What it does best
Context aware code completion across functions and files. Inline chat that understands your repository. Code review suggestions and quick test generation.
Where GitHub Copilot shines
Copilot provides context-aware code completions, inline chat, code review, and agent features across major IDEs and GitHub.com. New Free, Pro, and Pro+ tiers expand access to modern models (including GPT-5/GPT-5 mini) with increasing premium request quotas.
Where it fits in your workflow
Use it when building new features or exploring unfamiliar code. It speeds up boilerplate reduces search time and can suggest idiomatic patterns for your language.
Plans and availability
Free tier with monthly limits. Pro plan at 10 dollars per month. Pro Plus at 39 dollars per month. Business and enterprise options available. No standalone API access outside GitHub and IDE integrations.
AI pair programming inside your editor
GitHub Copilot, powered by OpenAI models, has become the most recognized AI coding assistant in the world. It integrates directly into IDEs such as Visual Studio Code, JetBrains, and Neovim, offering real-time code suggestions as developers type. Beyond autocompletion, it can generate full functions, write boilerplate code, and suggest test cases. Developers often describe it as a junior pair programmer that dramatically reduces repetitive coding. Copilot’s key strength is its deep integration with GitHub, which makes it contextually aware of repositories and widely adopted across engineering teams.
Adoption and who benefits
Copilot is used by software engineers, data scientists, and hobbyist coders alike. Startups rely on it to accelerate prototyping, while large enterprises deploy it to improve productivity across thousands of engineers. Students benefit from its ability to explain code and suggest learning patterns. Its impact is most visible in reducing development cycle time, especially for boilerplate-heavy work in frameworks like React, Django, or Node.js. For teams already working in GitHub, Copilot fits naturally into their workflow with minimal onboarding.
Critical insights and limitations
Copilot is not perfect—it can generate insecure code, hallucinate APIs, or suggest outdated syntax. Security-conscious organizations must review outputs carefully. It also works best with strong prompts and context, meaning weak or ambiguous code comments may lead to suboptimal suggestions. Pricing is another factor for organizations at scale. Despite these issues, Copilot remains the market leader in AI-assisted coding, setting the benchmark for developer productivity and shaping the future of integrated coding assistants.
Prompts
Each block is a copy-ready prompt.
Complete this function based on the docstring. Use idiomatic code style for the given language. Explain the following code to a junior developer. Point out the logic the data structures and any edge cases. Suggest unit tests for this function. Include both happy path and error path examples. Refactor this block of code for readability and maintainability. Suggest variable renames and function extraction where useful. Generate an example snippet that uses this library or API in a realistic scenario.
Show me how to fix common errors in this code snippet. Include the corrected code and a short explanation.
Convert this function from one language to another while keeping equivalent logic.
Generate documentation comments for this class including parameter descriptions and return values.
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Last updated:
Drop a note in your team hub when prompt tweaks perform well, and revisit this tool whenever GitHub Copilot ships new features.