How AI is Transforming the Daily Work of Software Developers
By: James Kilungya, Founding Member of Orange Nile
In recent years, artificial intelligence (AI) has had a tremendous impact on how software developers perform their tasks. From writing code to testing and debugging, AI tools help developers work faster and more efficiently. In this blog, we explore how developers use AI daily and the benefits it brings with some concrete insights from our Orange Nile development community.
There are in general four possible day-to-day applications for the use of AI in software development:
- Code Suggestions and Autocompletion One of the most direct ways AI assists developers is through code suggestions and autocompletion. According to a Stack Overflow survey, 76% of developers use AI coding tools, with 81% reporting increased productivity[1]. Suggestions on online platforms like Reddit and MetaStackExchange indicate that the use of tools like ChatGPT by software developers has led to significantly less frequent visits to the GitHub platform.
- Improved Code Quality and Security AI tools like Snyk and DeepCode analyze code to identify bugs and security issues that traditional tools might miss. These tools use machine learning to recognize patterns and suggest improvements, resulting in safer and more reliable software[2].
- Accelerated Learning and Development AI also helps developers learn new skills faster. For example, GitHub Copilot can provide contextual assistance when learning new programming languages or frameworks. This makes it easier for developers to adapt to new technologies and expand their knowledge[3].
- More Efficient Collaboration AI tools enhance team collaboration by automatically generating documentation and code comments, making it easier for team members to understand and contribute to each other’s work. This fosters a more collaborative and productive work environment[4].
AI Usage in Coding by Our Orange Nile software development network
Our colleagues at Orange Nile all use AI in their work. Most often, they utilize AI for improving code quality and security, followed closely by accelerated learning and development. Only a few colleagues use AI for code suggestion and auto-completion.
For example, in the area of accelerated learning, one of our Kenyan colleagues used ChatGPT to draft a questionnaire with 150 questions and answers about the .NET stack to prepare for an interview. Regarding code suggestion, another Kenyan colleague uses AI to copy master data contribution types for a SaaS solution, which saves him a lot of time.
The Future of AI in Software Development
While there are concerns about the possibility of AI replacing programmers, the consensus is that AI is more of an enhancement than a replacement. AI tools take over repetitive tasks, allowing developers to focus on more creative and complex aspects of their work. This leads to a more efficient workflow and higher quality software.
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