Trained on billions of lines of public code, GitHub Copilot puts the knowledge you need at your fingertips, saving you time and helping you stay focused.
A startup from the United States.
Productivity Boost
GitHub Copilot helps developers write code faster by providing intelligent suggestions and automating repetitive tasks. This can save significant time and reduce the cognitive load on developers.
Learning Tool
For less experienced developers, Copilot can serve as a learning tool by suggesting best practices and introducing them to new coding patterns and techniques.
Support for Multiple Languages
Copilot supports a wide range of programming languages, making it a versatile tool for developers working in different tech stacks.
Context-Aware Suggestions
Copilot offers context-aware suggestions based on the code that has been written so far, making its recommendations relevant to the current development task.
Integration with GitHub
Seamless integration with GitHub simplifies the development workflow, enabling smoother transitions from coding to version control and collaboration.
Promote GitHub Copilot. You can add any of these badges on your website.
It definitely increases my productivity.
Overall, GitHub Copilot is a beneficial tool for many developers, especially those looking to increase their productivity and experiment with new coding styles. It can be seen as an intelligent coding assistant that complements a developer's workflow rather than replaces it.
We have collected here some useful links to help you find out if GitHub Copilot is good.
Check the traffic stats of GitHub Copilot on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of GitHub Copilot on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of GitHub Copilot's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of GitHub Copilot on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about GitHub Copilot on Reddit. This can help you find out how popualr the product is and what people think about it.
Where llms.txt genuinely gets read is a different layer: coding and agent tooling โ Cursor, Claude Code, GitHub Copilot, Windsurf โ pulling a documentation site's pages with less token waste, plus emerging agent protocols like OpenAI's Agents SDK. That's real, and it's growing fast. - Source: dev.to / 26 days ago
You need an active GitHub Copilot subscription. Plans are available at individual, business, and enterprise tiers at github.com/features/copilot. Once active, all tools use your GitHub account credentials. - Source: dev.to / about 2 months ago
For over a decade PhpStorm (starting in my WordPress era) and later WebStorm have been my main IDEs for web development. So when GitHub Copilot launched, it was a natural choice to try it out in WebStorm. It was one of the first AI coding tools I used, and it had a big impact on how I thought about AI-assisted coding. - Source: dev.to / about 2 months ago
Before we get into it, there are some things about AI usage worth addressing. I've had my fair share of scepticism in the past, but recent model releases have made it increasingly difficult to argue that AI isn't a viable tool for the majority of workstreams, including building user interfaces. Most large language models are trained on public data scraped from the internet, which means your internal design system... - Source: dev.to / about 2 months ago
Most developers still treat GitHub Copilot like a very good autocomplete engine. That's useful, but it's not the real unlock. - Source: dev.to / about 2 months ago
Look at how the current generation of AI coding tools is built. IDE-integrated agents like Cursor and GitHub Copilot index the open workspace for context. CLI-based agents like Claude Code and Aider operate within a single repository directory. Code intelligence platforms like Sourcegraph Cody can bridge repositories, but doing so requires explicit multi-repo configuration that most teams skip. - Source: dev.to / 2 months ago
GitHub Copilot is an AI coding assistant integrated into IDEs that suggests code completions, functions, and generates code from comments as you type. Copilot uses OpenAI and GitHub models to offer context-aware recommendations. - Source: dev.to / 2 months ago
I run 53 autonomous AI agents on GitHub Copilot that manage my family's finances, meals, home maintenance, content publishing, and even NICU care coordination for our premature twins. They execute on 57 cron jobs. They make real decisions โ moving money, sending messages, creating PRs, scheduling appointments. - Source: dev.to / 2 months ago
I've been running 71 skills across 50 production agents on GitHub Copilot since before Microsoft made it official. My family's entire life โ finances, meals, content publishing, home maintenance โ runs on this pattern. And the moment Microsoft announced Agent Skills, I knew: this is the architecture that scales. - Source: dev.to / 2 months ago
The most interesting pricing experiments are at the edges. Anthropic offers flat-rate Claude Code subscription tiers, with Max in particular sitting above the per-token consumption model and effectively capping the variable cost. GitHub Copilot has been per-seat from the beginning, with no per-token surcharge for the user. Cursor uses tiered per-seat plans with consumption guardrails. Cognition's Devin charges in... - Source: dev.to / 2 months ago
Most teams measure GitHub Copilot's value the wrong way. They count accepted suggestions, track lines generated, and call it a productivity win. - Source: dev.to / 2 months ago
The skills are agent-agnostic and work with Claude Code, Cursor, Windsurf, GitHub Copilot, and any other agent runtime that follows the agentskills.io spec. - Source: dev.to / 2 months ago
GitHub Copilot reached 20 million users by July 2025. 90% of Fortune 100 companies deployed it. Developers completed coding tasks 55% faster. The tool contributed 46% of all code written by its users (61% for Java). 87% reported reduced mental effort on repetitive tasks. Pull request cycle times dropped from 9.6 days to 2.4 days in enterprise settings. - Source: dev.to / 2 months ago
But what's the definition of success for: - Customer service bots? Ticket resolution time? Customer satisfaction? Cost per interaction? How do you weight them? - Code generation? Lines of code? Bugs per commit? Developer productivity? - Scientific research assistance? Papers published? Hypotheses generated? Reproducibility? - Source: dev.to / 3 months ago
