Published on October 25, 2023, 1:58 pm
Generative artificial intelligence (AI) and other AI-based programming tools are gaining popularity in the software development community. These tools have the potential to revolutionize the way developers create applications, and even make coding accessible to non-developers. However, it may take some time before we see their full potential as productivity-enhancing tools.
According to a recent survey by O’Reilly, one-third of developers are already utilizing generative AI environments such as GitHub Copilot and ChatGPT. However, it is likely that this estimate underestimates the actual usage of these tools, with many programmers experimenting with them on personal projects or using them alongside their regular workflow.
While generative AI shows promise in simplifying development processes, widespread adoption may still take some time. The survey revealed that training and ease of use are two significant challenges for developers working with these new tools. This finding comes as a surprise since these tools are designed to be low-code or no-code solutions. It suggests that there is a learning curve associated with incorporating generative AI into workflows, and its complexities may have been underestimated.
Despite these challenges, productivity tools like Copilot are reshaping software development in radical ways. They offer value to developers but require investment in terms of learning and understanding their capabilities fully. Unlike what some might believe, using generative AI doesn’t mean effortlessly generating an enterprise application with a single prompt. Each tool has its own learning curve that should not be underestimated.
Once developers become proficient in working with generative AI-developed code, we can expect it to extend its benefits to citizen developers as well. Generative AI holds tremendous potential for transforming how software is built, tested, and deployed—adding an entirely new dimension to the low-code and no-code movement.
Katherine Kostereva, CEO of Creatio, expresses excitement about the future of generative AI for no-code automation. She envisions numerous use cases emerging in the coming years, where generative and conversational AI will streamline the development process. The convergence of no-code and generative AI enables developers and non-developers alike to leverage visual drag-and-drop tools. Generative AI can automatically generate templates, components, or entire applications based on user input, saving time and effort in converting basic requirements into prototypes.
Generative AI also opens up opportunities to enhance apps with new capabilities and use cases. For instance, it allows for the addition of human-like text responses, analysis of historical data within an app, or even generating decision recommendations. As generative AI continues to evolve in the low-code and no-code space, we can anticipate accelerated development. Tools that incorporate generative AI will expedite application creation using no-code methods. Users will be able to focus more on describing the expected outcome rather than manually laying out each step.
In conclusion, generative AI has shown remarkable potential in transforming software development processes. While there are challenges involved in training and mastering these tools, their benefits are worth exploring for both developers and non-developers alike. As generative AI advances, we can expect it to become a valuable asset in streamlining application development and boosting productivity across the board.