GitHub Copilot

GitHub Copilot for JetBrains 1.18.0 brings AI-assisted tool approvals, more control over agent conversations, and shared skills and instructions for your organization. You can also review plans with the Codex agent and manage MCP tools with persistent controls. What's new AI-assisted tool approvals AI-assisted tool approvals, called assisted approvals, are now in public preview for Copilot agent sessions. Low-risk tool calls receive automatic approval, while higher-risk actions continue to prompt you for a decision. This gives you fewer approval interruptions for low-risk actions while keeping higher-risk decisions in your hands. Re-edit earlier messages You can now re-edit a previous user message in a Copilot agent session. Before sending your replacement message, Copilot rewinds both the conversation and file changes. This lets you revise an earlier request and continue from that point, rather than adding another message to correct the direction of the conversation. Shared skills and instructions

Understand how Copilot agents perform and interact with models and tools. The GitHub Copilot app now supports OpenTelemetry (OTel) configuration through enterprise-managed settings. OTel is an open source observability framework. Administrators can use it to send agent activity data to their organization's compatible monitoring tools. This helps teams:

• Analyze agent sessions: Follow the flow of a session, including requests to AI models and the tools an agent uses.
• Investigate unexpected behavior: Review step-by-step traces of agent execution in their existing monitoring tools.
• Manage monitoring centrally: Apply telemetry settings across teams instead of requiring each developer to individually configure them. Get started Configure the telemetry property in your enterprise's managed-settings.json file to enable export and specify the endpoint that will receive the data. Prompt and response content is excluded by default—review your content-capture settings before enabling it. Learn more about OpenTelemetry for agent monitoring and configuring enterprise-managed settings . copilot Share Copied Shared Related Posts Sep.22 Release

Grok 4.7, xAI's latest reasoning model, is now rolling out in GitHub Copilot. Building on Grok 4.6, it is designed for agentic coding and complex, multistep workflows. This model is billed at provider list pricing under usage-based billing. See Models and pricing for GitHub Copilot for details. Availability in GitHub Copilot Grok 4.7 will be available to Copilot Pro, Pro+, Max, Business, and Enterprise SKUs. You'll be able to select the model in the model picker in:

• Visual Studio Code
• Visual Studio
• Copilot CLI
• GitHub Copilot cloud agent
• GitHub Copilot app
• JetBrains
• Xcode
• Eclipse Rollout will be gradual. Check back soon if you don't see it yet. Enabling access Copilot Enterprise and Copilot Business plan administrators can manage access to Grok 4.7 through the model policy in Copilot settings. Under default model enablement, new models are automatically enabled unless an administrator has turned off the global default or explicitly disables this model. Learn more To explore all models available in GitHub Copilot, see our documentation on models and get started with Copilot. Table of Contents

Availability in GitHub Copilot

Enabling access

Learn more

We will deprecate the following models across all GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions) on October 19th, 2026: Model Deprecation date Suggested alternative Gemini 3.7 Flash 2026-10-19 Gemini 3.8 Flash GPT-5.5 2026-10-19 GPT-5.6 Sol GPT-5.4 2026-10-19 GPT-5.6 Sol GPT-5.4 mini 2026-10-19 GPT-5.6 Luna GPT-5 mini 2026-10-19 GPT-5.6 Luna Grok 4.5 2026-10-19 Grok 4.6 Please update your workflows and integrations to use the supported models before this date. Under default model enablement, the suggested alternatives are automatically enabled for Copilot Enterprise and Copilot Business customers unless an administrator has turned off the global default or explicitly disabled the model. If you've turned off the global default, you can enable access to the alternative models through their model policies in Copilot settings. Once enabled, users will see the model in the Copilot Chat model selector in supported GitHub Copilot experiences. No action is required to remove the models after they have been deprecated.

This week, GitHub Copilot adds new model selection options, code review updates, and Sentry integration in the Copilot app. There are also updates for admins, plus new agent features in VS Code. GitHub Copilot

• Copilot code review now resolves addressed comments during subsequent reviews, leaving outstanding feedback open. It also suggests commit messages when you apply its code suggestions. Reviews can use shell tools to validate changes, and Lite reviews now combine findings from multiple agents.
• Choose how Copilot weighs cost, quality, and response time with the new efficiency, balance, and intelligence tiers in auto model selection. All three tiers select from the same available models. This update is rolling out in VS Code, Copilot CLI, and the Copilot app. GitHub Copilot Business and Enterprise users
• Measure adoption and activity in the dedicated VS Code Agents window with new usage metrics that are now generally available. Enterprise and organization reports include daily active users, session counts, and user message totals, alongside user-level activity data. These metrics are separate from the editor-window metrics.

