How to Use Microsoft Copilot

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Corrin Jones

POSTED ON

September 24, 2024

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Categories: Artificial Intelligence

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How to Use Microsoft Copilot

There’s debate over what will become of artificial intelligence (AI). Last year, Pew Research studied consumer attitudes toward this sophisticated and rapidly evolving computer science and found more than half of Americans are more concerned than excited by AI. But love it or hate it, AI is here, rapidly finding its place in virtually every industry and impacting jobs significantly.

Software development is a surprising area to watch as the evolution of AI unfolds. Ironically, the applications software developers build can now impact how they do their jobs. According to Wired, tools like Microsoft Copilot are “rewiring coders’ brains.” Microsoft Copilot, an AI-powered code completion tool built on OpenAI’s GPT (Generative Pre-trained Transformer) architecture, is a revolutionary addition to the developer’s toolkit. By leveraging machine learning models trained on vast code repositories, Copilot assists developers in writing code faster and with greater accuracy.

This article delves into the intricacies of Microsoft Copilot, its functionalities, best practices and how developers can seamlessly integrate it into their workflow to enhance productivity and efficiency.

Understanding Microsoft Copilot

Microsoft Copilot is a generative AI code completion tool integrated into various popular development environments, including Visual Studio Code and GitHub’s native code editor. It operates by analyzing the context of the written code and suggesting relevant completions, ranging from entire functions to smaller code snippets. Unlike traditional autocomplete features, Copilot generates suggestions based on the intent of the code rather than mere syntactic patterns.

Thomas Dohmke, the CEO of GitHub, says, “The only question is, how fast do you get on board? Or are you going to be stuck in the past, on the wrong side of the ‘productivity polarity’?” According to Wired, there are more than one million paid Copilot accounts today, and each quarter, there is a 30% uptick in subscribers. Microsoft is developing several AI Copilots that integrate into their ecosystem of software tools. These tools are still under development; the quality of the code remains debatable. However, GitHub research shows:

  • 85% of developers felt more confident in their code quality when using Copilot.
  • 88% of developers reported a better “flow state” of increased productivity when using Copilot AI to write code.
  • Code reviews were completed 15% faster with Copilot.

If you’re wondering how to use Microsoft Copilot, there’s no question it’s a powerful AI tool. What features and functionalities make this software a popular choice for the changing field of software engineering?

Microsoft Copilot Key Features and Functionalities

Microsoft Copilot is a powerful new tool for software developers. Like any other language or framework, coders must determine the best way to use this software to increase efficiency. You can start by understanding some of the critical functionalities the software offers:

  • Contextual code suggestions: Similar to a generative AI like ChatGPT, Copilot can examine the code context, including variable names, function signatures and comments to provide contextually relevant line completions. This feature is a jumpstart for a stuck brain, enabling developers to write code more fluently and reducing the cognitive burden associated with recalling coding syntax and semantics.
  • Code generation: Programming involves a certain level of repetition, which Copilot can alleviate. Based on the context you provide, Copilot can generate entire functions, classes or files. This functionality proves invaluable in accelerating development workflows, especially during the initial stages of project setup or when implementing repetitive patterns.
  • Natural language queries: Copilot uses natural language processing (NLP), the same AI algorithm found in home assistants like Alexa. Developers can interact with Copilot using natural language queries, describing the desired functionality in plain English. The AI model translates these queries into executable code, offering suggestions that align with the specified requirements.
  • Multi-language support: Microsoft Copilot supports multiple programming languages, including but not limited to Python, JavaScript, TypeScript, Java and C++. This broad language support extends its utility across diverse development ecosystems, catering to the needs of a wide range of developers.

ComputerWorld gives an overview of how to use Microsoft Copilot:

For text generation, Copilot uses a large language model (LLM) to do its work. It’s based on the GPT-4 model, developed by a company called OpenAI in which Microsoft is the largest investor. It’s trained on massive amounts of articles, books, web pages and other publicly available text. Based on that training, it can respond to questions, summarize articles and documents, write documents from scratch and much more.

Anyone can access Copilot in Windows 11, in the Edge and Bing browser windows or from their dedicated web page.

How to Best Use Microsoft Copilot Features

Microsoft Copilot isn’t one size fits all. You can customize the output. A recent GitHub blog suggests developers can work this solution into their daily code writing, but “learning to provide as much context is key,” when working with Microsoft Copilot. The solution can infer context from the code itself, but developers can improve the AI’s output by:

  • Opening relevant files in editor mode so the AI can access that data. However, ensure the files are closed when context shifting to the next coding task.
  • Provide the AI with a concise project description to help with context.
  • Add the includes and imports you need for the work; Copilot needs the frameworks, libraries and versions the developer uses to create the best response.
  • Properly name variables and functions with descriptors that signify their intent.
  • Developers can also concisely comment on their code for more targeted responses; again, this gives the AI the context of what you’re trying to do.

Giving the AI some context is also a best practice for non-developers. For example, Copilot is a generative AI tool like ChatGPT. For content creators, accessing the Copilot site allows the same functionality for creating documents. The AI lets you select the tone, length and format of the document in addition to typing. Interestingly, you can even use pictures in a Microsoft Copilot query, unlike ChatGPT, which is strictly text-based. AI imaging edit tools are also built into Copilot to generate eye-catching graphics. While Copilot remains under development, these are valuable tools for front-end web developers.

