Developers are used to working in an environment where everything is at hand, but even so, they constantly have to get distracted: checking documentation, searching for a solution to an error, or recalling a function signature. AI assistants are gradually closing this gap by handling routine questions and explanations. One of the most notable tools of this kind is a built-in chat assistant for programmers that works right inside the code editor.
Getting to know the assistant
GitHub Copilot Chat is an AI tool designed to boost developer productivity. It integrates into the development environment and provides real-time answers to questions related to the current code. Instead of searching for information elsewhere, a programmer can formulate a query in natural language and receive a hint, an explanation, or a ready-made code snippet without leaving the IDE.
Its core relies on natural language processing and machine learning. The assistant analyzes not only the question itself but also the context: open files, project structure, and recent changes. Thanks to this, its answers are usually tied to the specific situation rather than being abstract reference material. Multiple programming languages are supported, so the tool doesn't force you to commit to just one.
You could say this isn't just autocomplete, but a full-fledged conversational partner that understands what you're working on. It's convenient for discussing architecture, finding the causes of bugs, and making sense of unfamiliar code.
Features that cover everyday tasks
The assistant's main advantage is the breadth of its scenarios. It isn't limited to generating simple functions but helps at various stages of development.
Code explanation and navigation
Often, a new developer — or even the original author after some time — comes across a difficult fragment: a complex algorithm, non-obvious logic, or simply someone else's style. The chat can explain what a selected piece of code does, break it down into steps, and point out potential issues. You can also ask questions about specific files, commits, or pull requests — this is especially useful during code reviews.
Debugging and fixing errors
Instead of manually stepping through code execution or inserting numerous logs, you can describe the symptom to the assistant: "why does an exception occur here?" or "how do I fix this check?" It will suggest likely causes and solutions based on the editor's contents. This also works for finding vulnerabilities: the chat will point out which areas are worth checking for security issues.
Generating unit tests
Writing tests is a useful but often monotonous task. The assistant can create unit tests for a selected function or class, taking its signature and behavior into account. The developer just needs to verify the correctness of the scenarios and add edge cases if necessary.
Quick hints and code completion
In addition to full-fledged dialogue, there are modes for quick questions where you don't need to type a query into a separate line — you can just type it directly while working. The chat also suggests code completions based on what you've already written and can immediately apply the proposed change in the editor.
General programming questions
Beyond project-specific tasks, the tool also works as a regular AI consultant: ask about syntax, best practices, or differences between approaches. This lets you resolve small issues without leaving your workspace or opening a dozen browser tabs.
Integration and ecosystem
GitHub Copilot Chat is built into several popular editors, so it's easy to fit into an existing workflow. The main options are Visual Studio Code, Visual Studio, and JetBrains IDEs. For Enterprise plan users, the chat is available directly on GitHub.com: you can talk to the assistant in the context of repositories, issues, and pull requests. This is convenient when code discussions happen on the platform itself rather than in the editor.
Importantly, the tool doesn't exist in isolation: it's extended through plugins that bring additional domain context from external services. For example, you can connect data from issue-tracking or CI/CD systems so the assistant understands not just the code but also the processes around it.
The interface is also designed for different scenarios:
- Chat View — a full-fledged panel for dialogue that takes the entire workspace into account;
- Inline Chat — the ability to apply the assistant's suggestion directly in the code without switching between windows;
- Quick Chat — a lightweight mode for quick questions and short answers.
This flexibility reduces the need to switch between tools and makes work more continuous. There are fewer reasons to open external documentation and more reasons to simply ask the built-in assistant.
Is it worth enabling
GitHub Copilot Chat is hardly a toy for experiments — it's a work tool that saves noticeable time. If you regularly write code, dig into other people's projects, or need to quickly cover functionality with tests, the assistant will noticeably speed up the process. This is especially evident when working with unfamiliar libraries or maintaining legacy code.
Of course, like any AI system, the chat can make mistakes. The suggested code isn't always perfect, and explanations sometimes suffer from inaccuracies. So recommendations should be verified, especially when it comes to security and complex business logic. But that's more of a reason to treat the tool as an experienced colleague rather than as the ultimate source of truth.
For those already using autocomplete, adding the chat is a natural next step. It covers scenarios where a simple hint isn't enough: for example, when you want a complete solution rather than a single line. Integration with popular IDEs and GitHub makes it a seamless addition to everyday work. If you often "google" while coding, the chat will likely take over a significant portion of those queries, and you'll notice the difference within just a few days of use.
