How to Use GitHub Copilot Chat

GitHub Copilot Chat is available on the GitHub website, in a range of IDEs, on GitHub Mobile, and through GitHub Copilot CLI [About GitHub Copilot Chat]. That multi-surface design is still underserved by VS Code-only tutorials, even though keyword demand for "github copilot chat" is material (about 1,300 monthly US searches, keyword difficulty 33, CPC about $2.39). The practical gap is not "how do I open a chat panel." It is learning which surface to use, which slash commands save tokens, and how teams keep shared context when chat output leaves the local editor.

GitHub Copilot Chat is the AI-powered chat interface for GitHub Copilot. You interact with models in a conversational format to get coding assistance, explanations, and suggestions. Official docs list typical tasks: code suggestions, natural language descriptions of what code does, unit tests, and proposed fixes for bugs [About GitHub Copilot Chat]. You remain responsible for reviewing and validating generated code before it ships.

Inline Tab completion and Chat are related but not the same skill. Completions guess the next lines at the cursor. Chat answers questions, plans multi-file work, and in agent mode can edit files and run tools until a task completes. If you only use ghost text, you leave most of the product on the table.

Helpful product context for the files Chat cannot hold forever: Fast.io Workspaces, Fast.io AI, and storage for agents.

This sequence is the fast path from "I have a plan" to a useful first chat. It works for VS Code and maps cleanly to Visual Studio, JetBrains, Xcode, and Eclipse once the extension is installed and you are signed in with the GitHub account that owns the plan.

1. Confirm access. You need an active GitHub Copilot plan. Org members cannot use Chat if the organization disabled it. Enterprise admins can also hide agent mode.

2. Install and sign in. Use a current IDE build. Install the official GitHub Copilot extension or plugin for your editor, then sign in with GitHub. If authentication fails, fix sign-in before debugging prompts.

3. Open the chat view.

• VS Code: click the chat icon in the title bar (enable Command Center if the icon is missing). Inline chat uses Command+I (Mac) or Ctrl+I (Windows/Linux). Quick chat uses Shift+Option+Command+L (Mac) or Ctrl+Shift+Alt+L (Windows/Linux).
• Visual Studio: View → GitHub Copilot Chat. Inline: right-click and choose Ask Copilot.
• JetBrains: open the GitHub Copilot Chat icon on the right side of the IDE window.
• Xcode: Editor → GitHub Copilot → Open Chat.

4. Pick Ask mode for the first turn. Keep agent mode off until you understand how Keep/Accept works.

5. Give concrete context. Open the file you care about. Select a function if the question is local. Then ask something specific, such as:

Explain what this function does, list two edge cases it misses, and sketch unit tests for them.

6. Review before you apply. Use insert, copy, or Keep only on code you understand. Expand "Used n references" (or References) to see which files shaped the answer. Treat the output like a junior teammate's PR.

7. Follow up in the same thread. "Add tests using Jest" or "Rewrite the error handling without changing the public API" keeps conversation context instead of starting from zero.

Competitor articles often stop after the VS Code panel. Official how-tos cover the same product family on the website, phone, and terminal. That is where review, on-call, and shell work actually happen.

GitHub.com. Navigate to github.com/copilot or open Copilot from repository, issue, and pull request context. Type a question and press Enter. General examples from docs include language comparisons, framework questions, and small scripts. You can stop a streaming answer, ask follow-ups in the same thread, attach images or PDFs when the selected model supports vision, and switch models from the picker when policy allows. On GitHub, Chat can share context with Copilot cloud agent sessions: start an agent task from chat, keep talking while it runs, and later ask about the resulting pull request using agent session logs. Conversation history keeps up to 100 recent conversations, with messages retained for 28 days before permanent deletion.

GitHub Mobile. Tap the Copilot icon (bottom right when shown). Ask general software questions, open a repository and ask architecture questions, or open a file and ask about the whole file or pasted lines. Example repo prompts from docs: "What is the main purpose of this repo?", "Where is rate limiting implemented?", "How is the code organized?" Mobile is ideal for reading a PR on the train and asking for a risk summary before you get to a full IDE.

