AI coding tools mean there are no more junior software developers

• AI coding tools like GitHub Copilot have transformed software development and productivity.
• AI assistants close inexperience gaps, although they can lead to less secure, error-prone code.
• Software engineering skills, such as creating intelligent architecture for code, will continue to be relevant.

Before graduating college, Jacob Jackson founded the AI ​​coding assistant TabNine in 2018. Jackson, a computer science student, wanted to reduce the repetitive, sometimes boring tasks a programmer might encounter.

“We were just trying to save people’s keystrokes. There was no talk of designing AI or writing complete algorithms,” he said.

His startup eventually raised about $60 million and was acquired by the Israeli company Codota in 2019. Jackson continued to work with AI, continuing to work on OpenAI, the company that built ChatGPT.

In the past couple of years, there has been a boom in AI coding assistants. OpenAI’s competitors have released widely used generative AI development tools such as GitHub Copilot and Claude Anthropic. The rise of ChatGPT and AI coding assistants has changed the way software developers do their jobs. Using AI to write code could also bridge the experience gap between junior developers and senior developers, as it usually takes several years of work and even personal projects to level up.

“There are no more junior developers, because AI basically elevates everyone to be beyond that,” said Nikolas Gauvreau, who has worked as a developer in Canada for more than 20 years.

More than 97 percent of 2,000 respondents from the US, Brazil, Germany and India said they used AI coding tools at work, according to a GitHub survey published in August. Generative AI code suggestion tools can also increase the productivity of software developers by 26 percent, according to a study that analyzed data from Microsoft, Accenture and an unnamed Fortune 100 electronics manufacturing company.

Developers say the adoption of AI coding assistants will accelerate the field of software engineering rather than eliminate jobs, the way computers have accelerated math, despite initial protests from teachers against its adoption.

While these tools can increase productivity, they can also introduce security issues that create more work for developers. According to a 2022 study led by Stanford University cryptography professor Dan Boneh, people using an AI assistant type significantly less secure code than those without access to those tools. While AI assistants can speed up the coding process, they can create more errors that require human supervisor intervention.

AI assistants can empower coders

Most generative AI coding assistants focus on auto-completion, meaning the tool suggests code as the programmer types. Other language learning models (LLM) require prompt engineering, where the user can then apply the suggested AI. code as a starting point for their idea, depending on the complexity of the problem they want to solve.

Before coding assistants came along, DeepAI founder Kevin Baragona always had a Google search window open in case he needed help solving a problem. Programmers often did research from resources such as Stack Overflow, an online community forum where programmers shared their solutions. Stack Overflow’s traffic has declined since the rise of coding assistants.

“Every few minutes when you’re programming, it was kind of the cheat code back then, and it just became normalized as what you do when you’re coding: you do a lot of Googling,” Baragona said.

Knowing several coding languages, such as JavaScript, Python or Ruby, gives a programmer more flexibility in the job market when companies change priorities. Learning a whole new language, however, would require a lot of time and learning.

Now, deep learning models have enabled the translation of many programming functions from one language to another, making it easier for developers to switch between programming languages ​​without having to learn them quickly. Baragona said these tools make him feel like he knows “every programming language, even if I don’t, because AI will help me get over the hump very quickly.”

Gauvreau said AI coding assistants have empowered him because he’s less afraid to take on more customers, even when they may not yet know the solution. He said he has doubled the number of languages ​​he has learned in the past year, more than his entire career.

AI can help computer science students

Instead of shying away from coding assistants, some universities have developed their own versions that would help students ask the right questions — another way AI tools can bridge the skills gap.

David Malan, a professor who oversees the popular CS50 Introduction to Computer Science course at Harvard University and online on edX, helped lead the creation of the cs50.ai chatbot for the course. Malan said AI programs are “all too willing to answer all your questions, but not in a way that’s probably consistent with what a good teacher or tutor would prefer you do.”

“The goal is to teach students how to think and how to solve problems with the tools we have today and will eventually have when it comes to real world and software application,” he said. Malan told Business Insider.

AI coding assistants can especially help online students in the class, who might not necessarily have the luxury of a teacher’s assistant, have a “virtual tutor by their side,” Malan said.

AI has shortcomings

While Baragona said AI coding will become an everyday reality for the next generation of programmers, he believes it’s about training programmers to be lazier, which could create problems they won’t know how to solve solve them.

“You quickly get to a point where the AI ​​has done all the work, but it still has bugs and you don’t understand the code at all because you didn’t write it,” he said.

Once the code reaches a certain level of complexity, it discovers that the AI ​​has dug a hole deep enough that it can’t get out.

“And at that point, you’re really mad because you can’t understand the code, you can’t fix it, and neither can the AI,” he said.

Developers for studios under Microsoft have been encouraged to adopt Microsoft Copilot as a coding assistant, according to an Activision Blizzard contractor whose identity was confirmed by BI and who asked to remain anonymous because he is not authorized to speak to the media. However, he said he has to be very specific when working with Copilot.

“AI doesn’t have a view of what you’re trying to build because coding is really like building a building. AI can build you a small piece,” he told BI. “We actively tried to use Copilot in our tests, but it just wasn’t good.”

While many developers have chosen to delegate specific AI coding tasks to reduce their workloads, they say establishing a solid foundation in computer science and software engineering will continue to be relevant.

Software engineers don’t just code; also solve problems and design systems. In this case, people still have an advantage.

“Today’s AI tools don’t create thoughtful architectures the way a human would. They’re kind of coding with short-term thinking,” Baragona said.