💻

GitHub Copilot

AI coding assistant for completions, chat, agents, reviews, and pull requests

Freemium 💻 Code Assistants 🕒 Updated
Facts verified on Active Data as of Sources: docs.github.com, github.com, docs.github.com, docs.github.com, docs.github.com
Visit GitHub Copilot ↗ Official website
Quick Verdict

GitHub Copilot is one of the strongest AI coding platforms for teams already using GitHub and mainstream IDEs. Its 2026 value is no longer just autocomplete; it is chat, review, agent workflows, and repository-aware customization. The main watchout is billing and governance: usage-based pricing and AI-generated code risk require budget controls, tests, and human review.

Best For
Developers and GitHub-based engineering teams
Free Plan
Yes, with monthly request and completion limits
Major 2026 Change
Usage-based billing starts June 1, 2026
Code Review
Available on paid plans and supported surfaces
Agent Workflows
Cloud agent and IDE agent mode available by plan
Human Review Needed
GitHub says Copilot review can miss issues
📡 What's new in 2026
  • 2026-06 Usage-based billing transition
    GitHub says Copilot moves from request-based to usage-based billing on June 1, 2026.
  • 2026-04 Temporary signup pauses
    GitHub docs note temporary pauses for some new Pro, Pro+, student, and Business signups during billing rollout.
  • 2026 Broader agentic workflows
    Copilot now covers cloud agent, IDE agent mode, code review, Spaces, MCP, and customization workflows.

GitHub Copilot is Microsoft GitHub's AI coding assistant for developers and software teams. It provides inline code suggestions, chat, CLI help, code review, pull request summaries, agent mode in IDEs, and cloud-agent workflows that can research repositories and propose code changes. In 2026, Copilot is shifting toward more granular usage-based billing, so teams should evaluate both productivity gains and budget controls before standardizing it across engineering.

About GitHub Copilot

GitHub Copilot is an AI coding assistant embedded across GitHub, VS Code, Visual Studio, JetBrains IDEs, Xcode, Eclipse, GitHub Mobile, GitHub CLI, and related developer workflows. Its value is strongest when it reduces repetitive implementation work: autocomplete suggestions, chat-based debugging, test generation, pull request summaries, code review feedback, and agent workflows that can plan changes and open pull requests for human review. The product has expanded beyond autocomplete.

GitHub documents assistive features such as Copilot Chat, inline suggestions, PR summaries, commit messages, CLI help, and supported IDE workflows. It also documents agentic features including Copilot cloud agent, IDE agent mode, code review, third-party agents, Copilot Spaces, prompt files, custom instructions, MCP support, and memory features. That breadth makes Copilot more of a developer workflow platform than a single coding model.

Pricing and availability require careful reading in 2026. GitHub lists Copilot Free with monthly limits, Pro at $10/month, Pro+ at $39/month, Business at $19/user/month, and Enterprise at $39/user/month, but official docs also state that new sign-ups for some paid individual and organization plans are temporarily paused during billing changes. GitHub docs say Copilot is moving from request-based billing to usage-based billing on June 1, 2026, with token-based pricing tables for model usage.

Teams should not rely on old premium-request-only pricing assumptions. Copilot is best for engineering teams already using GitHub and mainstream IDEs. It is not a replacement for senior review, secure coding processes, or architecture ownership.

GitHub explicitly warns that Copilot code review can miss issues and should be validated carefully. The practical buyer decision is therefore not whether Copilot can write code; it can. The decision is whether your team has repository context, coding standards, tests, budget caps, and review practices strong enough to turn Copilot into measurable throughput instead of unchecked AI churn.

What makes GitHub Copilot different

Three capabilities that set GitHub Copilot apart from its nearest competitors.

  • Copilot is deeply embedded in GitHub pull requests, issues, code review, GitHub CLI, and multiple IDEs.
  • It combines assistive coding features with agentic workflows such as cloud agent and IDE agent mode.
  • GitHub's official docs expose plan, feature, model, and billing details needed for enterprise evaluation.

Is GitHub Copilot right for you?

✅ Best for
  • Developers who want autocomplete, chat, and refactoring help inside their IDE
  • GitHub-based teams that want PR summaries, code review, and issue-to-PR workflows
  • Engineering orgs with tests and review discipline that can safely adopt AI coding agents
❌ Skip it if
  • Teams that need deterministic code with no human review step
  • Organizations unable to manage budget caps or changing usage-based billing
  • Highly restricted environments where cloud AI code processing is not allowed

GitHub Copilot for your role

Which tier and workflow actually fits depends on how you work. Here's the specific recommendation by role.

Solo Developer

Strong fit if you want IDE completions, chat, CLI help, and faster boilerplate.