Copilot code review now gives you a clearer view of how a review changes over time, more intelligently auto-resolves its own suggestions, and generates useful commit messages when you accept eligible suggestions in a batch. These updates help you focus on findings that still need attention and make the resulting commits easier to understand. These updates are now generally available. 🔍 Clearer review progress at a glance The refreshed overview comment shows Copilot's current assessment of your pull request, the review effort level it used, and lists a summary of the findings it identified in its review. Findings are now grouped into:

• Open: Issues that have not been addressed yet. These may have a new label, indicating that they were introduced by a new commit.
• Resolved since last review: Copilot has validated that you've fixed those issues it found earlier. Each finding includes its severity and a link to the corresponding inline comment, so you can quickly move from the overview to the relevant code.

GitHub Copilot expands existing CLI report coverage with agentic activity metrics for skills, custom agents, Model Context Protocol (MCP) servers, slash commands, and plugins. What's new The fields appear in enterprise and organization per-user and aggregate 1-day reports, per-user 28-day reports, and the day_totals entries in aggregate 28-day reports. In a per-user report, the fields answer two questions about that user's activity. In an aggregate report, they answer the same questions across the enterprise or organization:

• Which items are used most? The totals_by_skill , totals_by_custom_agent , totals_by_mcp , totals_by_slash_cmd , and totals_by_plugin arrays list up to five items with the most recorded activity. Each entry includes an interaction_count . Depending on the category, this counts invocations for skills, slash commands, and plugin skills, plus custom agent starts and MCP server connection attempts.
• How many different items were used? The distinct_skill_use_count , distinct_custom_agent_use_count , distinct_mcp_use_count , distinct_slash_cmd_use_count , and distinct_plugin_use_count fields count the number of different items used. In a per-user report, each item

The Copilot impact dashboard now shows how many active users regularly use key Copilot features. Enterprise administrators can quickly see which experiences are widely adopted and which may need more enablement. Enterprise and organization report APIs now include the same 28-day feature engagement breakdown, along with an AI adoption phase reporting improvement that adds each phase's full rolling 28-day population as of each report day. What's new

• Copilot impact dashboard: Shows how many active users engaged with each included feature on at least two days during the 28-day period.
• copilot_feature_engagement : Adds the dashboard's active-user total and feature engagement counts to enterprise and organization 28-day aggregate reports.
• totals_by_feature : Breaks engagement down by code completion, agent edit, passive Copilot code review, active Copilot code review, Copilot cloud agent, Copilot CLI, and Copilot app.
• users_in_phase_28d : Reports the full rolling 28-day population classified into each AI adoption phase as of that day. The existing total_engaged_users field continues to only report users in the phase who were active that day. Why this matters

Previously, when a member used all the Copilot AI credits available to them, they were blocked from Copilot features that consume credits. This release adds a flow for them to request more budget the moment they hit the limit. You can approve, adjust, or deny that request without leaving your settings. Requests automatically route to whichever account pays for the budget. Requests against an organization-owned budget appear in your organization's settings, and requests against an enterprise-owned budget appear in your enterprise's settings. As an organization owner, enterprise owner, or billing manager, you can review pending requests under "Requests from members", set a new amount for each one, and select Approve and increase . Approving a request updates the member's budget to the amount you set and immediately restores their access to AI credits. This feature is available with the GitHub Copilot Business and GitHub Copilot Enterprise plans under usage-based billing. To learn more, see Managing requests for additional Copilot budget and Setting up budgets to control spending on metered products . copilot Share Copied Shared Related Posts Sep.15 Release

GitHub Copilot can now suggest allowed values when you create a custom property for repositories in your organization. This feature is in public preview for GitHub Copilot Business and Copilot Enterprise plans. Custom properties let enterprise and organization admins attach governance metadata to repositories, which you can then use to target repositories with rulesets. Custom properties are one of the most popular ways to scope rulesets, but getting started has been a challenge. Admins often aren't sure which properties to define or what allowed values to use, and inconsistent metadata makes it harder to apply governance consistently across a large fleet of repositories. With this release, when you create a new custom property definition at the enterprise or organization level, Copilot will suggest relevant allowed values based on the property you're defining. For example:

• Creating a multi-select property like FedRAMP surfaces suggested compliance-related values.
• Creating a single-select property like internet-facing surfaces suggested values such as yes and no . You can accept a suggestion in one click, helping you stand up a meaningful custom property taxonomy faster.

