ChatGPT’s ability to translate natural language into working code has sparked tremendous interest in the programming community. Developers are exploring ways to use ChatGPT to reduce redundant tasks, from creating code snippets to analyzing and debugging programs. This also allows them to focus on more complex tasks like data analysis and monitoring with the help of a strong full-stack observability platform. Despite ChatGPT’s impressive capabilities, developers and their employers are split on whether the AI chatbot significantly boosts developer productivity.
We will explore how to use ChatGPT to benefit your developers’ productivity and go over the advantages and disadvantages of ChatGPT to help you make the right decision for your business.
How to use ChatGPT for Better Productivity
ChatGPT has quickly become the most popular intelligence chatbot, with over a million user signups in its first five days and over 100 million in the first two months. Here are a few ways ChatGPT, developed by OpenAI, can help boost productivity in your organization.
Improve Their Code
Sometimes manually written code snippets consume additional CPU resources. Using ChatGPT, developers can optimize their functions for better performance. Additionally, ChatGPT can also write test cases and spot security vulnerabilities in their code, helping developers work faster.
Simplify Documentation
ChatGPT can give a simple explanation for the layman, avoiding technical jargon to a large extent. For instance, a developer at Twitter fed ChatGPT their code and it responded with a pretty detailed explanation. Using ChatGPT to generate the first draft of a company’s internal documentation would make knowledge transfers easier. New hires could quickly get up to speed on the company’s codebase. Further, ChatGPT could also be used for external-facing documents where other developers can learn how to use the company’s APIs and frameworks.
Test and Understand Code
ChatGPT can write automated tests for code that is fed into it. Although many developers consider testing boring and stressful—and sometimes a waste of time—it’s a critical step in ensuring that published applications are bug-free.
With ChatGPT, developers can output reliable, well-tested code much more quickly and easily. ChatGPT can also give high-level and line-by-line explanations of code and even teach developers how to use external modules and APIs in their own code, helping them build much faster.
Debug Code
ChatGPT makes a great debugging tool for developers. It can take in error messages and output information on the likely cause of the error and how to fix it. This is typically a lot more time efficient than browsing forums and blogs for a solution.
The tool can also suggest helpful code alternatives. Many developers claimed that ChatGPT can be much faster and less mentally challenging than the conventional approach of searching the web for a solution.
As the CEO of Replit, Amjad Masad, put it, “ChatGPT could be a good debugging companion; it not only explains the bug but fixes it and explains the fix.”
Code Comprehension
ChatGPT’s terabytes of training data come from various sources, including common crawl and WebText2. This training data makes it easy for ChatGPT to simplify explanations of complex pieces of code for developers. Therefore, developers can save time deciphering any code’s underlying logic and structure.
For instance, Stanford instructor and well-known developer Matt Harrison used ChatGPT to build a simple graphic design tool. He explained, “I’m using ChatGPT to create a GUI program for drawing lines. I haven’t used QT [a development framework] in years, yet I can throw this together really quickly.”
Generate Documentation
Writing code documentation is often considered a mundane task by developers. With ChatGPT, developers can significantly cut down on the amount of time needed for documentation. For instance, they can expedite the creation of troubleshooting guides, tool user manuals and test cases by asking ChatGPT to perform code analysis and generate detailed technical reports. Accelerating this documentation process allows for easier onboarding of new developers and faster product release times.
Writing Tests
ChatGPT can analyze code snippets and automate testing for them, saving developers lots of time and helping them output reliable code. Test coverage is an essential metric for most enterprises, and ChatGPT could help streamline the process.
ChatGPT Disadvantages
While many developers have praised ChatGPT for increasing developer productivity, others have criticized it as unreliable. Let’s understand some key areas where the tool falls behind.
Outputting Buggy or Unusable Code
Developers have complained that the chatbot would sometimes output plausible-looking code that doesn’t work. This might result from misunderstanding the user’s requirements or simply being unable to come up with a correct answer—then faking it.
Programming Q&A forum Stack Overflow even issued a temporary ban on ChatGPT-generated answers. The ban was because the chatbot generated an influx of answers whose average accuracy was pretty low. ChatGPT sometimes uses nonexistent commands and outdated modules in its code, so while they theoretically might make sense, they don’t work in practice.
Writing Outdated Code (and Forgetting Previously Written Code)
Since ChatGPT’s training data cut off in September 2021, the chatbot has no knowledge of the recent developments in programming languages and modules after that. As a result, ChatGPT often needs to use outdated commands, modules and paradigms in its code.
ChatGPT also occasionally forgets the context within which it is working, affecting code output. Some users have reported that ChatGPT sometimes forgets about the task at hand and begins generating incompatible code.
Security Concerns
Security concerns are the biggest drawback to having developers work with ChatGPT. Open AI uses the data users input into ChatGPT to train the underlying AI model.
Research by cybersecurity firm Cyberhaven has shown that 11% of the data employees input into ChatGPT is confidential. This presents a significant risk, as such data can be used in the chatbot’s next responses. Corporations like JPMorgan and Verizon have even gone as far as to block employees’ access to ChatGPT because of these concerns.
Lacks Problem-Solving Skills
A developer’s job is to understand the business problem and develop customized solutions to address it. Although AI/ML tools like ChatGPT help developers code faster, they can’t help in problem-solving or implementing a software application.
Furthermore, when developers become overly reliant on AI-generated code, they’re discouraged from upskilling on new programming frameworks and languages. This can hurt the organization in ways that might not be evident immediately.
To ChatGPT or not to ChatGPT
As Google’s head of developer experience Bret McGowen said, “While AI will transform software development in many ways, human judgment, intuition and creativity will remain essential to building great products.”
While ChatGPT may not be a perfect solution for every aspect of software development, it can be a useful addition when combined with human problem-solving skills. However, companies should be careful while allowing the usage of AI in day-to-day processes. Guidelines educating in-house developers on the fair usage of AI are a must to protect sensitive information and maintain a high-quality control process.