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Copilot

Bring the power of generative AI to engineering teams with GitHub Copilot. Learn how you can maximize developer velocity and innovation.

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Security

Stay one step ahead by shipping your software securely within GitHub: Identify and fix security issues directly in the developer flow.

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Why GitHub?

Learn why more than 90% of the Fortune 100 use GitHub—the leading developer platform compared to alternative solutions.

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GitHub Learning Pathways

Become a GitHub expert in CI/CD, application security, governance, and AI-developer tools through expert-guided learning pathways with tips and insights from leading enterprise organizations.

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Announcing the launch of GitHub Well-Architected 🎉

January 6, 2025

A new and ever-evolving resource designed to help organizations effectively adopt and deploy the GitHub platform.

GitHub case study: Enhancing customer support with AI

November 19, 2024

GitHub Copilot empowers engineers to help their organizations achieve better business outcomes for their customers. But AI doesn't simply help engineers do the same work more quickly; it can help them get to places they haven't been able to get to before! We're excited to share how our GitHub customer success team has been using AI to better serve our customers.

Browse by topic

Explore all the GitHub offerings by topic.

Latest videos

Curate blazing fast developer environments and help your organization be more agile, secure, and efficient.Learn more

Advanced Security

Ship secure applications with a community-driven, developer-first approach.