Windows Terminal Canary. With Copilot connected to Terminal Chat, ask command-line questions such as "how do i list all markdown files in my directory", then click a suggested answer to insert it into the command line. Org policies that disable Copilot CLI also block this path.

IDE family beyond VS Code. Visual Studio 2022 17.8+, JetBrains IDEs (IntelliJ, PyCharm, WebStorm, and many others), Xcode, and Eclipse all host Chat after you install and authenticate. JetBrains and Xcode also expose Plan and Agent modes in current docs. Features such as edit mode, subagents, and MCP integration ship on staggered schedules, so treat the official cheat sheet tab for your IDE as the source of truth when a command is missing.

Keep Copilot Chat plans where the team can find them

Store plan Markdown, prompt libraries, and review notes in a shared Fast.io workspace with version history, Intelligence Mode search, and MCP access for agent handoffs. Start with a 14-day free trial.

Start 14-Day Trial

Once the first chat works, quality comes from structure, not longer prompts.

Choose the mode that matches risk. Ask mode for "what does this do?" Plan mode for "add billing webhooks without breaking existing tests" when you want a reviewable plan first. Agent mode for multi-step work where Copilot may edit files and propose terminal commands. Official docs note that agent-mode prompts consume GitHub AI Credits. If Agent is missing from the dropdown, org or enterprise policy may have disabled it.

Shape context deliberately. Highlight relevant lines. Open related files. In VS Code, use #file, #selection, and @workspace. In Visual Studio, use #MyFile.cs or #solution. In JetBrains, drag files into chat or use Reference File in Chat. Attach screenshots or PDFs when debugging UI or error dialogs on models that support image input. Supported types in docs include JPEG, PNG, GIF, WEBP, PDF, HEIC, and HEIF.

Write durable instructions once. Personal instructions tailor responses for you. Repository instructions live in the repo so every prompt in that project picks them up. Organization owners can add org-level instructions for all owned repositories. That is how teams stop retyping "use our error-handling pattern" on every thread.

Pick models for the job. Different models trade speed, cost (AI credits), and depth. Business users may need org permission to switch models. After a weak answer, regenerate with another model and compare rather than rewriting the entire prompt.

Extend with MCP when Chat needs tools. Model Context Protocol servers connect Chat to external data and actions in supported IDEs. Day one does not require custom MCP. Day five often does, once you want Chat to reach issue trackers, docs stores, or a shared workspace. Configure one server at a time and approve tools carefully.

Chat produces code in the repo and conversation text in the IDE or on github.com. The harder problem for teams is everything around the patch: design notes, exported plans from Plan mode, prompt libraries, sample payloads, screenshots, and review checklists. Those artifacts scatter across laptops, chat logs that expire, and ad hoc Drive folders.

Local disks work until a machine dies or a contractor leaves. Object storage such as Amazon S3 holds blobs but does not give reviewers semantic search over the writeup next to the patch. Consumer drives such as Google Drive or Dropbox share files well for people, yet they stay passive buckets for agent-style workflows. For team handoffs, prefer a shared workspace with version history, permissions, and search.

Fast.io is one option for that layer. Create an org-owned workspace for the project, drop plan Markdown and generated artifacts into folders with granular permissions, and enable Intelligence Mode so the workspace indexes files for hybrid search and citation-backed chat. Agents and humans can use the same workspace through the UI, API, or the Fast.io MCP server (Streamable HTTP at /mcp, legacy SSE at /sse; see mcp.fast.io/skill.md). Per-file version history keeps concurrent edits auditable. Ownership transfer supports the agent-builds-then-human-owns pattern when a bot sets up structure and a person takes the org. Plans start at Starter $29/mo, Business $99/mo, and Growth $299/mo, each with a 14-day free trial that requires a credit card.

Pair that with GitHub-native team controls: repository custom instructions, org custom instructions, and clear policy on whether Chat and agent mode are allowed. Chat answers stay local to each surface; the shared workspace is for the durable outputs you want every teammate to find next week.