GitHub Copilot auto model selection now offers three tiers: efficiency, balance, and intelligence. Choose the tier that reflects how you want auto to weigh cost, quality, and response time for each prompt. Copilot will then optimize accordingly.

• Efficiency prioritizes keeping costs low and suits fast, straightforward tasks.
• Balance weighs cost, quality, and latency together, and is a good fit for everyday work.
• Intelligence prioritizes quality and is built for complex tasks. All three tiers use the same set of available models. Auto individually evaluates each prompt to select a best-suited model. For example, a simple task like adding a docstring to an existing function may use a small, efficient model even when auto is optimizing for intelligence. This feature is currently rolling out in Visual Studio Code, Copilot CLI, and GitHub Copilot app. Usage is charged based on the model auto selects, regardless of tier. Paid subscribers continue to receive a 10% discount on usage billed through auto. This is the first step in our journey toward letting you customize how model selection works for you, with more visibility into the tradeoffs you're making.

Copilot code review now resolves its own comments once you address them and writes smart commit messages for you when you apply its code suggestions. Behind the scenes, Copilot now uses a broader set of shell tools to validate the code it reviews, and an ensemble of agents produce a more thorough review within the Lite effort level. Together, these updates make it easier to focus on the feedback that still matters and give Copilot more ways to check its work. Review experience updates ✅ Automatic resolution of addressed comments When you push a commit that addresses a Copilot code review comment, Copilot now resolves that comment during its rereview. Instead of manually resolving threads that are no longer relevant, you can now rely on the open comments to reflect only the feedback that still needs your attention.

• Comments are automatically resolved when a later commit addresses the underlying feedback.
• Feedback that is still outstanding stays open, so nothing gets lost. Smart commit messages on Copilot autofix suggestions

GitHub Copilot usage metrics reports now include generally available metrics for activity in the dedicated VS Code Agents window, helping you measure adoption and engagement across enterprises and organizations. What's new Aggregate enterprise and organization reports for both 1-day and 28-day periods now include:

• daily_active_vscode_agent_users : An optional count of unique users active in the VS Code Agents window each day.
• totals_by_vscode_agent : Optional aggregate of session_count and total_user_messages values. Enterprise-user and organization-user reports for both 1-day and 28-day periods now include:
• used_vscode_agent : An optional indicator of whether the user used the VS Code Agents window.
• totals_by_vscode_agent : Optional per-user session_count and total_user_messages values. Why this matters These metrics help you understand how many people use the VS Code Agents window and how they engage with it. You can use the aggregate reports to track adoption and activity trends, then use the user-level reports to understand usage across teams. Important notes

This week, GitHub Copilot introduces Jira integration in Copilot app and adaptive model orchestration with Project HydraFusion in Copilot CLI. We also introduced new agent automation in Visual Studio Code and expanded enterprise controls for Copilot in JetBrains. GitHub Copilot app Turn Jira issues into action. Bring Jira issues into a shared canvas, choose what moves forward, and let Copilot carry the context into investigation, implementation, and pull request preparation. Download the Copilot app . GitHub Copilot CLI Project HydraFusion is now in /experimental . HydraFusion delivers automated semantic routing between local, cloud, and compound models. You select HydraFusion like any other model, and it chooses a workflow that balances performance, cost, and latency for each task. To learn more, read the Project HydraFusion blog post . Install Copilot CLI . VS Code 1.137 release updates

• Schedule recurring agent tasks to run hourly, daily, or weekly, or run them on demand with automations, now in public preview.
• Voice mode is now in experimental so you can talk to, interrupt, or redirect Copilot while it works on your code.

We have deprecated MAI-Code-1-Flash across all GitHub Copilot experiences (including Copilot Chat, inline edits, ask and agent modes, and code completions) today, September 10, 2026. Model Deprecation date Suggested alternative MAI-Code-1-Flash 2026-09-10 MAI-Code-1.1-Flash Please update your workflows and integrations to use a supported model. Copilot Enterprise administrators may need to enable access to the alternative model through their model policies in Copilot settings. As an administrator, you can verify availability by checking your individual Copilot settings and confirming that the policy is enabled for the specific model. Once enabled, you'll see the model in the Copilot Chat model selector in VS Code and on github.com. No action is required to remove the deprecated model. GitHub Enterprise customers with questions or concerns are encouraged to reach out to their account manager for further assistance. Share your feedback To learn more about the models available in Copilot, see our documentation on models and get started with Copilot today. Join the GitHub Community Discussion to share your feedback. copilot Share Copied Shared Related Posts Sep.11 Improvement