GitHub Copilot Adds Per-User AI Credits Usage Metrics

High-Frequency AI Prompts for Work, Learning, and Teaching guide

High-Frequency AI Prompts for Work, Learning, and Teaching

Practical AI Side Project Course guide

Practical AI Side Project Course

GitHub Copilot Sessions Can Move to VS Code With Context, Diffs, and Worktree Intact

GitHub has documented a handoff from a Copilot app session to Visual Studio Code. The workflow keeps the session context, changed-file diff, and the same isolated worktree, so a developer does not need to rebuild the task history in a new chat. This article explains the prerequisites and provides a practical review sequence: open the session, inspect the diff, edit locally, run the relevant tests, and decide separately whether to push. The feature is useful when agent work needs human judgment or local tooling, but continuity is not proof that the generated changes are correct. Repository permission, the same GitHub account in both applications, and an existing session with changes are still required.

GitHub Copilot Model Policy API Is Generally Available Across Four Control Levels

GitHub has made GET and PATCH endpoints for Copilot model policies generally available at four levels: enterprise, enterprise team, agent application, and organization. This is an administrative API release, distinct from the earlier global model policy interface. The article gives technical administrators a cautious workflow: read current state, save a baseline, identify the controlling level, review the intended delta, apply one minimal update, and read the result back. No live organization, credential, or production mutation is used in the example. The approach helps teams automate inventory and consistency checks without turning an API into an unreviewed bulk-change mechanism, especially where enterprise policy delegates control to lower levels.

GitHub Introduces HydraFusion Max: When Multi-Model Review Is Worth Trying

GitHub has updated HydraFusion and introduced HydraFusion Max, an orchestration option for demanding coding work. It is not a new standalone model: the system chooses how to draft, review, or revise a response using models allowed for the account. Both options remain research previews, so access and suitability need checking before adoption. This article explains the distinction from automatic single-model selection and proposes a bounded bug-fix comparison that records tests, changes, and usage. It does not rank model quality or promise lower cost. The suggested exercise is designed for people already using an AI coding assistant who want to decide when additional review passes are worth the time and credits.

GitHub Copilot Model Retirement on November 16: A Migration Checklist

GitHub announced on October 15, 2026 that three models will be removed from GitHub Copilot experiences on November 16: Claude Opus 4.8, Claude Opus 5, and GPT-5.6 Terra. The change covers Copilot Chat, inline edits, ask and agent modes, and code completions. GitHub recommends Claude Opus 5.5 for both Claude models and either GPT-6.1 Sol or GPT-6 Luna for GPT-5.6 Terra. Under default model enablement, suggested alternatives are enabled automatically for Copilot Business and Enterprise unless an administrator disabled the global default or the specific model. Claude Opus 4.8 remains available to individual annual subscribers as an exception. This guide provides a durable migration checklist for inventorying model references, checking policies, testing prompts and integrations, comparing quality and cost, communicating the switch, and keeping a rollback path before the deadline.

GitHub Agentic Autofix Is Generally Available, but Humans Still Own the Merge

GitHub made Agentic Autofix for code scanning alerts generally available on October 15, 2026. After an eligible alert on the default branch is assigned to Copilot, the agent explores relevant files, proposes a fix, reruns CodeQL, iterates when needed, and opens a draft pull request for review. Teams can select as many as 25 alerts for one pull request, or assign the Copilot agent through the REST API. The feature is available to GitHub Code Security and GitHub Advanced Security customers on GitHub Enterprise Cloud, requires enterprise policy enablement and a Copilot billing method, and consumes both Code Security AI Credits and GitHub Actions minutes. This article provides a review checklist for scope, test evidence, hidden behavior changes, credit budgets, rollback, ownership, and final human approval before merge.

GitHub AI Scan for Pull Requests Is Generally Available: What It Checks

GitHub made AI Scan for pull requests generally available on October 15, 2026. When code scanning and the repository's effective AI Scan setting are enabled, it automatically reviews pull request changes and complements CodeQL for languages and frameworks that CodeQL does not currently cover, including PHP, Shell or Bash, Terraform HCL, Dockerfiles, Java JSP, and C# Blazor. Findings appear beside CodeQL results with an AI indicator and may include a risk explanation and suggested fix. They remain advisory: they do not fail the code scanning check and cannot block a merge through rulesets. This article explains repository eligibility, excluded fork and Dependabot pull requests, Code Security AI Credit billing, and a human-review workflow for confirming reachability, impact, tests, and residual risk before accepting a suggestion.

GitHub Changelog：AI credits consumed per user now in the Copilot usage metrics API，2026年6月19日

GitHub Docs：REST API endpoints for Copilot usage metrics

GitHub Docs：Requests in GitHub Copilot

GitHub Docs：REST API endpoints for billing usage