in monthly total credits.
• Max: Costs $100 per user/month. This tier provides 2.9x more usage than Pro+, priority access to new models and features, and $200 in monthly credits.
• Business: Costs $19 per user/month for teams wanting pooled credits, access control, budget control, and IP indemnity.
• Enterprise: Costs $39 per user/month, doubling the included usage of the Business tier and offering priority access to new features.

To protect proprietary code in enterprise environments, the system respects content exclusion policies configured at the enterprise, organization, and repository levels. This ensures excluded files are never used as context.

However, users should note that the tool may still generate code that is a match or near match to publicly available code. This can occur even if the "Suggestions matching public code" policy is set to "Block".

Usage optimization

Start a new session when switching tasks to keep the context focused. This avoids carrying irrelevant history into unrelated work. For early exploration, use Chats to clarify requirements and reduce rework before opening a full session.

User feedback and current limitations

Based on early feedback gathered in May 2026, some developers have already identified friction points in the desktop experience.

• Windows and WSL constraints: One user noted that Windows and WSL support remains rather limited. Another reported being unable to log in on Windows after installation. The application provided an 8-digit code and stated it was opening GitHub.com, but the web browser never opened. Navigating manually to the device login page resulted in a "we couldn't find anything" error.
• Installation warnings: Some users reported that their operating system flagged the application installer as not trusted. They had to manually report it as a safe app list exception.
• Remote connectivity gaps: Another user highlighted that introducing a feature similar to VS Code's remote SSH would be highly beneficial. This specific capability would allow users to open repositories remotely, letting agents run commands on a target machine without requiring local tooling on the host device.
• System requirements: A user attempted to pull the Appimage to a RHEL 8.8 system without success, requesting that the application be built for older systems used in corporate spaces.
• Commit customizations: Developers requested the ability for the "commit" button to use a custom commit message syntax with a given model. This would mirror the functionality that VS Code currently provides.
• Pricing shocks: In a community discussion, users noted that the Copilot Agent became very expensive under the initial pricing update. For a mid-sized project, teams needed around 300 to 500 requests per day per developer. An average issue-handling session cost around 70 premium requests, translating to roughly $320 per developer per month.
• Agent efficiency: One solo founder reported burning through 600+ premium requests for a single task in less than a few hours because the agent required continuous redirecting. Another developer noted that a 35-minute session generated 221 requests in the Copilot app, whereas they achieved the exact same result using the VS Agent with only 6 requests.

Fortunately, GitHub later addressed the runaway billing issue. The system was fixed so it only costs 1 premium request per prompt, multiplied by the chosen model.