How to Integrate Microsoft Copilot into the Production Environment

How to Integrate Microsoft Copilot into the Production Environment

The next step in learning to use subscription-based Microsoft Copilot is determining the best methods for integrating it into the development and production process. There are a few ways to do this:

  • Installing Visual Studio Code Extension: For end-users leveraging Visual Studio Code, installing the Copilot extension from the Visual Studio Code Marketplace is the first step. Once installed, the extension seamlessly integrates Copilot into the integrated development environment (IDE), augmenting its capabilities with AI-powered code suggestions.
  • GitHub integration: GitHub users can access Copilot directly within the GitHub native code editor. This integration simplifies leveraging Copilot’s suggestions while collaborating on projects hosted on GitHub repositories.
  • Authentication and permissions: Depending on the environment, users might need to authenticate their accounts and grant necessary permissions to fully enable Copilot’s functionalities. For example, you may need to register the application in Microsoft Azure to gain access to the Microsoft Copilot application project interfaces (APIs), which serve to bridge both tools (Copilot and your application).

Remember, if your organization subscribes to Microsoft 365 programs such as Excel, Outlook, PowerPoint, Teams or Word, Copilot is a wraparound program impacting this entire ecosystem. However, for programmers, there are a few ways to integrate Copilot into your daily workflows slowly. For example:

  • Copilot can extrapolate comments into code. The tool can even do mapping functions.
  • It can also autofill reusable or repetitious code. This auto-paste feature is particularly useful for saving time on tedious tasks.
  • Copilot works with most languages, so programmers can incorporate new frameworks and code bases where appropriate.
  • It can speed testing by suggesting code snippets that will pass the review and test process. However, this doesn’t mean you can skimp on the code review or testing process. Keep in mind that, like all AIs, Copilot can generate incorrect outputs. Its learning library, in large part, is taken from GitHub. Also, given that there are many ways to write a line of code, Copilot may generate a less than elegant output.
  • Can’t remember the correct command? Copilot makes helpful suggestions to help developers remember the commands they’re looking for.

While Copilot offers some exciting developer productivity enhancements, there are a few caveats to consider. What are the drawbacks of how to use Microsoft Copilot in a developer production environment?

Limitations of Using Microsoft Copilot

Overall, while Microsoft Copilot can be a valuable development tool for speeding up coding tasks, it’s essential to weigh these benefits against the potential drawbacks:

  • Dependency on external service: Some developers feel Copilot is a crutch of sorts, leaving them vulnerable to a third-party vendor for doing their job. It’s true that Copilot relies on cloud-based AI models, meaning developers are reliant on Microsoft’s infrastructure and service availability. If there are service interruptions or if Microsoft discontinues the product, developers could face workflow disruptions.
  • Limited customization: Today, Copilot’s suggestions are based on pre-trained models and may not always align perfectly with a developer’s preferences or coding style. While it learns from user feedback, it might not adapt quickly or comprehensively enough to suit every developer’s needs.
  • Potential for overreliance: Depending too heavily on Copilot could hinder a developer’s ability to learn and improve their own coding skills. Relying solely on Copilot for code solutions might lead to a lack of understanding of the underlying principles and concepts behind the code. Without this context, the programmer’s education and abilities are woefully incomplete.
  • Security and privacy concerns: Developers might have concerns about sharing proprietary or sensitive code with a cloud-based service, especially if they work in industries with strict data privacy regulations. There could be risks associated with exposing code to third-party services, including potential leaks or breaches. While Microsoft Copilot offers unprecedented convenience and efficiency, developers must remain vigilant regarding security and privacy considerations such as:
    • Developers should exercise caution when incorporating Copilot-generated code into production environments. The quality of the generated code may vary. Developers still need to review and test the code produced by Copilot to ensure it meets their project’s standards for readability, performance and correctness. Code reviews should focus on sanitizing generated outputs to mitigate the risk of vulnerabilities or even malicious injections.
    • Understand the data privacy implications of utilizing Copilot, particularly regarding the code snippets and context provided to the AI model. Ensure compliance with data protection regulations and adopt best practices for handling sensitive information.
    • Have you heard about the Samsung developers caught pasting their code base into ChatGPT? Cutting and pasting internal or proprietary code into any generative AI is risky. Avoid exposing sensitive or proprietary code snippets to Copilot, especially when operating in shared or public repositories. Implement access controls and encryption mechanisms to safeguard confidential code assets.
  • While Copilot supports a wide range of programming languages and frameworks, it might not offer the same level of assistance for less popular or niche languages. Developers working in specialized domains might not find Copilot as valuable as those working with more mainstream technologies.
  • Copilot generates code based on its training data, which includes open-source repositories from GitHub. Developers must be mindful of licensing and intellectual property issues when using code generated by Copilot, especially if they plan to distribute or monetize their software.

Getting Started with Microsoft Copilot

Microsoft Copilot represents a paradigm shift in code completion and productivity enhancement for software engineers. Red River helps companies incorporate these tools to streamline their organizational productivity. We support several AI tools and algorithms as part of our work to improve technology integration and functionality for our clients. If you’re ready to explore how to use Microsoft Copilot, we can help. Contact us to find out more.

Q&A

How can I try out Microsoft Copilot for free?
As of this writing, Microsoft offers a free trial of their Copilot Pro Product, with subscriptions starting at just $20.00 per user per month.

Is Microsoft Copilot a better tool than ChatGPT?
The answer to this question depends on your usage goals. ChatGPT is a generative AI tool designed to produce written content. While it can create code as part of its outputs, Microsoft designed Copilot to help developers improve their work.