Are Developers Actually Relying on Low-Code and No-Code Tools?

Do technologists actually use low-code and no-code tools? A new study suggests that a significant portion of professional developers rely on these tools for at least some of their workflow.

SlashData’s latest State of the Developer Nation shows that 46 percent of professional developers use these tools for some of their work. Within that group, most (19 percent) use it for less than 25 percent of their development work; only four percent use it for 75 percent or more of that work.

“As experience increases, developers are less likely to use [low-code/no-code] tools at all,” the report stated. “This is particularly true among those with more than ten years of experience. These tools are often framed as being best suited for simple programming tasks. Hence, the complexity of development work assigned to more experienced developers may be less appropriate for [low-code/no-code] approaches.”

In other words, these tools have a long way to go before they replace manual coding and traditional workflows. “Using [low-code/no-code] tools without a degree of accompanying manual coding is highly uncommon across all experience levels,” the report added. “Therefore, [low-code/no-code]’s most likely role is as an occasional adjunct to existing coding tools, regardless of developers’ experience.”

For those who don’t know how to code, though, these tools could provide a way to spin up simple apps without needing to ask a (possibly overloaded) tech team. A few years ago, for example, Microsoft released an update to PowerApps that allowed anyone within an organization to put a mobile app together with some drag-and-drop and very simple coding. However, some managers, network engineers, and sysadmins are understandably leery of employees churning out apps without checks or supervision.

As more companies embrace machine learning and artificial intelligence (A.I.) as a way to make apps and services “smarter,” we may also see more teams deploy low- and no-code tools for building machine-learning models and more. Even if you’re a technologist who insists on manual coding, many employees may turn to automated tools to accomplish vital tech work.