How ChatGPT is changing the way we think about software development

Over the past few decades, perhaps no field has evolved as radically and dynamically as software development. Relevant technologies and methods are emerging at breakneck speed, and the advent of generative artificial intelligence promises to accelerate this progress even further.

While some believe that generative A.I. products mean the end of professional software development as a human vocation, I firmly believe that nothing could be further from the truth. Developers who incorporate A.I. into their workflows can gain a significant advantage in the talent marketplace. Instead of having a steamy conversation with a programmer or coworker, searching for information on Stack Overflow or Google (which is not very efficient 80-90% of the time), a developer can communicate with their A.I. Assistant. By doing so, developers will become 10-100 times more productive than they are today.

Developers who do so will see immediate and long-term benefits across the board - not only in increased productivity, but also in responding to real-time feedback, improved accuracy, and better code overall.

Real-time review and feedback

One of the main ways that software developers can benefit from incorporating technologies like ChatGPT into their work is by using A.I. to develop comprehensive code review processes. By using ChatGPT for code review, developers can get automated feedback on quality and style. Coders can enter code into the ChatGPT interface and, by asking the right questions, receive almost instant analysis of potential problems, suggestions for improvement, and explanations of all recommendations.

Developers can also use ChatGPT to view offline documentation, including API references, user guides, and technical specifications. As with code, they can put the documentation into the A.I. interface for review, and ChatGPT can answer questions about language clarity, completeness, and organization. This helps ensure that all documentation is complete and complies with code base standards.

ChatGPT is a great resource for bug tracking as well. By analyzing bug reports, ChatGPT can help developers sort and prioritize issues, identify potential duplicates, and assign them appropriate labels or categories. It can even suggest solutions or workarounds based on historical data and existing knowledge.

Auditing codebases is a time-consuming and sometimes boring process, but very important. Developers can free up this time for other activities by submitting parts of the codebase to ChatGPT. The artificial intelligence can then analyze the code for performance bottlenecks, security vulnerabilities, and adherence to coding standards. With ChatGPT, the coder can quickly identify specific areas for improvement, as well as overall compliance with industry standards and organizational best practices.

Finally, ChatGPT can help organize and run project review meetings by acting as a virtual facilitator, collecting and documenting feedback from participating developers, and aggregating and summarizing it in reports.

These reports generated by ChatGPT contain two main findings: First, they identify common themes emerging from developer feedback. This helps identify areas of concern or need for improvement that apply to the development team as a whole. Second, they suggest specific actions: e.g., individual challenges, process improvements, areas for better alignment, and new opportunities for collaboration.

CI/CD implementation

One of the broadest uses of ChatGPT in software development is to improve what is known as the Continuous Integration/Continuous Delivery (CI/CD) pipeline. This is a complex and time-consuming process, but ChatGPT can help.

In the continuous integration (CI) phase, developers make regular code changes to a shared code repository, automate build processes to compile new code, run unit tests, and perform static code analysis. In the continuous delivery (CD) phase, developers prepare code for deployment, which includes tasks such as packaging the application, configuring the infrastructure, and preparing deployment artifacts.

Developers can integrate ChatGPT into their existing CI/CD pipeline as an embedded step or by connecting it to the system's APIs. Developers can then quickly perform many tasks that used to be time-consuming. For example, ChatGPT can analyze code changes, perform static analysis, and provide feedback on overall code quality, security vulnerabilities, or performance issues.

Similarly, when a developer submits a rework request, ChatGPT can automatically analyze code changes, check coding standards, and provide suggestions for improvement. This is very important for identifying problems early in the development process.

ChatGPT can also help identify bugs, suggest troubleshooting steps, and provide the necessary documentation to help third parties understand and resolve code issues quickly. Developers can use ChatGPT to improve endpoint efficiency, including generating deployment configurations, validating deployment scenarios, and providing recommendations to optimize the entire delivery process.

Perhaps most importantly, developers can use ChatGPT to evaluate the overall performance of the CI/CD pipeline. ChatGPT can analyze performance metrics, identify potential bottlenecks, and make recommendations for code and configuration improvements to improve performance.

Active involvement of developers

The success of a ChatGPT integration policy ultimately depends on the active involvement of developers in the process. It is important that all members of your development team are thoroughly familiarized with the capabilities of ChatGPT, as well as its ethical aspects, before you begin the technical aspects of implementation.

For example, ChatGPT user data may contain sensitive information. Developers should handle user data responsibly by following best practices for data privacy and security. Applying measures such as data encryption, anonymization, and data access control can effectively protect user data as such. Technology companies should develop transparent guidelines, policies, and even codes of ethics for the proper use of ChatGPT in an organization.

Once you have implemented ChatGPT into your development process, you should actively solicit feedback from team members for continuous improvement. They should be involved in selecting the datasets you use to train artificial intelligence, as well as in analyzing and evaluating the quality, bias, and fairness of input and output data.

Developers should feel empowered to contribute their experience and expertise to the ChatGPT learning process. Their active participation will not only help align it with the organization's values, but also determine how those values should evolve to meet the rapid changes in the platform's capabilities.

Don't fall for dire predictions -hatGPT and other generative A.I. platforms are not coming for developer jobs. As we have already seen, A.I. generative systems are powerful tools for increasing productivity, optimizing overall code quality, and improving industry wide best practices.

In short, A.I. can do what you tell him to do if you know how to talk to him effectively. But he cannot decide for himself what he should do. It is likely that a human will continue to be forced to think before the A.I. can work its magic, performing time-consuming, laborious, and sometimes monotonous tasks, freeing up the time of skilled professionals so they can focus on more important functions.