Decoding the Low-Code Dilemma
- By Winston Thomas
- January 12, 2025

Remember when AI-powered low-code promised to unlock software development geek-dom, handing the keys to the uninitiated masses? Well, the reality is a bit more complicated. Yes, GenAI has indeed crashed the party, bringing a whirlwind of possibilities. But it has also introduced a new set of severe headaches.
“Companies were just scrambling to understand GenAI and how it may impact their business, both from an opportunity perspective and as a challenge or threat,” says Mark Weaser, vice president of APAC at OutSystems. “Now they’ve realized this technology is going to be ubiquitous, and we need to find vendors with a good roadmap for integrating these technologies into existing solutions.”
The main challenge? This AI-powered low-code revolution is speeding development. Some companies are simply struggling to keep up.
The speed paradox
The allure of GenAI driving rapid application development is undeniable. But while speed-to-value remains a critical metric for success in application development, it can also be a double-edged sword.
When you combine GenAI and low-code platforms, you get what Weaser calls a “hyper-acceleration” of development cycles. “We were building things three to five times faster than traditional development. This accelerates [software development lifecycles] by a factor of 20 or 30; maybe even faster,” he notes.
But this unprecedented acceleration is causing organizational whiplash. Companies are not prepared for it. Many lack the cultural and structural framework to manage such rapid development cycles. And, of course, once you set end-user expectations of faster rollouts, it’s hard to roll them back.
This creates high-risk applications that are being developed without rigorous oversight or governance as those parts of the software development lifecycles get buried in, well, code.
Reimagining the SDLC
OutSystems’ response to this challenge is the Mentor, formerly called Project Morpheus. It adds a digital worker to help the developer focus on developing better code. For example, the system can transform a requirements document into a working application prototype in seconds — a process that traditionally took weeks or months.
“It’s kind of like giving your kid a puzzle with 10,000 pieces and then giving them the puzzle with 9,000 pieces already done,” Weaser explains. “You’ve made so much progress already, and then you can use the platform to finish off the application.”
This capability fundamentally alters the software development lifecycle. The front end of development is dramatically compressed, but the need for proper integration, security, and governance remains. They are also where the developers will now be focusing more of their energy.
It’s a shift that’s particularly relevant in the Asia Pacific, where according to an IDC InfoBrief “Mission-Critical Software, Delivered: Harnessing the Synergy of Low Code and GenAI,” sponsored by OutSystems, 60% of applications still run on legacy systems.
“Our platform tended to be able to repurpose legacy systems at a faster rate,” Weaser notes. “We put OutSystems over the top of it, drop APIs down, and then build the high change layer on top of the legacy system.”
The developer identity crisis
The rise of AI-powered low-code platforms is sparking heated debates about the future of software development. Critics argue these platforms will lead to a decline in coding skills. Weaser disagrees: “The role of the developer is being automated, but it's not going to get rid of developers. It’s just going to change the nature of how they do things.”
Instead, he sees a shift toward higher-level skills with solutions like his company’s Mentor. “The Enterprise Architect role will become even more important. It’s like at Tesla — the guy overseeing the robots [in the production line] now has a very important job, and he needs to be technically fluent in those technologies. But his role is different.”
Perhaps the biggest advantage of Mentor is the ability to flag unauthorized code during development. As AI-powered low-code platforms democratize development, companies face increased security risks from unauthorized code deployment.
“When you lose visibility to development, that’s what’s dangerous in a company,” Weaser warns. “You don’t want people in the business putting unauthorized code out there that might be a security risk.”
Platform-based governance models provide visibility and control over development activities. This becomes particularly crucial as companies grapple with the ethical implications of AI development tools and potential biases baked into these models. But in the past, development teams were fighting against time; with the AI Mentor, they won’t, says Weaser.
Navigating a low-code future
The convergence of AI and low-code development is not a question of “if” but “when”. Companies that resist this trend risk being left behind in the dust. But those who embrace it blindly without addressing the governance gap face a different set of dangers.
The key lies in finding the right balance — leveraging the speed and efficiency of AI-powered low-code platforms while maintaining robust governance frameworks. As Weaser puts it, "If you try to do things just purely the old way, you'll get buried."
The future of application development is not about choosing between traditional coding and AI-powered low-code platforms. It's about orchestrating both approaches within a secure, governed environment that can deliver value at the speed of business. It’s about ensuring that we build functional applications faster while also being responsible and ethical. This will matter more as the world hurtles toward Agentic AI.
Image credit: iStockphoto/master1305
Winston Thomas
Winston Thomas is the editor-in-chief of CDOTrends. He likes to piece together the weird and wondering tech puzzle for readers and identify groundbreaking business models led by tech while waiting for the singularity.