Top use: Generate tests and refactor repetitive code.
Best tier: Free or Pro
Engineering Team

Strong fit if GitHub PRs and IDEs are central to your workflow.

Top use: PR summaries, code review, and issue-to-PR agent workflows.
Best tier: Business
Enterprise

Useful at scale if governance, budget controls, and code policies are configured first.

Top use: Standardize AI-assisted development across many repositories.
Best tier: Enterprise

✅ Pros

  • Deep integration with GitHub, pull requests, CLI, mobile, and major IDEs
  • Broad feature set covering completions, chat, review, summaries, and agent workflows
  • Useful customization options through repo instructions, Spaces, prompt files, and MCP

❌ Cons

  • Billing is changing in 2026, so cost forecasting is less simple than older plans suggested
  • Generated code and code review feedback still require human validation
  • Advanced features vary by plan, IDE, policy settings, and preview status

GitHub Copilot Pricing Plans

Current tiers and what you get at each price point. Verified against the vendor's pricing page.

Plan Price What you get Best for
Free $0 Limited monthly chat/agent requests and completions; good for trial and light usage. Individual developers evaluating Copilot
Pro $10/month More premium usage and full individual workflow features; new sign-ups temporarily paused per GitHub docs as of this audit. Individual developers
Pro+ $39/month Higher usage allowance and advanced individual features; signup availability may be affected by billing transition. Power users and agent-heavy individual workflows
Business $19/user/month Organization controls, policies, and business features; moving to usage-based billing from June 1, 2026. Software teams and SMB engineering orgs
Enterprise $39/user/month Enterprise controls and GitHub Enterprise integration; moving to usage-based billing from June 1, 2026. Large engineering organizations
💰 ROI snapshot

Scenario: A 10-developer team saves 2 hours per developer per week on boilerplate, tests, and reviews.
GitHub Copilot: $190/month on Copilot Business before usage-based overages or future billing changes. · Manual equivalent: 80 developer hours/month; at $75/hour loaded cost, that is $6,000/month. · You save: Up to $5,810/month if the time saved is real and does not create extra review/rework.

Caveat: Savings depend heavily on test coverage, prompt quality, review discipline, and billing controls.

GitHub Copilot Technical Specs

The numbers that matter — context limits, quotas, and what the tool actually supports.

Supported Surfaces GitHub.com, GitHub Mobile, GitHub CLI, VS Code, Visual Studio, JetBrains, Eclipse, Xcode, Windows Terminal
Core Features Completions, chat, PR summaries, CLI help, code review, cloud agent, IDE agent mode
Billing Change Usage-based model billing begins June 1, 2026 per GitHub docs
Customization Custom instructions, prompt files, Spaces, memory, MCP, and repository context
Code Review Availability Supported on GitHub.com, CLI, Mobile, VS Code, Visual Studio, Xcode, and JetBrains IDEs
API Copilot features are accessed through GitHub and supported clients, not a general consumer generation API

Best Use Cases

  • Speed up boilerplate implementation, tests, refactors, and documentation inside an IDE
  • Review pull requests for missed issues before senior engineers do final review
  • Assign scoped GitHub issues to a coding agent and review the resulting branch or pull request

Integrations

GitHub VS Code Visual Studio JetBrains IDEs Xcode Eclipse GitHub CLI GitHub Mobile Windows Terminal

How to Use GitHub Copilot

  1. 1
    Install Copilot in your coding surface
    Enable Copilot in VS Code, Visual Studio, JetBrains, Xcode, Eclipse, GitHub.com, CLI, or another supported surface. Confirm your plan and organization policy allow the features you need.
  2. 2
    Use chat and completions for implementation
    Ask Copilot to explain files, generate tests, refactor code, or complete repetitive logic while you keep control of architecture and acceptance criteria.
  3. 3
    Add repository context and instructions
    Use custom instructions, prompt files, Spaces, and repository docs so Copilot follows your coding standards, frameworks, and security practices.
  4. 4
    Review output through tests and PR review
    Run tests, inspect diffs, request Copilot code review if available, and keep human review as the final gate before merge.

Sample output from GitHub Copilot

What you actually get — a representative prompt and response.

Prompt
Write a PHPUnit test for a Laravel service that validates expired subscriptions.
Output
Copilot can draft test cases, mocks, and assertions for active, expired, and missing subscription states, which a developer then validates against project conventions.

Ready-to-Use Prompts for GitHub Copilot

Copy these into GitHub Copilot as-is. Each targets a different high-value workflow.