Every time an engineering team wants to connect an AI agent to a data platform, they rebuild the same plumbing from scratch: OAuth2 flows, token management, rate-limiting logic, API versioning, error handling. That's before the agent even does anything useful. Multiply that across a company running GitHub Copilot, Claude, Cursor, and Copilot Studio simultaneously, and the integration surface becomes unmanageable. - Source: dev.to / 3 months ago
If youโd like to explore AI-based reviews, you can try any tool that suits your needs; some include GitHub Copilot, Claude, and Perplexity. For this tutorial, weโll use a popular AI tool like ChatGPT to review and examine common vulnerabilities with a Python Flask application that manages user profiles and handles photo uploads. - Source: dev.to / 3 months ago
Every major AI coding tool today, GitHub Copilot, Cursor, Windsurf, OpenAI's Codex โ operates on the same underlying model: you define the work, the agent does it. You write the prompt, you review the output, you write the next prompt. The developer is still the scheduler, the project manager, and the QA team. The AI is a very fast, very capable executor. - Source: dev.to / 3 months ago
GitHub Copilot handles this kind of pattern-following well when the context is visible. For handlers in languages like TypeScript, including the relevant framework documentation or type imports in the prompt also helps anchor the output to your specific framework's conventions. - Source: dev.to / 3 months ago
GitHub Copilot is the most widely deployed AI coding assistant in professional settings. It integrates directly into VS Code, JetBrains IDEs, and several other editors. The free tier is available for students and open source maintainers; paid plans cover professional use. - Source: dev.to / 3 months ago
With AI tools, convention drift can happen fast. A developer working with GitHub Copilot or Cursor accepts 20 suggestions in an afternoon. Each suggestion is syntactically valid and logically plausible. But several of them use import paths that differ from your project's convention, name variables using a pattern the tool learned from a different codebase, or skip error handling that your team has agreed is... - Source: dev.to / 3 months ago
Affiliate disclosure: No affiliate relationship with GitHub or Microsoft. Links go directly to github.com. - Source: dev.to / 3 months ago
GitHub Copilot, launched by GitHub in collaboration with OpenAI, is rapidly transforming the landscape of AI-assisted coding. This tool, categorized under AI assistants, developer tools, and code autocomplete, harnesses advanced machine learning models like OpenAI Codex and GPT-4 to offer robust functionality for developers worldwide. As an AI-powered coding assistant, Copilot aims to enhance productivity by providing real-time, context-aware code suggestions across a multitude of programming languages, including but not limited to JavaScript, Python, Ruby, and Go.
Integration and Usage:
GitHub Copilot is highly integrated into popular Integrated Development Environments (IDEs) like Visual Studio Code, Visual Studio, Vim, and JetBrains, allowing developers to seamlessly integrate AI assistance into their daily workflows. Copilotโs real-time code suggestions include autocomplete, code explanation, and even complex logic generation, often cited as a key advantage in enhancing developer productivity.
Features and Improvements:
GitHub Copilot's constant evolution is marked by new feature rollouts such as enhanced chat history, drag & drop functionalities, and improved ways to provide context. This evolution is crucial for users seeking seamless integration with existing tech stacks, especially those utilizing open-source platforms or working within educational contexts. Notably, GitHub Copilot Chat is emerging as a significant offering, providing a platform where developers can query code explanations or request code improvements directly within their IDE.
Market Perception and Competitors:
Despite its many strengths, GitHub Copilot faces competition from other AI-powered tools like Tabnine, Kite, Codeium, Cursor, Visual Studio IntelliCode, Amazon CodeWhisperer, and Windsurf Editor. Among these, Cursor is often highlighted as a notable competitor due to its strong feature set that some users have found comparable. However, GitHub Copilot distinguishes itself with its comprehensive capabilities such as pair programming assistance, bug fixes, and the capacity to work with large codebases.
Concerns and Criticism:
Public opinion towards GitHub Copilot is largely positive, with many considering it a game-changer in the realm of AI-assisted development. However, concerns have been raised regarding potential copyright issues, given the tool's reliance on open-source codebases for training its models. These concerns underline the need for careful ethical considerations as AI continues to advance in software development.
Financial Accessibility:
From a pricing perspective, GitHub Copilot is accessible to students and open-source contributors for free, while individual developers can subscribe for $10/month, and business users for $19/month. This pricing model, combined with its feature offerings, makes Copilot a viable option for both new and experienced developers.
Conclusion:
GitHub Copilot remains a leading player in the AI coding assistant market, thanks to its robust functionality and seamless integration into the developer workflow. As AI technology continues to progress, GitHub Copilot is poised to offer even more sophisticated features that promise to streamline coding tasks and significantly improve the software development lifecycle. Nevertheless, as with any AI tool, potential users must remain cognizant of ethical implications and consider the full ecosystem of competing products to ensure the best fit for their specific development needs.
Do you know an article comparing GitHub Copilot to other products?
Suggest a link to a post with product alternatives.
Is GitHub Copilot good? This is an informative page that will help you find out. Moreover, you can review and discuss GitHub Copilot here. The primary details have not been verified within the last quarter, and they might be outdated. If you think we are missing something, please use the means on this page to comment or suggest changes. All reviews and comments are highly encouranged and appreciated as they help everyone in the community to make an informed choice. Please always be kind and objective when evaluating a product and sharing your opinion.
This is the first AI programming tool I've ever used.
Future of Coding
pretty much fastens writing code for me
Some people have been complaining but I've had only good experience with Copilot. I've been using it since its beta, and I can't imagine my day-to-day work without it nowadays. I'm saying this as a happy paying user.