AI Tools Improve Learning Process for Developers

In the new technology era, AI helps software developers speed up their work. It also enables them to learn and switch between new technologies more easily. AI assistants make learning more efficient and save time for developers.

How exactly can AI be useful for developers to develop and learn new technologies?

Developers can use AI to create a roadmap to learn new technologies, for example, new programming languages or new frameworks. AI assistants will help them focus on studying specific goals, tasks, and projects.

Previously, in order to start working with a new technology, developers had to watch hours of tutorials or re-read many articles, but now they can get short instructions and code examples from AI.

AI can generate comparison tables for programming languages or frameworks, helping developers adapt more quickly. Additionally, AI makes it possible to quickly find the necessary part of the documentation.

When a developer starts working on a project with new technologies, AI can help them understand the project’s business processes faster, provide descriptions, and explain what’s happening in specific modules or files of the project.

Usually, a developer needs to spend some time understanding how a piece of code works, and with the assistance of Artificial Intelligence, this time can be minimized. AI is especially convenient when working with new technologies, as it can explain processes and quickly locate necessary files or code.

Personal Experience

Personally, I have experience switching from one technology to another. I am a Java software developer; I was working with Spring Boot. I recently started learning a new technology for me, Node.js. And since Spring Boot framework and Node.js runtime environments are used for creating web applications and APIs, using AI made it as easy as possible for me to understand the environment for building a back-end application.

An AI assistant generated for me Node.js code examples and compared them with similar examples for Spring Boot. As a result, thanks to such analogies, I quickly understood how the Node.js runtime environment works. I used GitHub Copilot, which allows you to choose and use different language models.

This was convenient because if I didn’t use AI, I would spend more time re-reading the documentation and Stack Overflow to find the answer to a question, but now the AI assistant did it for me. This saved me a lot of time and allowed me to immediately get into practice. The AI also immediately checked the code I wrote and provided recommendations for its improvement.

Debate

There is a debate that AI reduces the level of developer skills, but I believe that if you have a smart approach to using AI, then the amount of knowledge and skills that a developer has can actually increase.

Thanks to AI, a developer can switch between various technologies that are used for similar purposes (for example, backend or frontend) many times faster than before, if a person already has experience in development and has good knowledge of system architecture and patterns.

All things considered, developers’ use of AI combined with their own experience, ideas, and intuition can take project development to a new level.

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