GitHub Copilot Overview
This GitHub Copilot review examines how the AI coding assistant holds up in 2026, after GitHub moved chat and agentic features to usage-based AI Credits billing. Copilot has grown well beyond its origins as an autocomplete plugin: it now offers an in-editor chat, an agentic coding mode, automated code review, and a terminal-based CLI, all living inside the editors developers already use.
What is GitHub Copilot?
GitHub Copilot is an AI pair programmer built by GitHub. Trained on large amounts of public code and natural language, it suggests lines, functions, and entire blocks of code as you type, and it can explain, refactor, and debug existing code when asked. Unlike standalone chatbots, Copilot works inside your development environment — VS Code, Visual Studio, JetBrains IDEs, Neovim, and others — so help arrives where the code actually lives.
Over the past year the tool has changed noticeably. Agent mode can now take a plain-language request and carry out multi-step tasks: creating files, running tests, and fixing errors on its own, with you reviewing the result. Copilot Code Review automatically scans pull requests for bugs and style issues, and the Copilot CLI brings the same assistance to the terminal. You can also switch between models from OpenAI, Anthropic, and Google depending on the task, which makes it less of a single-model product than it used to be.
How GitHub Copilot Works
Getting started is straightforward: install the Copilot extension for your editor, sign in with a GitHub account, and choose a plan. Once active, Copilot reads the surrounding code and comments to offer inline suggestions, which you accept with the Tab key or dismiss by typing on. The suggestions improve when your code is well structured and your names are descriptive, since the model leans on context to guess your intent.
For bigger questions, Copilot Chat opens a sidebar where you can ask about an error, request a refactor, or generate tests for a function. Agent mode goes further: describe a goal like adding input validation to a form, and it will plan the edits, touch multiple files, and iterate until the tests pass. This is also where the 2026 pricing change matters. Since June 1, 2026, chat, agents, and code review draw from a pool of AI Credits worth one cent each, with a monthly allowance included in every plan. Inline completions and next-edit suggestions remain unlimited on paid plans, so the core autocomplete experience is unaffected — but heavy agent users need to keep an eye on usage. The free tier offers 2,000 completions and 50 chat messages per month, which is genuinely usable for evaluation.
Who Should Use GitHub Copilot?
Professional developers who spend their days in VS Code or a JetBrains IDE will feel the most benefit. Copilot’s suggestions are strongest for common patterns — boilerplate, API calls, tests, and documentation — and it saves real time on repetitive work. Teams already on GitHub get extra value from the integrated code review and organization-level controls, including the data privacy guarantees that come with the Business and Enterprise plans.
Students and open-source maintainers can get the paid Individual plan free through GitHub’s verification programs, which makes it one of the cheapest ways to add AI assistance to a learning workflow. That said, Copilot is not the right pick for everyone. If you want an AI-first editor rather than a plugin for your existing one, alternatives like Cursor may fit better, and developers who run long, expensive agentic sessions may find the metered credit system harder to budget for than a flat-rate tool.
Our Verdict on GitHub Copilot
In this GitHub Copilot review, the bottom line is straightforward: at $10 a month, Copilot remains the default AI coding assistant for most developers, especially those already invested in the GitHub ecosystem. Autocomplete is fast, reliable, and unlimited on paid plans, and agent mode plus model choice keep it competitive with newer rivals. The AI Credits system is the main caveat — it adds a billing variable that did not exist before, and heavy agent usage can push costs well past the seat price. If your workflow is mostly writing and editing code with occasional agentic help, Copilot is easy to recommend; if you want to automate broader workflows between apps, a platform like Zapier may be the better investment. Browse more options in our AI Developer Tools category.
Key Features
- Inline code completions that suggest lines and functions as you type
- Next-edit suggestions that anticipate your follow-up changes
- Copilot Chat sidebar for explaining, debugging, and refactoring code
- Agent mode that plans and executes multi-step coding tasks across files
- Copilot Code Review that scans pull requests for bugs and style issues
- Copilot CLI bringing AI assistance to the terminal
- Choice of AI models from OpenAI, Anthropic, and Google
- Native extensions for VS Code, Visual Studio, JetBrains, and Neovim
GitHub Copilot Pricing
| Plan | Price |
|---|---|
| Free | $0 (2,000 completions + 50 chats/mo) |
| Pro | $10/mo |
| Pro+ | $39/mo |
| Max | $100/mo |
| Business | $19/user/mo |
| Enterprise | $39/user/mo |
Pricing checked on October 4, 2026 — always confirm on the official site.
GitHub Copilot Pros & Cons
✓ Pros
- Deep integration with VS Code, JetBrains, and other major editors
- Unlimited inline completions and next-edit suggestions on every paid plan
- $10/mo Pro plan undercuts most AI coding competitors
- Choice of models from OpenAI, Anthropic, and Google for different tasks
- Agent mode, CLI, and automated code review cover the full dev workflow
✕ Cons
- AI Credits make heavy agent usage unpredictable to budget
- The June 2026 billing change frustrated some users with cost spikes
- Suggestions can contain subtle bugs, so everything needs human review
- Less compelling outside its supported editors and IDEs