7 Ways to Future Proof Your Developer Job in the Age of AI

Artificial intelligence (AI) is relatively new to most programmers, but within Microsoft, tens of thousands of developers are already using GitHub Copilot, said Microsoft’s Amanda Silver, corporate vice president of product, developer division.

“I’m already seeing the positive impact AI is having on developers and their teams firsthand,” Silver told The New Stack. “GitHub Copilot saves developers time on mundane tasks like writing boilerplate code and learning a new domain, freeing up time to focus on more meaningful aspects of product making.”

Microsoft’s research shows that 90% of developers using GitHub Copilot are completing tasks faster and 73% are better able to stay in flow, she added.

Developers don’t seem to fear AI. In fact, the data and antidotal evidence shows they’re embracing it. The 2023 Postman’s State of the API queried more than 40,000 developers/API professionals and found that 60% are using generative AI, with more than half those using it to find bugs in their code and over a third relying on AI to generate code. A GitHub survey of 500 developers revealed that 92% of U.S.-based developers are already using AI coding tools both in and outside of work. That reflects what those we spoke to are seeing in the field.

“A high percentage of coders are using AI to their benefit,” Scott Likens, leader of PWC’s Innovation Hub, told The New Stack. “Will it change the way we code? Sure, but that’s probably okay because we’ve been coding the same way for a long time and it’s giving us an opportunity to rethink and to really empower engineers to use the tools.”

Should Programmers Be Worried?

While the six industry leaders we spoke to said developers shouldn’t worry about AI taking their jobs, they also cautioned that developers should prepare to adapt the way they work in light of AI. That said, they told us AI will create an overall positive experience for developers, who will be able to leverage it for mundane tasks such as writing tests and code documentation.

“AI will absolutely change the way we work — and it already has,” Silver said. “But I see this as a really good thing for developers. As generative AI tools are increasingly integrated into the development lifecycle, developers can move beyond tasks that have historically bogged them down and instead hone in on building innovative, complex, and differentiated applications. They can focus on the fun and leave the chores to the AI.”

Likens, who started out as a programmer, expressed a similar idea, saying “the brilliance of programming is still a human trait,” but AI will require developers to evolve.

“We’ve seen that with technologies and being a programmer from the early ’90s, languages have changed. Even Python today is very different than when I coded and C, C++, Assembly, back in the day, very different,” Likens said. “And what that allowed us to do is focus more on the fun part, which was the problem solving versus the syntax.”

Developers are constantly learning something new and should treat AI with the same growth mindset, suggested Dana Lawson, vice president of engineering at Netlify.

“The worst thing somebody could do is just freak out and not at least understand how they can implement and enable their job,” Lawson said.

Future Proof Your Career

Which brings us to the real question — how can developers future-proof their careers in the age of AI? Here’s what industry leaders told The New Stack:

1. Adopt systems thinking. This is the integral part of being a developer that cannot be done by AI, Silver said. Practice systems thinking to “create and refine complex solutions that address real problems,” she suggested. “The ability to understand how complex things interact is crucial for building apps that are resilient and scalable.”
2. Infuse AI into your solutions. “At Microsoft Build we were able to share building blocks in our tools and services so that developers can infuse AI into their solutions,” Silver said. In other words, don’t just look at how AI can help you do your job, but look at how it can be leveraged within your solutions to solve problems for others.
3. Start with the Basics. Focus back to the basics of your website or web application, advised Lawson. Are there performance issues you could address, for instance? Then allow AI to do some of the tasks that aren’t your strength or you don’t want to do, she advised. “Maybe you are doing a brand campaign and you want to do checks and balances, make sure everything’s been updated and change testing the software, being smart about it,” she said. “Instead of writing all the test cases by yourself, you’re going to have a tool that can look at your code and say, ‘I know where to find it.’ That’s going to be really powerful.”
4. Leverage AI where your own skills are weak. Leandro von Werra, a machine learning engineer at Hugging Face, used a model to help him write HTML code. “I used such a model to help me do it because I had no idea and I didn’t have to read tutorials, and… I could make it work pretty quickly.” Many programmers have professed to using AI to learn new languages, as well.
5. Check for hallucinations. Hallucinations are a valid concern, experts agreed. Fortunately, with code, you can compile it or test it to ensure it works. But watch for AI to improve in this regard, say Lee Robinson, vice president of developer experience at frontend platform Vercel. “A lot of the newer large language models, when you see the improvements that they’re rolling out, they’re adding a lot more nuance,” Robinson said. “They’re presenting both sides of the argument, and they’re clearly linking back to the sources that they were generated from.” It’s also easy enough to have the AI fix incorrect code, he added, by pasting the error back into the AI and telling it the code is incorrect.
6. Expand your skills “It would be good for developers to familiarize themselves with AI-powered coding tools which can help code faster and more efficiently,” said Gaurav Kachhawa, CPO of Gupshup, a conversational AI platform. Developers should also look at contributing to open source projects to learn new skills and get involved in the coding community, he added. Silver also suggested developers hone any skills that machines don’t do well. “Focus on building your skills in creative problem solving, relationship building, and getting to know your end-customers or organizational operations well so you can build apps that are relevant and valuable,” she said. She added developers should “lean into” any specialized skills or interests that they have because niche and nuanced expertise is less likely to be automated by AI.
7. Embrace a growth mindset. Silver said developers must be willing to adapt and learn AI. “At the end of the day, try to remember that growth and change always lead to innovation, which is a cornerstone of our industry. Stay curious and keep asking questions,” Silver advised.