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The rise of generative AI tools like ChatGPT and GitHub Copilot has changed the software development landscape. These tools automate repetitive tasks and provide coding help. Jacob Jackson started the AI coding assistant TabNine in 2018.
This might be the best “AI Engineer” I’ve tried so far.
I’m an old school developer who started 30 years ago. I feel very uncomfortable letting AI take control of my code, but for the sake of science, I spent two hours building an application that took me weeks to build a… pic.twitter.com/4EQH0Hb85t— Santiago (@svpino) October 1, 2024
He wanted to reduce the repetitive tasks programmers face. “We were just trying to save people keystrokes. There was no talk of AI designing or writing full algorithms,” Jackson said.
“it managers have long said that their bosses want ever more digitisation with ever tighter budgets. Thanks to ai and offshoring, that may no longer be too much to ask.” https://t.co/m3f4oGZP2q
— Yosuke YANASE （柳瀬陽介） (@yosukeyanase) September 30, 2024
His startup raised about $60 million and was bought by the Israeli company Codota in 2019. In recent years, many AI coding assistants have launched. This has changed how developers work.
“Code analysis firm sees no major benefits from AI dev tool when measuring key programming metrics, though others report incremental gains from coding copilots with emphasis on code review.”https://t.co/ioNgB8O94y#GenerativeAI #programming
— Bob E. Hayes (@bobehayes) September 30, 2024
What’s Wrong With Generative AI-Driven Development Right Now | By @jkriggins#GenAI #CyberSecurity @SonyaMoissethttps://t.co/I6Do58EbtY
— The New Stack (@thenewstack) October 1, 2024
Nikolas Gauvreau, a developer in Canada, says, “There’s no such thing as junior developers anymore because AI basically elevates everybody to be beyond that.”
More than 97% of 2,000 people across the US, Brazil, Germany, and India have used AI coding tools at work. These tools can increase software developer productivity, according to a study that looked at data from Microsoft, Accenture, and an anonymous Fortune 100 electronics manufacturing company. While AI coding assistants boost productivity, they also bring potential security issues.
A 2022 study led by Stanford University cryptography professor Dan Boneh found that people using AI assistants wrote less secure code compared to those who did not. Generative AI coding assistants mainly focus on auto-completion, where the tool suggests code as the programmer types. Other language learning models (LLMs) let users apply AI-suggested code as a starting point for solving complex problems.
Kevin Baragona, the founder of DeepAI, noted that these tools have reduced the reliance on resources like Stack Overflow for problem-solving.
GitHub Copilot’s impact on developers
Knowing more than one coding language provides a competitive edge in the job market.
However, learning a new language takes a lot of time and effort. AI tools have made it easier for developers to switch between programming languages without much hassle. Baragona says these tools make him feel like he knows “every programming language, even though I don’t.”
Gauvreau shares a similar view, stating that AI coding assistants have empowered him to take on more clients and learn new languages faster than ever before.
Some universities have developed their own versions of AI coding assistants to help students ask the right questions. David Malan, a professor overseeing the Introduction to Computer Science course at Harvard University, helped create a chatbot for the course. Malan emphasized that the goal is to teach students how to think and solve problems with current and future tools.
Baragona warns that while AI coding will become a daily reality for the next generation of coders, it may lead to complacency. “You quickly get to a point where the AI did 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. An anonymous Activision Blizzard contractor noted that while AI tools like Copilot can help, they require very specific instructions.
“AI doesn’t have a vision of what you’re trying to build because coding is really like building a building. AI can build you one little piece,” he said. Despite the advances in AI tools, establishing strong fundamentals in computer science and software engineering remains important.
Software engineers are not just coders; they also solve problems and design systems. Baragona remarked, “The AI tools today don’t create thoughtful architectures the way a human would. They kind of code with short-term thinking.”
AI coding assistants undoubtedly speed up the coding process and fill some gaps between junior and senior developers.
However, the essence of thoughtful software engineering still relies on human expertise.
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