Generate Express CRUD Endpoint
Create a simple REST CRUD endpoint quickly
You are GitHub Copilot acting as a senior backend engineer. Task: generate a single-file Express.js CRUD endpoint (GET, POST, PUT, DELETE) for a resource named "items". Constraints: use TypeScript, ES modules (import/export), async/await, simple in-memory store (no DB), input validation for POST/PUT (id as UUID string, name non-empty). Output format: return a comment with the filename (src/routes/items.ts) then the complete TypeScript code block only. Example route: POST /items accepts { name: string } and returns created item with id.
Expected output: One TypeScript file contents for src/routes/items.ts implementing Express CRUD endpoints with validation.
Pro tip: Ask Copilot to also generate a minimal router unit test file if you plan to plug it into existing test suites.
React Component Test Generator
Create unit tests for React functional components
You are GitHub Copilot acting as a frontend test engineer. Task: generate Jest + React Testing Library unit tests for a functional React component named "UserCard". Constraints: use TypeScript test (.test.tsx), mock props and simulate user events, cover rendering, accessibility role assertions, and one error state. Output format: provide a filename comment (tests/UserCard.test.tsx) then the complete test file code only. Example prop: { id: 'u1', name: 'Alice', onSelect: () => void } and simulate clicking a select button to assert onSelect called.
Expected output: A single TypeScript test file tests/UserCard.test.tsx with several Jest/RTL tests covering render, events, and error state.
Pro tip: If the component imports hooks, include jest.mock stubs to avoid unrelated network calls or side effects.
Node Monorepo CI Workflow
Author CI workflow for Node monorepo builds
You are GitHub Copilot acting as a DevOps engineer. Task: create a GitHub Actions workflow for a Node.js monorepo using Yarn workspaces. Constraints: YAML format, run on push to main and PRs, matrix Node versions [14,16,18], install with cache, run lint, build, and test for changed packages only, and upload cache/artifacts. Output format: provide workflow filename comment (.github/workflows/ci.yml) then the full YAML workflow. Include a short section (3 lines) after the YAML explaining how changed-package detection works and one environment variable to override parallelism.
Expected output: A .github/workflows/ci.yml YAML file implementing matrix builds, caching, changed-package detection, and a 3-line explanation.
Pro tip: Set up caching keys that include yarn.lock/lockfile hash to avoid stale dependency caches across branches.
Refactor Callbacks To Async/Await
Convert callback codebase to async/await safely
You are GitHub Copilot acting as a refactoring engineer. Task: convert a callback-based function named "fetchUserAndPosts" into async/await across its module. Constraints: present a file-by-file plan, include exact code diffs (unified format) for up to three files, preserve behavior and error handling, add TypeScript types where missing. Output format: list changed filenames, then for each file show a unified diff snippet (--- old +++ new lines) with full updated function implementations. Example: original uses callbacks like fetchUser(id, cb) and fetchPosts(userId, cb).
Expected output: A plan plus unified diff snippets for each changed file showing callback-to-async/await conversions with types.
Pro tip: Ask Copilot to run through potential breaking changes: event loop behavior, returned promises, and places where callers must now await the function.
PR Security Review And Fixes
Audit PR diffs for security vulnerabilities and fixes
You are GitHub Copilot acting as a senior application security engineer. Task: analyze a provided PR diff (paste below) and produce a security review with prioritized findings, concrete remediation code snippets, and CI policy updates. Constraints: identify OWASP-relevant issues, insecure dependency changes, sensitive data leaks, and missing auth checks; assign severity (Critical/High/Medium/Low); for each critical/high issue give a one-paragraph exploit scenario and a patch code snippet; propose a GitHub Actions policy that blocks merges until automated checks pass. Output format: JSON with fields: findings[], patches[], ci_policy (YAML string), and summary (3-sentence). Paste PR diff into the prompt when using.
Expected output: A JSON object containing findings array, patch snippets, CI policy YAML string, and a concise summary.
Pro tip: When pasting large diffs, include only the changed files most likely to affect security (auth, input handling, dependency updates) to get focused results quickly.
Property-Based Tests With fast-check
Generate property-based tests for complex functions
You are GitHub Copilot acting as a senior QA engineer. Task: produce property-based tests using fast-check for a pure function named "mergeUserProfiles(a,b)" that merges two user profile objects. Constraints: include generator definitions for profiles (optional fields, nested address, email format), shrinkers or minimal counterexample guidance, three property tests (commutativity where applicable, idempotence with identical profiles, and stability with null fields), and a failing example demonstrating a discovered bug. Output format: provide filenames and full code blocks for generators (tests/generators.ts) and tests (tests/mergeUserProfiles.prop.test.ts), plus one paragraph explaining how to run them and interpret counterexamples.
Expected output: Two test files (generators.ts and mergeUserProfiles.prop.test.ts) containing fast-check generators and three property tests with a failing example.
Pro tip: Seed the failing run with a fixed RNG seed included in the test output so CI can reproduce any flaky counterexample deterministically.