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Page for /well-architected","title":"Announcing the launch of GitHub Well-Architected 🎉","description":"A new and ever-evolving resource designed to help organizations effectively adopt and deploy the GitHub platform.","body":"We are thrilled to announce the initial launch of the [GitHub Well-Architected Framework](https://wellarchitected.github.com).\n\nIt combines design thinking with prescriptive recommendations, empowering leaders and GitHub administrators to achieve their highest priority business goals.\n\nThe site's content is driven by GitHub's customer-facing engineers, our expansive Partner community, and customer contributors, and is organized around the five key pillars of the GitHub Well-Architected Framework:\n\n![Productivity, Collaboration, Application Security, Governance, Architecture](/images.ctfassets.net/wfutmusr1t3h/yGOZCRZIdkRSp0HCRMyt8/2365633676dcdc5932896c3a9f705556/Screenshot_2024-09-18_at_7.30.36_PM.png)\n\n### Why Well-Architected?\n\nOur customers don't go looking to acquire sets of features, they are looking to solve problems. The GitHub Well-Architected Framework is designed with exactly that in mind - focusing on the business goals that a software development platform can and should help you achieve, and providing opinionated guidance on how GitHub can be used to achieve those goals. With any decision comes trade-offs, and the framework is also designed to help you understand those trade-offs and make the best decisions for your unique situation. It has an active contributor community and its content library will continue to expand.\n\n### The Framework at a glance\n\nThe GitHub Well-Architected Framework, or GitHub \"WAF\" for short, is structured in layers:\n\n- __Pillars__: Foundational topics that the framework aims to address. Each pillar is defined by a specific business outcome that is achieved by following the prescriptions of the pillar.\n\n- __Design principles__: Each pillar is supported by design principles that provide the \"how\" to achieve the \"what\" of each pillar, guiding teams toward achieving their goals effectively. For example, if you want to achieve the outcome of \"Productivity\", you should keep topics like Automation, Continuous Improvement, and Feedback at the forefront of your decision-making process.\n\n- __Checklists__: These are the actionable items that can be used to evaluate your implementation of the design principles and the overall pillar. The checklists are a great starting point for a current state assessment.\n\n- __Scenarios and recommendations__: These are articles centered on scenario-based recommendations and tradeoffs. They are designed to help you understand, with technical examples, the implications of the decisions you make and how they impact your organization.\n\nThe site's content is only growing from here. We are committed to continuously improving the framework with content that is driven by our customers' common scenarios and feedback.\n\nWe invite you to explore [wellarchitected.github.com](https://wellarchitected.github.com) and take advantage of the resources available. Whether you're a seasoned architect or just starting out, we hope you'll find the site helpful and inspiring.\n\n### What's next?\n\nIn line with our vision from [last year's GitHub Universe announcement](https://github.blog/news-insights/product-news/copilot-in-github-support-is-now-available/), 60% of the cases presented to it were resolved, with the majority being solved in under 7 minutes. This is equivalent to over 20,000 customers having their problems solved through Generative AI.\n\nBy resolving these queries, the AI assistant has allowed our support team to focus on more complex customer questions, where their expertise can have the most impact. We have seen customer trust and satisfaction in the system grow through increased usage since general availability.\n\n__Future implementations__\n\nGitHub support's AI assistant has been deployed into Copilot chat on GitHub.com. [This capability](https://docs.github.com/en/enterprise-cloud@latest/copilot/using-github-copilot/asking-github-copilot-questions-in-githubcom#currently-available-skills) helps GitHub users access product \u0026 support related information whilst remaining within their workflow.\n\nWe are currently developing further AI capabilities tailored specifically for our internal support team, aiming to further enhance their ability to deliver exceptional customer service. This tool will provide intelligent suggestions, assist with routine task automation, and offer quick access to relevant information, enabling our support staff to manage their workflow more effectively and address complex inquiries with greater ease. We are also planning to expand the knowledge base for the AI-assistant and refine its response capabilities to better handle a wider range of inquiries.\n\n## Insights Gained\n\n__The power of tailored AI experiences__\n\nThroughout the development and deployment of the AI assistant, one significant lesson learned was the importance of tailoring experiences. Our engineers discovered that by optimizing the AI assistant based on customer queries---through tailored responses and context-specific guidance---we could significantly enhance its relevance and effectiveness across a broad range of use cases. For instance, developers and admins often require different types of support, and we've built the system to adapt accordingly. By taking into account the size and complexity of the user, we enable the AI assistant to deliver personalized assistance that addresses the specific needs of each user.\n\n__Expanding innovation beyond productivity__\n\nAnother key takeaway is the potential for AI to drive innovation beyond just enhancing productivity. We encourage engineers to experiment with AI, pushing the boundaries of what's possible. Consider new ways in which AI could be leveraged to achieve novel customer and business outcomes, such as creating more personalized customer experiences. By thinking creatively about the possibilities, engineers can support their organizations to unlock new value and opportunities that go beyond the traditional scope of support automation. This proactive approach to exploring the capabilities of AI not only enhances customer satisfaction but also positions your organization to lead in their respective fields, using AI as a powerful tool for innovation.\n\n## How to enhance your organization with AI\n\nBring a customer-centric approach to engineering with AI:\n\n1. Identify a customer pain point that may benefit from the power of AI.\n\n2. Define the benefits you want to deliver to your customer and any disbenefits you want to avoid and evaluate different AI solutions to address the customer pain point. Ensure you plan for tracking customer feedback and whether the solution is achieving the desired benefits.\n\n3. __Customize and implement your AI solution.__ Based on your evaluation, consider an initial high-level architecture proposal. It can be useful to undertake a proof of concept (POC) to test your proposal for the likelihood of meeting the target benefits. If your POC is promising, move into building for production ensuring ongoing testing as you build and that you meet any of your internal development processes and requirements. Once you have finished development and completed any release activities required by the team/organization, deploy to a small number of customers for initial feedback.\n\n4. __Review and iterate.__ Regularly collect feedback from your customers and internal stakeholders and scale your deployment of the solution as you grow confidence. Use feedback to refine the solution continuously, enhancing its effectiveness and ensuring it continues to deliver value.\n\n## Looking forward to the possibilities ahead for GitHub Support\n\nAs we continue to refine and expand the usage of AI in GitHub Support, we are excited about the broader possibilities it presents for enhancing various aspects of our services. The success of AI in handling level 1 support queries has demonstrated the potential of automation to not only improve responsiveness and customer satisfaction but also to empower our support team to tackle more complex challenges.\n\nLooking ahead, we see significant opportunities to extend the capabilities of AI in the realm of customer success:\n\n- __Product usage guidance.__ AI could be adapted to assist users in navigating and utilizing GitHub's features more effectively. By offering real-time guidance and tips based on user behavior and context, AI could enhance the overall user experience, helping customers unlock the full potential of our platform.\n- __Support data analytics.__ We envision AI playing a crucial role in support data analytics, where it can help identify common issues, trends, and patterns. This data-driven approach can provide valuable insights to both our support and product development teams, leading to proactive improvements in our products and services that directly benefit our customers. We recently published a [blog post](https://github.blog/ai-and-ml/machine-learning/how-github-harnesses-ai-to-transform-customer-feedback-into-action/) on how we harness AI to transform customer feedback into action.\n- __Training and onboarding.__ Beyond supporting the support team, AI can be instrumental in the training and onboarding of new team members across the organization. By providing instant access to a wealth of knowledge, best practices, and contextual guidance, AI can help new employees quickly become productive, accelerating their integration into the team.\n\nIn conclusion, AI gives engineers an unprecedented opportunity to enhance both customer and business outcomes in an organization. GitHub will continue to explore these possibilities and collaborate closely with developers, and customers to ensure that AI continues to evolve and meet the ever-changing needs. If you haven't yet, try GitHub's Support AI-assistant by visiting the GitHub Support Portal and entering your query in the search bar. We value your feedback and would love for you to be part of this exciting journey as we continue to improve how we serve our community.\n\nWant to learn more about the strategic role of AI and other innovations at GitHub? Explore [Executive Insights](https://github.com/solutions/executive-insights) for more leadership perspectives and thought leadership on the future of technology and business.\n\nWill you join the call to use AI to accelerate your organization's success? 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