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Github Copilot

Copilot Workshop and Implementation

GitHub Copilot is your active colleague and intelligent coding assistant, equipped with all the knowledge of your company. It helps reduce debugging efforts and improves product quality. In our workshop, we will work with you to explore the possibilities of GitHub Copilot for your organization. We will be glad to present the features of this AI tool that supports developers in their daily work.

What can GitHub Copilot do?

  • provides intelligent code suggestions
  • significantly reduces repetitive tasks
  • automatically refactors code
  • quickly creates test cases
  • uses configuration files to maintain coding standards
  • generates comprehensive documentation

You receive tailored, real-time code recommendations based on your project and coding style. You can describe code in natural language and simple words, and Copilot will translate it into code. At the same time, the AI automatically suggests improvements for structure and readability.

What do you gain as a developer? Copilot in numbers!

Increased productivity:

55% faster task completion
46% of code automated
78% successful task completion

Improved code quality:

Up to 55% fewer bugs

Up to 15% faster code reviews

Greater consistency

Accelerated learning:

Faster onboarding with Copilot code snippets

Satisfaction:

60–75% feel less frustrated
87% report more energy

73% say Copilot helps them stay in flow

The implementation process consists of several stages. We analyze the work environment and technical infrastructure, test Copilot with a small pilot team, provide training, roll out Copilot, monitor processes, conduct feedback sessions, and finally carry out optimizations and documentation.

Implementation based on the 4D model

Analysis and diagnosis

We thoroughly analyze the current work environment, evaluate technical infrastructure, identify potential challenges and risks, and conduct legal analysis (copyrights, AI Act, etc.).

Configuration and customization

For the pilot phase, we form a small team and install Copilot in a test environment to collect initial feedback and experiences.

At the same time, training begins with introductory workshops, customized training materials, and best practices discussions.

Deployment and user training

The entire team gradually gains access to Copilot and provides feedback to adjust processes.

Support and solution development

In the optimization phase, we refine guidelines and best practices to continuously improve Copilot integration into the workflow. At the same time, system components that can be improved or automated are identified.

Workshop for Preparing for GitHub Copilot

In a preparation workshop for GitHub Copilot, we demonstrate the core features and discuss best practices to unlock the full potential of this powerful tool. In the hands-on session, you can watch our developer code in real time and see how GitHub Copilot supports them by, for example:

  • generating and improving unit and integration tests,
  • creating technical documentation with minimal effort,
  • suggesting AI-powered code refactoring.

Sample Agenda

Our clients especially value these live sessions, as they provide a realistic view of working with GitHub Copilot in practice. A possible workshop flow could include:

  1. Welcome and introduction
  2. Legal risks of GitHub Copilot and similar tools
  3. What is Prompt Engineering and how does it work?
  4. GitHub Copilot – functionality and licensing
  5. Live coding session with IntelliJ and VS Code
  6. GitHub Copilot Enterprise features overview, preview, and alternatives
  7. Development performance metrics
  8. Optional demonstration
  9. Q&A and wrap-up
We start by reviewing IDEs and technical setups, then perform a readiness check to verify whether the development environment and operating systems meet the requirements. License management is carried out, along with checking the alignment of AI tool usage with your internal IT and compliance policies.

GitHub Copilot Workshop: Structure and Methodology

The contents of the GitHub Copilot course are tailored to your specific needs. After a short welcome and introduction, we first address the legal risks of such tools to provide confidence in using Copilot and similar assistants. Then we dive right in!

Together, we tackle the question:

In our workshops, interaction is key to getting everyone on board and working toward the same goal. The exchange helps all participants stay engaged throughout the session and be well-prepared for upcoming tasks and challenges.

What is Prompt Engineering and how does it work? In this section, we emphasize the importance of Prompt Engineering and show participants how to effectively build prompts.

We provide practical tips and demonstrate different techniques before moving on to:

  • Functionalities
  • Licenses
  • Workflows

Workshop Highlight

The highlight of the Copilot workshop is the Live Coding Session with IntelliJ and VS Code. We demonstrate code generation, explain functions and methods in detail, and generate complete files.

We also focus on explaining code, debugging (error detection and fixing), code refactoring, test case generation, and documentation (docstrings and comments).

To round off, we provide an overview and preview of GitHub Copilot Enterprise features and alternatives, along with insights into development performance metrics to optimize and better evaluate productivity, quality, and efficiency.

Optionally, you can choose a follow-up demonstration of ChatGPT and Claude in programming, or a practical workshop with chats.

The workshop concludes with a Q&A session, an open discussion, evaluation of a trainee with one year of AI-assistant experience, and a summary.

We assess whether, and in which areas, GitHub Copilot brings value to your company. We identify team requirements and define concrete use cases based on Copilot’s capabilities.

Implementing GitHub Copilot in the Company

The implementation of GitHub Copilot involves a set of preparation and execution measures to ensure that all elements interact smoothly and deliver the desired results. We support you at every stage, ensuring the implementation is a success.

