GitHub Copilot: Enhancing Efficiency or Diluting Developer Expertise? 

Author: John Whitehead, VP of Data Services

With the rise of generative AI, IT professionals have increasingly explored potential benefits and drawbacks associated with harnessing these tools. The following article provides a comprehensive overview of GitHub Copilot with careful consideration given to the overarching impact of generative AI on the field of database management. Additionally, gain expert insights from developers on their authentic experiences with Copilot. 

Developed in collaboration with OpenAI, GitHub Copilot is powered by OpenAI Codex, a new AI system created by OpenAI. OpenAI Codex has broad knowledge of how people use code and is significantly more capable than GPT-3 in code generation, in part, because it was trained on a data set that includes a much larger concentration of public source code. GitHub Copilot works with a broad set of frameworks and languages, but this technical preview works especially well for Python, JavaScript, TypeScript, Ruby and Go. 

Why Use GitHub Copilot? 

When harnessed effectively, Copilot is a transformative technology that can be a game changer for businesses. It can serve as a teacher, a gap filler, a problem solver, and much more. Explore opportunities to add Copilot to your software teams’ tool kit and advance your data strategy: 

Boosting Productivity 

• Faster Code Generation: Speed up your coding tasks by letting Copilot generate snippets for you. 
• Code Quality Enhancements: Get optimization suggestions that could uplift your code’s performance. 
• Expand Your Toolbox: Consider Copilot as a companion, much like Visual Studio Code or Postman. Remember; it is not the ultimate solution for every coding challenge. 
• Hear from a developer: “I use it every day. It saves me time switching between IDE and browser to google something, creating test data, and doing repetitive property assignments.” 

“One thing that jumps to mind is I was looking at a specific StackOverflow answer for something I needed to get done, I started typing, and it filled in almost the exact block I was looking at. That was impressive, but then I didn’t know the extension existed until I looked at the SO answer. However, it was slick at adapting it to my current codebase.” 

Learning and Growth 

• Discover New Coding Patterns: Copilot can help to provide a myriad of solutions and broaden your coding horizons. 
• Master New Languages: Dive into new programming territories with Copilot’s snippet suggestions. 
• Hear from a developer: “It has changed my practice by allowing me to learn other ways of thinking. If it suggests a chunk of code, I may or may not like it, but allows me a chance to see other ways of solving the problem (kind of like an always there but don’t need to deal with the awkward silence pair programmer).” 

Top Use Cases 

• Code Completion: Need a function or a snippet? Copilot has your back. 
• Syntax Memory Booster: Forget the constant Google searches for syntax; Copilot reminds you in real-time. 
• Boilerplate Code in a Jiffy: From setting up RESTful APIs to initiating database connections, Copilot can do the heavy lifting. 
• Hear from a developer: “My favorite part of using it is when it detects I’m doing something repetitive it provides some incredibly accurate suggestions. This saves time.” 

Understanding Limitations 

While GitHub Copilot can be a fantastic asset, developers should be wary of potential pitfalls, from over-reliance to security concerns. 

Over-Reliance Dangers 

• Understanding Goes Down: You might lose touch with the underlying mechanics if Copilot does all the work. 
• Atrophying Skills: Relying too much? Your skills might just become rusty. 
• Hear from a developer: “It shut off at one point and I started getting frustrated while coding. I stopped to ask myself why, turns out it was because it wasn’t running, and I was having to think a lot harder on what the syntax was.” 

Contextual Misunderstandings 

• Not Always Right: Copilot can’t always grasp the broader context, leading to off-mark suggestions. 
• Flaw Propagation: If you start with flawed code, Copilot might just amplify those mistakes. 
• Hear from a developer: “…the code it does suggest can look fantastic but have bugs in it, so having that accountability to review/test the code is important.” 

Security and IP Nightmares 

• Sneaky Sensitive Info: Copilot, trained on public code, might unknowingly suggest code revealing sensitive data. 
• Whose Code Is It Anyway? IP concerns could arise, with code suggestions potentially sourced from others’ work. 

Danger Zones 

• Critical Security Code: Avoid relying on Copilot here; the stakes are too high. 
• Proprietary Projects: Tread carefully; you wouldn’t want to expose valuable IP or utilize competitor-derived code. 
• Complex Problems: For niche, intricate issues, trust your expertise more than Copilot. 

Ethical and Collaborative Hiccups 

• AI Bias and Environment Concerns: Every AI has its biases. Plus, the environmental costs of using AI tools can be significant. 
• Consistency Challenges: Different developers might get varying Copilot suggestions, causing codebase inconsistencies. 
• Hear from a developer: “It’s good at filling out repetitive blocks but usually that’s a cue for me to refactor and it doesn’t strictly help me identify that. However, it’ll help me write the similar refactored code quickly and fill in new usages as well.” 

Guiding Principles for Harnessing Copilot 

Remember, whether it’s original, borrowed, or Copilot-assisted, it’s YOUR code. Blaming Copilot won’t cut it. Create a culture of transparency and awareness as you attempt to make your and others professional lives better. Some points to consider immediately (whether you’ve rolled Copilot out already or not): 

Set the Rules 

• Craft a clear Copilot usage guideline for your team that clearly defines the when, how, and why it should be used. 
• Promote a culture of shared learnings and experiences with the tool. 

Uniformity is Key 

• Ensure coding standards remain consistent. 
• Keep abreast of tech trends, adapting standards as required. 

Rigorous Code Reviews 

• Equip reviewers to spot Copilot-induced errors. 
• Promote transparency in Copilot usage during reviews. 

Safety First 

• Reinforce security guidelines for Copilot use. 
• Schedule security audits to address Copilot-related concerns. 
• Explore our blog on data security if your protection strategies could use updates. 

Foster Collaboration 

• Boost developer interaction about their Copilot experiences. 
• Offer multiple platforms for Copilot discussions and clarifications. 

Monitor and Adapt 

• Track Copilot usage metrics to make informed future decisions. 
• Stay updated with training sessions on Copilot’s evolving features.
• Hear from a developer: “My summary would be that it’s 100% better to have it than to not have it, but the limitations need to be understood and worked with” 

Harnessing the full potential of GitHub Copilot requires thoughtful guidelines, consistent coding practices, rigorous reviews, and a culture of collaboration. GitHub Copilot can be a boon for developers, enhancing productivity, facilitating learning, and serving a multitude of coding purposes. Ready to leverage this tool? Talk with our team today.