How to Use GitHub Copilot

GitHub Copilot Free limits individual developers to 2,000 code completions and 50 chat requests per month [GitHub Copilot plans]. Pro starts at $10 USD per month with unlimited completions and a monthly AI credit allowance [Plans for GitHub Copilot]. That free quota is enough to learn the product, but only if you treat Chat, CLI, and multi-file context as first-class skills instead of stopping after Tab-to-accept.

Using GitHub Copilot means enabling plan access, accepting inline code suggestions, and chatting with Copilot in your IDE or on GitHub to write, explain, and fix code faster. Inline ghost text is the entry point. The durable skill is choosing the right surface for the task: autocomplete for the next function body, Chat for refactors and explanations, and the CLI when you want agent-style work without leaving the terminal.

GitHub positions Copilot as an AI coding assistant that helps you write code with less effort so you can put more energy into problem solving. Official docs cover Free signup, first questions on github.com and in IDEs, inline suggestions, and links into Chat and CLI workflows across editors. This article follows that path, then fills the gap most beginner tutorials leave open: how suggestions degrade without open-file context, how Chat and CLI differ, and where shared project files should live when agent output needs a human review.

Copilot works especially well for Python, JavaScript, TypeScript, Ruby, Go, C#, and C++. Quality varies by language volume in public training data. Treat every suggestion as third-party code you still review, test, and secure.

Helpful references: Fast.io Workspaces, Fast.io Collaboration, and Fast.io AI.

Treat the first hour as a fixed sequence. Skip a step and you will get blank suggestions, auth loops, or a chat panel that never appears.

1. Enable plan access. Sign in to a personal GitHub account and open Copilot Free, or accept Pro, Pro+, Max, Student, teacher, open source, or organization access. You need an active Copilot plan before the editor will serve suggestions.

2. Install and sign in where you write code. In VS Code, hover the Copilot icon in the Status Bar, choose Use AI Features, and complete GitHub sign-in. If you already have a subscription, VS Code uses it. If not, Free signup can complete during the flow. Keep VS Code current. For Visual Studio, JetBrains, Xcode, or Eclipse, install the official Copilot extension or plugin and add your GitHub account in the IDE.

3. Get your first inline suggestion. Create a JavaScript file and type a function header such as:

function calculateDaysBetweenDates(begin, end) {

Gray ghost text should appear with a full function body. Press Tab to accept. The exact suggestion varies. If nothing appears, check that Copilot is enabled for the language, that you are signed in, and that Free monthly completion limits have not been exhausted.

4. Run your first Chat session. In VS Code, open Chat with Control+Command+I on Mac or Ctrl+Alt+I on Windows and Linux, or use the chat icon in the title bar. Ask something concrete: explain the open file, propose tests, or scaffold a small multi-file feature. Review the diff and Keep only what you understand. On github.com, open a file, click the Copilot icon, and ask "Explain this file" or "How can I test this code?"

5. Upgrade your next surface after Tab works. Spend day two on either Copilot Chat multi-file edits, GitHub Copilot CLI in the project directory (copilot for interactive mode), or both. That is where multi-file projects stop being a Tab demo and become a real workflow.

Inline suggestions are the product feature people mean when they say "autocomplete." Copilot reads code around the cursor, other open files, and path or repository signals, then predicts what is likely next. Your job is not to accept everything. Your job is to shape context so the prediction is worth reading.

Open the files that define types, callers, and tests before you start the function you want completed. Close huge unrelated files that pollute context. Write a short, specific comment or function signature before you wait for ghost text. Prefer partial acceptance when only the first few lines match your intent. When the suggestion drifts, delete it and tighten the signature instead of arguing with the model.

Next edit suggestions continue the same idea after you accept a change: Copilot proposes the next related edit elsewhere in the file or project. Navigate and accept those only when the chain still matches the design you approved. If organization policy disables matching public code, suggestions that look like long public snippets may be filtered. That is intentional, not a bug.

Chat is for questions that need a plan, an explanation, or a multi-file edit. Agent mode is for multi-step work where the assistant proposes file changes you review. The CLI is for the same class of work when the terminal is your primary surface.

In VS Code Chat, start with scoped asks: "What does this file do?", "Explain the selected lines", "Add tests for the public API in this module." For larger work, describe the end state and constraints: language, files to touch, and what not to change. Review every generated file before Keep. Organization owners can disable Chat; if the panel refuses to load under a company account, check policy before reinstalling extensions.

GitHub Copilot CLI runs on Linux, macOS, and Windows (PowerShell or WSL). Start an interactive session with copilot from a trusted project directory. Pass a one-shot prompt with -p or --prompt when you want a single task and an exit. Plan mode (cycle with Shift+Tab in interactive mode) makes the CLI draft an implementation plan before writing code, which is safer for multi-step changes. CLI sessions can talk to GitHub.com (list issues, open PRs, summarize commits) when authenticated.

Security is not optional on the CLI. Launch only from directories you trust. Approve tools carefully. Avoid --allow-all-tools on machines with production credentials. Prefer local or cloud sandbox options when you want isolation. Treat MCP servers and custom agents as extra privilege surfaces: configure only what the project needs.

Keep Copilot handoffs in one shared workspace

Store the notes, schemas, and review packs that sit next to your repo so humans and agents pull the same context. Fast.io workspaces include Intelligence Mode, per-file version history, and MCP access, with a 14-day free trial on paid plans.

Start 14-Day Trial

Copilot generates code in the repo and conversation text in the IDE or CLI. The harder problem on multi-file projects is the supporting material: design notes, exported patches, prompt libraries, screenshots, sample payloads, and handoff checklists. Local disks work until a laptop dies. Object storage such as Amazon S3 holds blobs but does not give teammates semantic search over the writeup next to the patch. Consumer drives such as Google Drive or Dropbox share files well for people, yet they are passive buckets for agents.

Fast.io is an option when you want a shared, org-owned workspace that both humans and agents can use. Enable Intelligence Mode so uploaded notes and specs are indexed for semantic search and citation-backed chat. Agents can use the Fast.io MCP server over Streamable HTTP at /mcp (legacy SSE at /sse) with a consolidated MCP toolset. Per-file version history keeps concurrent agent and human edits restorable. Ownership transfer lets an agent scaffold structure and hand the org to a human while keeping admin. Every organization runs on a paid subscription with a 14-day free trial that requires a credit card: Solo at $29/mo, Business at $99/mo, Growth at $299/mo. Creating a user account is free, but real workspace work needs an organization on a paid subscription.

Practical pattern: keep source of truth in Git. Put durable project memory (API contracts, runbooks, acceptance criteria) in a shared workspace humans open in the browser and agents reach through MCP. Use branded Send or Exchange shares when an external reviewer needs a package without full workspace access. Webhooks can notify downstream systems when files change so you are not polling.