Ally! AI Applied to Micro Tasks in Software Development

With the rise of numerous Artificial Intelligence (AI) tools, it is becoming increasingly accessible for developers to use them as allies in system development, with the potential to transform workflows in unexpected ways. However, many still view AI cautiously, likely out of fear that it could end up replacing their roles or negatively impacting their skills. But what if we start seeing AI as an assistant that needs constant supervision, using it to perform small everyday tasks?

This article will explore how developers can integrate AI into their daily tasks to increase productivity and streamline processes without compromising their skills.

AI as an Assistant, Not a Substitute

First, it's important to change our mindset about the role of AI. Instead of fearing that it will replace developers, we should view it as an ally—a tool that can increase efficiency and reduce the time required for certain tasks. AI can handle more routine and mechanical tasks, allowing developers to focus on more complex problems and achieve more creative solutions.

For example, instead of spending time writing repetitive code or reviewing small code snippets, AI can be used to automate these processes. Tools like GitHub Copilot already offer code suggestions and even complete parts of basic functions, saving time and mental energy.

Automating Repetitive Tasks

Although widely used as a research tool for answering specific questions, AI can be applied more broadly within development. One of the first areas where developers can begin to use AI is in automating repetitive and tedious tasks. Instead of manually coding multiple repetitive functions, AI can be used to automatically generate code snippets, refactor old code, or even adjust formatting according to predefined standards. Just as we used to rely on IDE shortcuts and extensions to generate classes, interfaces, and methods, AI can now be used to do the same on a broader scale within the project, more integrated with the developer's workflow.

Tools like Visual Studio IntelliCode and ReSharper, for example, offer intelligent suggestions based on common patterns found in large codebases. These small automations can save valuable minutes in each coding session, which adds up to significant time savings over time.

ReSharper itself already includes an AI assistant, adding another layer of intelligence to code analysis and suggestions, continuously learning from the developer's coding style and improving with each interaction, becoming more integrated with the developer's way of working.

AI to Improve Code Quality

AI can be a great ally in improving code quality. Machine learning algorithms can be trained to detect potential bugs, suggest performance optimizations, and even perform security analyses on the code.

Instead of manually reviewing hundreds of lines of code for subtle errors, developers can use AI-powered tools to quickly find problems and ensure the code follows best practices. This not only increases the quality of the final product but also reduces the amount of rework needed. AI can be an assistant that, working collaboratively with the developer, analyzes entire system codes in a short time—a task that would take hours and intense concentration for a professional. Using AI for these more repetitive and attention-demanding tasks frees up time for developers to focus on more essential system routines.

Using AI to Learn and Grow

Another major benefit of AI is that it can serve as a learning tool. By providing code suggestions, explaining patterns, or recommending libraries, AI can help developers—especially those with less experience—learn new languages, frameworks, and techniques in a practical way.

For example, if you're starting with a new language, AI tools like ReSharper, Intellisense, and others can suggest more efficient ways to write code, helping you learn best practices while working on real projects. AI can also offer insights into how other developers have tackled similar challenges, bringing inspiration and new approaches to your work.

As mentioned in the first article, "Developers and AI: Resistance to Incorporating AI in Software Development", Iavor Bojinov, from the course "AI Essentials for Business" at Harvard Business School, states that "AI is like a recent college graduate with a lot of information, much enthusiasm, but little practical experience." In other words, the human factor is essential. The adoption of AI in software development doesn't have to be drastic. Starting small, integrating AI into routine and repetitive tasks, and using "baby steps," allows professionals to experiment with the potential of this technology without losing control over the creative and development process. As confidence in these tools grows, AI can become a powerful ally to increase productivity and improve code quality.