Software developers, no matter how skilled, face tasks they’re not very good at. For Geoffrey Bourne, cofounder of Ayrshare (“airshare”), a New York-based startup that automates and manages social sharing for corporate clients, it’s using what’s called regular expressions—tools used in virtually every programming language to identify patterns of text.
Generative AI platforms like GitHub Copilot and ChatGPT have been trained on billions of lines of code for many programming languages and are surprisingly good at predicting what lines of code developers should use next.
AI-enabled coding assistants function like autocomplete on steroids. You start by typing an “if-then” statement, and suddenly the rest of it shows up on screen.
“About 30% of the time, it’s spot-on,” says Bourne. “What might have taken me five or 10 minutes of writing code takes about 20 seconds. Multiply that over a day of programming, and it saves me hours.”
In Copilot’s first year of release, almost one-third of its coding suggestions made it into final code, and Copilot cut the average amount of time needed to complete coding tasks by 55%.
They also offer another key benefit: helping coders be happier and more productive. Between 60% and 75% of Copilot users say they find their jobs more fulfilling, and 74% say these tools allow them to focus on more satisfying work.
As AI takes on more of the programming burden, organizations can expect to see boosts in productivity and creativity from their engineering teams. That aligns well with the need of many CIOs to extract productivity gains from every corner of IT.
“IT leaders report the most success when working with their teams to reduce complexity and streamline efficiency,” says Prasad Ramakrishnan, CIO at Freshworks, “including by adopting new automation technologies fueled by AI.”
Time-saver on steroids
AI coding assistants excel at the mundane, repetitive stuff nobody really enjoys doing, such as generating boilerplate code, explaining errors, creating documentation, or looking up syntax in a language you’re less familiar with, says Giancarlo Erra, founder and CEO of Words.Tel, an AI-based service that brands can use to create and reserve taglines and advertising slogans.
“I use AI for coding daily via ChatGPT, Anthropic’s Claude, or Copilot,” says Erra. “Most of the time, asking ChatGPT is all you need to solve your problem. The impact it has on the speed of my work is substantial.”
When software code hallucinates
However, sometimes the AI makes things up, a phenomenon known as hallucination.
For that reason, AI coding assistants are no substitute for experienced developers. If you don’t have the skills to recognize when the assistant is churning out garbage code, you could end up in trouble.
“You need to know enough to say, ‘That looks kind of right. Now I need to take that code snippet, run it, and see if it matches the results I expected,’” Ayrshare founder Bourne advises. “Otherwise, you’re taking a risk.”
However, by allowing developers to reduce basic work, gen AI coding tools can allow them to spend more time being creative and building great user experiences.
Bigger aspirations ahead
Overall, AI coding assistants can flatten the learning curve for less-experienced developers and save time for more advanced coders, notes Bourne. They can also lead to more innovative software solutions.
“These tools encourage innovation and creativity by allowing programmers to take on bigger projects, try out fresh concepts, and concentrate on more strategic areas of development,” adds Vikas Kaushik, CEO of TechAhead, a mobile app developer for Fortune 500 companies.
“Over the next three to five years, I see AI assisting devs not only with coding but also with choosing the right coding architecture, code reviews, and project management.”
A version of this story originally published on The Works.
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