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Don’t Think AI Is Taking Engineer Jobs! It’s Empowering Me!😅”

How Generative AI is Changing Engineers

Generative AI tools are making engineers’ daily work much more productive. Many engineers use AI coding assistants like GitHub Copilot, Amazon CodeWhisperer, and Tabnine, which help them code faster on average, more than 55% increase in speed. These tools take care of repetitive coding tasks, so developers can focus more on solving complex problems instead of writing the same code again and again.

AI also like the clean code…

Based on my experience, I want to explain environments where AI is well-suited for development and where it is not.

Useful in the following cases

  1. Repetitive coding tasks → Something like case division where the body of the code remains the same, AI can easily handle it, avoiding human errors such as missing commas or incorrect capitalization.

  2. Learning new development areas → When studying new technologies, we often feel exhausted due to unfamiliarity, but AI helps us overcome this.

  3. Exploring use cases → AI can suggest practical applications and implementations to help understand use cases.

  4. Debugging, error resolution, and environment setup → It assists in identifying bugs, fixing errors, and configuring development environments efficiently.

  5. Refactoring, architecture improvement, and modifications → AI helps optimize code structure, enhance maintainability, and suggest architectural modifications.

Don’t rely too much on AI in these cases…

  1. If versions differ with mine, referring to the latest official documentation may be faster.

  2. When user experience is crucial, it’s better to adjust variable values manually.

  3. Thoroughly review AI-generated code, sometimes it produces faulty code.

  4. Keep your code structure clean. lower modularization often leads to lower-quality code.

  5. If the issue persists, google search might be better way..

Cursor AI, Engineers do not use GPT more!

CursorAI is a new tool that helps engineers write code more efficiently using AI. Unlike GPT, which is a general tool for many tasks, CursorAI is made specifically for coding. It understands the details of programming languages and project structures, making it more useful and focused for engineers. CursorAI can do more than just suggest simple code completions, it gives us real-time help with debugging, finds possible errors, and can even create whole sections of code for us. While GPT can help with coding, GPT does not always give us the best suggestions because it’s not made just for programming. CursorAI, on the other hand, is designed to understand coding patterns, syntax, and best practices, so it gives us smarter suggestions that fit our project better.

How to Use AI for Better Mindset.

As software development keeps changing, generative AI like CursorAI is becoming an important tool for engineers. But it’s not just about automating repetitive tasks or writing code faster. It’s about thinking in a new way to be more efficient, focused, and work better with others. Here are some ways engineers can use AI to become better at what we do:

1. Think Bigger

Generative AI can help us stop spending so much time on the small, repetitive parts of coding and start focusing more on the big picture. AI can write the basic code for us, leaving us to think about the design and the overall structure of the project.

When AI handles the routine stuff, we have more time to think critically about how the project should work. This means we can create better solutions and spend more time making sure our code is organized, scalable, and future-proof.

2. Be a Fast Engineer Who Can Meet Deadlines

One of the best things about generative AI is how fast it can write code. This helps us finish tasks quickly, and it’s a huge advantage when you’re working under tight deadlines.

With AI helping us with repetitive coding, we can spend more time on important parts of the project. This means we can complete tasks faster, without sacrificing the quality of our work.

3. Be a Engineer Who Works Well with Others

Finally, AI can help us write clean, well-structured, and easy-to-read code. Code that is well-organized and properly commented makes it easier for everyone on the team to understand and work with.

When we use AI to write code efficiently, we not only finish our tasks faster but also make our code easier for other people to collaborate with. This is a huge advantage when working in teams, because everyone can quickly understand and build upon each other’s work.

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