AI coding tools are gaining traction throughout the high-tech industry. Recent research reveals which services are most popular among engineers.
In May, Jellyfish, who helps businesses manage their developer teams, surveyed 645 full-time experts in a variety of engineering roles, including individual contributors, managers and executives. Respondents came from companies ranging from small teams of less than 10 people to companies with over 500 engineers.
The findings shed new light on the explosive growth and impact of AI coding tools in software development.
Jellyfish has found that 90% of their engineering teams are now using AI in their workflows from 61% just a year ago. Almost a third are officially supported, widely adopted AI tools, and an additional 39% are actively experimenting. Only 3% of respondents also did not report on how AI is used and plans to change it.
Importantly, 48% of respondents reported using two or more AI coding tools, suggesting that teams take a diverse exploratory approach by simultaneously assessing multiple solutions rather than standardizing on a single platform.
leader
According to the survey, the leader in AI coding tools is Microsoft's Github Copilot, with 42% of engineers surveyed naming the selected tool. Google's Gemini Code Assist was second, but Amazon Q (formerly Codewhisperer) and cursor were tied to third.
These four tools formed the dominant layer of AI-powered code-assisted platforms, but according to reports, there were also several services in the mix.
A chart showing the popularity of various AI coding tools Jellyfish
This study focused on products designed specifically for software engineering, explicitly excluding general purpose generation AI tools such as ChatGpt. This distinction highlights the increasing specialization of AI solutions tailored to the needs of development teams.
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According to the report, 62% of engineers said speed and productivity increased by at least 25% thanks to AI coding tools, while 8% reported doubling the output. Less than 1% believe AI is slowing them down.
Human-AI Hybrid Workflow
Future, 81% of respondents believe that at least a quarter of today's engineering work will be automated by AI within the next five years. However, trends are not directed towards full automation. It's heading towards collaboration.
“AI can help creatives, but AI itself is not creative,” one engineering leader put it in the research response.
“If there are some smart people using AI, if they understand the topic/problem they are doing, the magic happens,” the person added. “If not, there are people who just want to look like you've done something amazing and don't really understand the problems you created with the help of AI.”
With productivity gains already measurable and adoption increasing, the current harvest of AI coding tools led by Github Copilot, Gemini, Amazon Q and Cursor appears to set the basis for a hybrid future where software engineers and AI systems co-create next-generation digital products.
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