The role of AI in software engineering is evolving. This shift brings excitement for some and anxiety for others. Understandably, this mix of emotions creates space for myths and misconceptions to take hold.
In this post, we tackle five common myths about AI tools in software engineering, debunking each one and encouraging those interested in coding to embrace AI tools to learn, boost productivity, and create impactful projects.
Myth 1: AI will replace developers.
As in many professions, tech and AI tools are changing the role of software engineers. Today’s engineers use AI to automate repetitive tasks, assist with code writing, and suggest optimizations, among other functions. According to the 2024 Stack Overflow Developer Survey, “76% of all respondents are using or planning to use AI tools in their development process this year, an increase from last year’s 70%.” The two most-used AI tools among developers are ChatGPT and GitHub Copilot, with roughly 41% of all developers reporting they used Copilot in the past year.
But these numbers don’t signal replacement – not even close. That’s because human software engineers are essential for using these tools effectively. They need a solid understanding of how software engineering works to use AI to enhance their processes.
Beyond technical skills, human engineers bring deep problem-solving abilities and unique creativity. They understand the business context behind their projects and collaborate with teammates and stakeholders, ensuring good communication and overall project alignment.
Rather than replacing software engineers, AI is becoming a powerful tool that enhances productivity and creativity. The human role in shaping, guiding, and innovating remains essential and irreplaceable.
Myth 2: AI can write perfect code.
AI productivity tools like GitHub Copilot, ChatGPT, and others are useful for assisting coders, but they don’t produce perfect results. These tools can boost speed, improve syntax, and generate standard code structures, but they fall short when it comes to context, nuance, problem-solving, and addressing cybersecurity concerns.
Ultimately, AI lacks the human judgment required in software engineering to balance critical trade-offs like speed vs. scalability or simplicity vs. flexibility. That’s why these tools are best used to enhance human work, not replace it.
Myth 3: Junior developers are becoming obsolete.
Junior developers are far from obsolete. They remain in high demand for many reasons, including their fresh perspectives and eagerness to learn. Junior developers also represent the future of tech teams, growing into mid-level and senior roles, which is a kind of growth that’s essential for any team’s long-term health. Every senior developer started as a junior. Without continued investment in junior talent, companies will struggle to fill more advanced roles down the line.
That said, today’s junior developers are often expected to use AI tools to enhance their productivity. To stay competitive in the job market, it’s crucial to master these tools while also building a strong foundation in coding, systems design, problem-solving, and collaboration – skills that AI can’t replace.
Myth 4: There’s no need for software engineers to learn new skills with AI.
This myth comes from the belief that AI can do – or will eventually be able to do – everything you need it to do. So why keep learning new skills?
But while AI is a powerful tool, it’s just that: a tool. The tech industry moves fast, and staying adaptable has always been part of being a great software engineer. AI can help write code, sure, but it’s still an engineer who decides what to build, why to build it, and how to do it right alongside their teammates.
The more you understand new frameworks, languages, and methodologies, the better you can use AI to enhance your work rather than overly relying on it and not understanding the mistakes it makes.
Myth 5: AI is only used in big tech.
The reality is that AI is being used everywhere, certainly not just in big tech companies. Software engineers across industries and companies of all sizes are using these tools to improve their work.
This includes engineers at startups, small businesses, mid-sized companies, and in non-traditionally-tech industries like healthcare, finance, retail, and more. AI is becoming a tool for software engineers at all levels and in all companies to learn and build faster and smarter.
Ready to learn how to use AI tools for software engineering?
Whether you’re just starting out or you’re an experienced coder, understanding how AI tools can help you learn and enhance your skills and projects is essential.
In our coding bootcamps, we start by teaching students the core coding fundamentals they need to succeed without relying on AI tools. Once those foundations are in place, we introduce GitHub Copilot, the popular AI productivity tool used by software engineers at every level. We believe that establishing a strong foundation is crucial, but once you’re ready, mastering AI tools becomes essential to your modern-day success as a software engineer.
Now is a great time to start learning! Get your coding bootcamp application started today.