Generative AI (GenAI) has transformed how developers work. But what exactly are they using it for?
To answer this question, we conducted a survey of 6,300 developers and tech leaders and gathered insights into how developers leverage GenAI to streamline workflows, learn new concepts, and automate tedious tasks.
Here’s what we found.
1. Learning New Concepts
GenAI is an invaluable assistant for developers venturing into new technologies or programming languages. Whether understanding complex algorithms or breaking down intricate frameworks, AI can be an interactive learning tool, providing real-time answers and guiding developers through unfamiliar territory.
What Developers Say:
“I use AI to get a start on unknown concepts as a conversational assistant.”
Tip for Developers: Use GenAI platforms like ChatGPT or GitHub Copilot as learning companions. When faced with new challenges, ask the AI to break down complex ideas step by step. For example, AI can simplify explanations if you need help understanding recursion or machine learning models.
2. Debugging
Debugging is a time-consuming task that GenAI helps automate. Developers can input their problematic code, and the AI will point out potential issues and suggest fixes. This significantly reduces the trial-and-error process and helps developers resolve bugs faster.
What Developers Say:
“[GenAI] helps me find answers for niche questions and summarizes documentation, allowing me to get to building faster.”
Tip for Developers: Consider tools like Tabnine that integrate AI into your development environment. These tools can automatically scan your codebase and identify real-time errors or inefficiencies.
3. Code Review
While code reviews are critical to ensuring high-quality, maintainable software, the work can be time consuming. GenAI can automate this process by flagging common coding mistakes, suggesting improvements, and even rewriting code sections for better performance.
What Developers Say:
“I use AI for repetitive tasks where I can see a pattern…for stuff that does not require a personal or human touch.”
Tip for Developers: Use AI tools like CodeGuru or Codacy to automate your code review process. These tools can help spot common errors, enforce best practices, and even improve code quality by suggesting alternative approaches.
4. Documentation
Maintaining up-to-date documentation is essential for team collaboration and code sustainability, but keeping pace with ongoing changes can be challenging. GenAI can automatically generate and update documentation, ensuring developers can access the latest information without sacrificing extra time.
Tip for Developers: Platforms like Scribe AI can automatically generate documentation from recorded workflows or live coding sessions. This tool can save developers time by keeping their project documentation in sync with their code changes.
5. Codebase Understanding
Navigating a large, unfamiliar codebase can be overwhelming, but GenAI can help developers quickly grasp the structure and relationships between various components. This is especially helpful when joining new projects or taking over a codebase developed by another team.
What Developers Say:
“AI helps me find answers for niche questions and summarizes documentation.”
Tip for Developers: Use tools like Sourcegraph to search, understand, and fix bugs more efficiently across large codebases. These tools make exploring the entire code structure and understanding dependencies easier.
6. Implementation
GenAI can be used to suggest optimized code during the implementation phase. It can take an initial problem statement and generate code solutions, allowing developers to focus on refining and adjusting the results to fit their needs.
What Developers Say:
“Mainly I use it to write some blocks of code…I don’t have to waste time writing the usual code again and again.”
Tip for Developers: Try using GitHub Copilot to generate code based on the problem you’re trying to solve. This allows you to implement initial solutions quickly and spend more time refining your approach.
7. Testing
Creating thorough test cases is vital, but manually writing them for every function can be tedious. AI can automatically generate test cases, improving code coverage and helping catch potential bugs before they become significant issues.
Tip for Developers: Tools like Test.ai can automate test generation and even create edge cases that a human developer might overlook. This improves the depth and breadth of testing coverage without extra effort from developers.
8. Refactoring
Refactoring code ensures long-term maintainability and efficiency, but it can be hard to prioritize due to how time consuming it can be. GenAI simplifies this by automatically suggesting refactoring options that clean up code and improve performance without changing its functionality.
What Developers Say:
“Optimizing code to reduce its complexity & increased speed is where AI proves to be most useful.”
Tip for Developers: Use refactoring tools like Refactor.ai that suggest code improvements while maintaining original logic. This can significantly reduce the time spent on manual refactoring and improve code quality.
9. Design & Architecture
While AI can’t entirely replace human creativity, it can assist in designing software architectures by suggesting frameworks, libraries, or technologies that fit the project’s scope. AI’s data-driven approach to recommending best practices can be a helpful guide in the initial stages of system design.
Tip for Developers: Use AI-driven architecture tools like AWS Well-Architected Tool to guide design decisions based on the architecture’s needs. It provides suggestions for frameworks, database setups, and infrastructure options based on your project’s requirements.
10. Deployment
AI can improve the deployment process by automating the setup and verification steps in CI/CD pipelines. It helps ensure configurations are correct and deploys new versions with minimal errors or rollback requirements.
Tip for Developers: Consider integrating AI with tools like CircleCI or GitLab to automate your deployment process. AI can handle environment setup, error checking, and automatic rollbacks.
11. Integration
Integration can often involve compatibility challenges for developers working with multiple systems or APIs. GenAI provides guidance and assistance with integrating disparate components, ensuring that everything works smoothly without conflicts.
Tip for Developers: Utilize AI-based integration platforms like MuleSoft that help developers seamlessly connect applications, reducing the time spent troubleshooting integrations.