AI has been one of the most prominent changemakers in the software development industry. From task automation and predictive analytics to software personalization and enhanced debugging, AI tools are revolutionizing almost every process of the software development lifecycle.
Additionally, one of the most significant areas that AI has impacted is coding. Coding remains a tedious stage of development, and thanks to AI coding tools, developers of any experience can complete coding tasks through AI automation. Auto-completing codes, offering intelligent code suggestions, answering queries about code characteristics, smart error detection in codes, and code search are some of the many things AI coding tools can do.
As beneficial as they are, these coding tools also have limitations. In this blog, we take a deep dive into understanding the pros of using AI coding tools and the drawbacks of the same. Through this, you will get a 360-degree overview of using AI coding tools and what to remember when doing so.
Table of Contents
Pros of using AI coding tools
Let’s first take a look at the benefits of using AI coding tools:
- Better productivity and efficiency
Increasing efficiency and productivity is one of the most significant benefits of using AI in coding. AI coding assistants streamline the coding process in two primary ways – automating repetitive daily tasks and offering intelligent suggestions in real-time. AI coding tools suggest code completion that empowers developers to code better, faster, and cleaner, resulting in lesser debugging.
Numerous tasks associated with coding are both repetitive and time-consuming, like code formatting, writing boilerplate code, code compilation, performing data exploratory analysis, and conducting basic SQL queries. AI coding tools automate these and allow developers to be more productive and complete tasks faster.
- Better code accuracy
Maintaining code accuracy is something a developer can do only if they are experienced. Intermediate or beginner-level developers and programmers often miss out on bugs and other discrepancies in code due to their limited experience. However, AI coding generators, when integrated with code editors, enhance coding accuracy through real-time suggestions based on historical data and best practices, allowing developers to avert common errors.
Analyzing the code when written, such AI tools can detect alarming database query patterns and offer real-time suggestions on using parameterized queries. This, in turn, helps developers to write more accurate and safer codes.
- Easier learning curve
Given how coding isn’t the easiest of topics to master, one of the biggest pros of using AI coding tools is learning coding more simply. These AI-driven coding tools offer suggestions, contextual guidance, and code snippets based on coding best practices, assisting novice programmers to understand and code better. Moreover, AI coding tools offer proper syntax and suggested code templates to accelerate the learning process and increase developer productivity, ultimately helping them build software more efficiently.
- Access to non-development talent
Continuing from the point above, the nature of AI coding tools to provide suggestions and guidance also helps non-developers understand coding and contribute to the codebase. Professionals like designers and project managers can use AI coding tools and be better-coding collaborators, which ultimately helps improve team functioning and developer productivity.
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Cons of using AI coding tools
As the benefits above indicate, AI coding tools are helpful. However, these tools also have certain risks you must know before using them. Here are the cons of using AI coding tools:
- Over-reliance
One of the primary reasons why most AI tools, including coding assistants, face backlash globally is that they result in over-reliance on the user’s side. Many organizations have expressed concerns about developers becoming overly reliant on such AI tools, as they do most of the coding work for them. This dependence can lead to potential degradation of coding abilities as developers begin leaning on AI suggestions without any self-discrepancy.
- The loss of creativity
The over-reliance on AI tools for code generation can also lead to their creativity being hampered. As developers use these tools daily and for almost every coding task, they may get habituated to relying on the AI’s solutions, often based on existing patterns. As such, this can lead to the developer not thinking out-of-the-box or being innovative and just implementing the AI tool’s solution.
- Inaccuracy
While AI algorithms are lucrative, they’re only as reliable as the data they’ve been trained on. Hence, if the training data is biased or outdated, the tool will also generate inaccurate output. This is a common problem that many users have reported with ChatGPT usage, as the output can often comprise outdated or irrelevant information. Many developers who have used AI coding tools have also reported the same. As per a recent Stack Overflow survey, no more than 3% of developers trust the accuracy of AI output. In comparison, 39.3% of the surveyed developers “somewhat trust” AI tools, 21.71% “somewhat distrust” them, and 5.46% “highly distrust.”
Conclusion
Ultimately, AI is the future, and so are its tools, including AI coding assistants. Similar to almost any technology that exists, AI coding tools bear their distinct pros and cons, and users will have to adapt to the technology and be aware of its risks when using it.
Given how widespread AI tools have become, it’s now a disadvantage not to know how to use them. At Be10X, we offer comprehensive cohorts to teach professionals about ChatGPT and other AI tools for upskilling and workplace efficiency. Learn more below.
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