GitHub Copilot vs Alternatives

Bottom line

Choose GitHub Copilot when your team lives in GitHub and wants AI inside commits, PRs, reviews, CLI, and IDE workflows. Consider Cursor for AI-native editor workflows, Amazon Q for AWS-heavy teams, or Tabnine/Codeium when procurement or privacy requirements differ.

Head-to-head comparisons between GitHub Copilot and top alternatives:

Compare
GitHub Copilot vs ChatPDF
Read comparison →

Common Issues & Workarounds

Real pain points users report — and how to work around each.

⚠ Complaint
Copilot generates plausible but incorrect code.
✓ Workaround
Require tests, static analysis, and human review for all AI-assisted changes.
⚠ Complaint
Code review misses edge cases or gives noisy comments.
✓ Workaround
Use Copilot review as a pre-check, not the final reviewer; add repo instructions and coding standards.
⚠ Complaint
Costs become harder to forecast under usage-based billing.
✓ Workaround
Set org-level budget controls, review model usage, and train teams on high-cost workflows.

Frequently Asked Questions

How much does GitHub Copilot cost?+
GitHub Copilot costs $10/month or $100/year for individuals. Copilot Business is $19 per user/month with organization controls and enhanced privacy. Copilot Enterprise is $39 per user/month and adds SSO/SAML, audit logs, and deeper GitHub integration across reviews and PRs. There's no per-token metering; usage is included. Pricing is billed through GitHub, and you can switch between monthly and annual billing to save on long‑term use.
Is there a free version of GitHub Copilot?+
Copilot isn't free for general use, but verified students and eligible open‑source maintainers can access it at no cost. Individuals can also try Copilot with a 30‑day free trial to gauge code quality, latency, and fit with their stack. After the trial, standard individual pricing applies. Organizations typically start on Copilot Business to evaluate policy controls and team management features before wider rollout.
How does GitHub Copilot compare to its top competitor?+
Against Amazon CodeWhisperer, Copilot stands out for GitHub-native features, repo‑aware chat, and excellent VS Code/JetBrains integration. CodeWhisperer shines in AWS-centric workflows and includes a security scan for AWS best practices. Copilot generally feels more contextually aware across diverse codebases and offers stronger PR assistance. If your team lives in GitHub and multi-language IDEs, Copilot fits better; if you're deep in AWS tooling, CodeWhisperer may edge it.
What is GitHub Copilot best used for?+
Copilot excels at accelerating routine coding: generating scaffolds, writing unit tests, drafting SQL, refactoring methods, and explaining unfamiliar code in context. It reduces time spent on boilerplate and helps maintain momentum during feature work, bug fixes, and reviews. It's especially effective in popular languages like JavaScript/TypeScript, Python, Java, and Go, where patterns are well learned. Use it to speed delivery while reserving human judgment for architecture, security, and edge cases.
How do I get started with GitHub Copilot?+
Sign in with your GitHub account, start a 30‑day trial or choose a plan, then install the Copilot extension for VS Code, JetBrains, or Neovim. Enable Copilot Chat, open a familiar repo, and begin with inline comments describing intent. Calibrate settings like suggestion verbosity and duplication detection. For teams, provision seats via GitHub, set organization policies, and pilot on a representative service to benchmark quality, latency, and review impact.
What is GitHub Copilot?+
GitHub Copilot is Microsoft GitHub's AI coding assistant for developers and software teams. It provides inline code suggestions, chat, CLI help, code review, pull request summaries, agent mode in IDEs, and cloud-agent workflows that can research repositories and propose code changes. In 2026, Copilot is shifting toward more granular usage-based billing, so teams should evaluate both productivity gains and budget controls before standardizing it across engineering.
What is GitHub Copilot best for?+
GitHub Copilot is best for Developers who want autocomplete, chat, and refactoring help inside their IDE. Its most important workflow fit is Inline code completions and next-edit suggestions in supported IDEs.
What are the best GitHub Copilot alternatives?+
Common alternatives or tools to compare include Cursor, Codeium, Tabnine, Amazon Q Developer. Choose based on workflow fit, integrations, data controls and total cost.
🔄

See All Alternatives

7 alternatives to GitHub Copilot — with pricing, pros/cons, and "best for" guidance.

Read comparison →

More Code Assistants Tools

Browse all Code Assistants tools →
💻
Tabnine
AI coding assistant for secure code completion and enterprise development
Updated May 13, 2026
💻
Amazon Q Developer
AI coding assistant and cloud development assistant formerly known as CodeWhisperer
Updated May 13, 2026
💻
Windsurf
AI coding assistant and agentic IDE formerly known as Codeium
Updated May 13, 2026