Junk Fee Transparency: Getting Your Website Ready
Learn how the FTC’s new junk fee rule impacts ticketing websites and what steps your organization can take to ensure compliance, transparency, and trust with patrons.
Boosting Development Velocity with AI: How We Use GitHub Copilot to Build Better and Faster
In today's fast-paced technological landscape, the demand for rapid software development is constant. However, speed can never come at the expense of excellence. For us at Adage, creating high-quality, reliable software remains the primary goal. The challenge, then, is to accelerate our development cycles while simultaneously enhancing the quality of our code. This is where artificial intelligence (AI) emerges as a transformative ally. Among the new generation of AI tools, GitHub Copilot stands out, helping our team achieve both speed and precision. Adage has been using GitHub Copilot for the past year and learned how to successfully integrate it into our development workflow.
Understanding GitHub Copilot
GitHub Copilot is an AI-powered code completion tool developed by GitHub and OpenAI. It works as an extension within popular code editors, like VS Code, providing developers with intelligent suggestions for single lines of code or even entire functions in real-time. By learning from billions of lines of public code, Copilot has a deep understanding of numerous programming languages and common coding patterns.
How GitHub Copilot Accelerates Development
The primary benefit of Copilot is its ability to reduce the cognitive load on developers and handle repetitive tasks. This translates into several key advantages:
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Accelerated Coding: By suggesting and autocompleting code, Copilot dramatically reduces manual typing, allowing developers to build features faster.
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Reduced Errors: The AI's context awareness helps in suggesting accurate and less error-prone code, minimizing time spent on debugging common mistakes.
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Allow developers to focus on complex problem-solving: By automating the generation of boilerplate and routine code, Copilot frees up our developers to concentrate on higher-level architectural decisions that lead to a better final product.
The Developer is Always Accountable
It is critical to understand that GitHub Copilot is a powerful assistant, not a replacement for developer expertise and judgment. Just as a writer using an AI to help generate content is ultimately responsible for the final article, the developer is always responsible for the code they submit.
Every line of code suggested by Copilot must be critically reviewed, understood, tested, and owned by the developer. The responsibility for code quality, security, and maintainability does not shift to the AI. The tool augments the developer's skill; it doesn't absolve them of their professional duty to deliver high-quality work.
Our Practical Experience: Strengths and Limitations
With that principle of accountability in mind, our interactions with Copilot have shown us where it truly shines.
We have found that Copilot is highly effective when working with well-established languages and frameworks, particularly JavaScript. The vast amount of public JavaScript code available for its training model means its suggestions are often insightful and accurate. This success has directly influenced our development strategy, reinforcing our adoption of more React-focused development.
Conversely, we have observed that Copilot can be only partially successful when working with complex, niche, or 3rd-party APIs. In these scenarios, the AI's suggestions can be less reliable, reinforcing the need for developer oversight.
One of the most significant considerations for adopting any AI tool is the security of proprietary code. For business and enterprise users, GitHub Copilot does not reuse your code to train its public models. This policy ensures that a company's intellectual property remains secure and confidential and has been a decisive factor in our successful adoption of the tool.
Conclusion: Innovation in Service of Quality
GitHub Copilot represents a significant leap forward in leveraging AI for software development. By understanding its strengths, acknowledging its limitations, and trusting its robust privacy policies, we can strategically apply it where it will have the greatest impact.
However, our journey doesn't stop here. Here at Adage, we are continuously innovating and actively exploring new AI coding tools and paradigms. This commitment is driven by a singular purpose: to make our development process better, faster, and cleaner. Ultimately, these tools are a means to an end, helping our developers fulfill their core mission of delivering high-quality, robust, and reliable software for our clients.
If your team is exploring how AI can accelerate development while keeping quality at the center, let’s start the conversation. Together, we can unlock new ways to build software that drives results and advances your mission.
Fortifying Your Digital Presence: A Collaborative Guide to Web Application Firewalls (WAFs)
A comprehensive guide to Web Application Firewalls (WAFs). Learn how a WAF acts as a digital bouncer, inspecting web traffic and stopping application-layer attacks like SQL Injection and Cross-Site Scripting before they reach your site. Discover why a WAF is a critical component of a robust security strategy, providing protection, ensuring compliance, and handling malicious bot traffic.
Advancing Arts & Culture: What We Learned at TLCC 2025
Discover key takeaways from TLCC 2025, including how Adage is helping arts & culture organizations reimagine patron experiences with Tessitura, AI ticketing, and new web functionality that drives engagement and revenue.