// Videos

Introduces enterprise repository policies in GitHub, a governance feature that lets administrators restrict repository operations—including visibility changes, creations, deletions, transfers, and naming—across all organizations in an enterprise account. The video also demonstrates repository properties defined at the enterprise level, giving organization admins consistent, inherited property values and requiring them at repository creation time to enforce compliance from day one.

Demonstrates GitHub Spark on mobile, building a podcast session timer app entirely through natural language prompts. The video covers iteratively adding timer controls (start, pause, reset), a reverse progress bar, a color-coded time-remaining indicator (green/amber/red), and AI-powered timer creation from a plain-language description—showcasing GitHub Spark's built-in LLM integration. It also demonstrates Spark's managed state storage and the share link for giving collaborators read or write access.

Demonstrates GitHub Spark, an AI-native micro-app platform from GitHub Next that lets anyone build, use, and share personalized apps through natural language—without writing code or managing deployments. The video creates a city travel log app that captures reviews with GPS coordinates, plots destinations on a map, generates AI city suggestions based on existing ratings, and uses the variant generator to explore alternate UI directions from an ambiguous prompt. It also covers the built-in theme editor, state management, and revision history for iterating on app design.

Demonstrates the o1-preview reasoning model integrated into GitHub Copilot Chat in Visual Studio Code, available to approved users via the chat model picker alongside GPT-4o and o1 mini. The video builds a JavaScript maze generator that supports keyboard navigation, BFS and DFS solving algorithms, and visual path rendering—using o1-preview's extended internal reasoning to satisfy complex multi-requirement prompts in fewer iterations than standard models.

Introduces GitHub Models on the GitHub Marketplace, a curated playground for exploring and comparing a range of top AI models using entitlements tied to your GitHub account. The video demos GPT-4o and phi-3 mini instruct side-by-side, shows how to tune system prompts and temperature in the interactive playground, and demonstrates calling model APIs from GitHub Codespaces and the GitHub CLI—all without requiring separate API keys or service sign-ups.

Introduces GitHub's Private Mirrors App, a self-hosted or GitHub-managed tool that helps organizations contribute to open source projects while managing compliance, legal, and security risk. The app creates private mirrors mapped to public forks, enabling teams to run CI/CD checks and policy enforcement before syncing changes back to the public fork for upstream contribution. The video demonstrates forking an upstream project, configuring multiple team mirrors, and integrating with an Enterprise Managed Users organization.

Shows GitHub Copilot Workspace running on the GitHub mobile app, allowing developers to capture ideas and iterate on code from a phone or tablet. The video covers using device dictation for task input, reviewing and editing the AI-generated specification and plan, inspecting code changes via the built-in diff view, running unit tests from the integrated terminal, and creating a pull request with an auto-generated description—all from a mobile device.

Demonstrates GitHub Copilot Workspace starting from a template repository to scaffold a to-do application, showing how AI can jumpstart creativity when starting a new project. The video walks through the full specification-to-plan workflow, iterating with a live app preview, and switching between Copilot Workspace and GitHub Codespaces to make direct code edits. It also covers the share feature for collaborating on work in progress and the automated first deployment via GitHub Actions.

A walkthrough of GitHub Copilot Workspace when starting from a GitHub Issue.

Add checks to pull requests that run automatically during your code reviews. Run the Bicep linter on your code, and deploy the resources to a temporary environment to enable further automated and manual testing.