We pay particular attention to the preparation phase, which starts with a GitHub Copilot course and a careful transition using a small pilot group before the full rollout.

Security and Compliance

In this sensitive area, we verify whether the use of GitHub Copilot complies with your company’s internal security and data protection guidelines. We also ensure that sensitive data is not passed on by the AI and that Copilot meets your compliance requirements.

Beyond checking general standards, additional security measures can be applied, such as restricting AI usage to specific areas.

Change Management and Employee Training

The core of change management and employee training should be transparent communication as well as mental and technical preparation for the upcoming changes.

AI will relieve employees from tasks that are often disliked and simultaneously support them in their core activities. As a result, productivity typically increases, along with overall job satisfaction. While AI will not replace a professional developer, it will become an active contributor to the programming process.

Pilot Phase and First Steps

Before the full rollout, a small group will test Copilot under controlled conditions in a secure test environment. This group will gather initial experience and provide regular feedback on the process.

In addition, there will be a training phase with introductory workshops to prepare the team. Training materials will be tailored to the real needs of your organization, and the phase will be accompanied by best practices for using Copilot.

Integration into the Existing Environment

Our task is to seamlessly integrate GitHub Copilot into your existing development processes and tools. We have developed a comprehensive concept that not only takes your individual needs into account but puts them at the center of our efforts.

We achieve this by supporting the configuration of your IDEs, connecting your company’s GitHub repositories, and ensuring that your developers’ workflow remains uninterrupted.

Technologies We Use

For success measurement, we use Key Performance Indicators (KPIs) that track productivity gains, error reduction, development time, developer satisfaction, and more. We gladly support you in selecting the right KPIs to give you a clear overview of the value GitHub Copilot brings to your organization. In the ROI analysis, we compare the benefits of investing in licenses, training, and implementation with the associated costs to determine the actual return on investment.

Best Practices and Use Cases

To ensure effective use of GitHub Copilot, we provide you with proven best practices and tailored solutions for your organization’s specific use cases.

The best practices we share are tried-and-tested methods and tips that enable developers to leverage Copilot purposefully and sustainably.

  • Copilot supports you but does not replace developers – full control over the code remains with humans.
  • It provides suggestions that can be interacted with to generate high-quality code.
  • Using Copilot in a team setting makes sense and is especially effective.
  • AI increases the consistency and speed of the entire development process.

Copilot can also be used for targeted applications, such as performing repetitive tasks like automated test writing. Other scenarios may include supporting developers in using new programming languages, quickly identifying errors (so-called debugging), or rapidly creating prototypes where the developer focuses on logic and functionality while Copilot handles code generation.

FAQ

GitHub Copilot assists developers by providing contextual code suggestions directly within the editor. This saves time on routine tasks such as writing tests, documenting code, or building repetitive structures. It also improves code quality and reduces human error. Teams report up to 50% time savings on standard development activities.

Our workshop follows a modular structure, starting with an overview of GitHub Copilot, its use cases, and limitations. We then analyze your technical environment and move into hands-on exercises such as live coding with Copilot, refactoring, and writing unit tests. The workshop can be delivered on-site or remotely, and the content is fully tailored to your organization’s specific needs.

We don’t offer a generic course – our format is fully customized to your team, codebase, and use cases. We work on real projects from your organization, showing exactly how Copilot can add value. Plus, we support you beyond the workshop with implementation, training, and change management.

Before the workshop, we conduct a technical readiness audit: we review your development environment, tools, and security requirements. We also define clear goals and use cases in advance, ensuring the content is directly relevant to your teams – from software architecture to industry-specific needs.

Yes – using the Enterprise version ensures full legal compliance. Code snippets from your repositories are not reused or shared externally. We also advise on data processing, licensing, intellectual property protection, and help ensure all your internal compliance policies are met.

Absolutely. The workshop is often just the first step. We assist with real-world implementation – including pilot phases, internal training, guidelines, and feedback loops. We also help manage stakeholders to foster team buy-in and avoid common change management pitfalls.

Clients report faster development cycles, more consistent code, and greater developer satisfaction. On average, time-to-feature is reduced by up to 30%. By automating repetitive tasks, developers can focus more on creative and high-value work.

Copilot integrates seamlessly with popular tools like Visual Studio Code, JetBrains IDEs, GitHub Enterprise, GitHub Actions, and various CI/CD environments. Our experts will show you how to connect Copilot to your existing DevOps ecosystem or cloud setup (e.g., Azure, AWS) and incorporate it into your release processes effectively.

Our 4D model includes Discover, Define, Develop, and Deliver. It guides you step-by-step – from identifying needs to full implementation. Together, we define measurable goals, train your teams, and support the rollout and scaling. This model ensures clarity, structure, and long-term integration success.

What kind of team do you need to accelerate work on your projects? Talk to our specialists about your needs.

Jakub Orczyk Member of the Management Board / Sales Director VM.PL
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