How Development Teams Are Rethinking the Way They Build Software

Zdravko Kolev, Manager of Product Development at Infragistics, explains why AI is forcing development teams to rethink their approach to software development. This article originally appeared in Insight Jam, an enterprise IT community that enables human conversation on AI.

A revolution is underway in software development, driven by the emergence of low-code/no-code platforms and the integration of AI. The aim of coding solutions is not to replace developers, but to make them more productive by handling mundane tasks, allowing them to focus on higher-level design and innovation.

All forms of programming are likely to coexist in the near future, rather than one prevailing over the others. Traditional programming will remain for intricate systems, while low-code/no-code and AI will address different needs. As the role of AI continues to expand, we will observe how this technology changes development mindsets and roles, with developers transitioning into “prompt engineers” who guide AI to produce the desired code output.

Exploring Programming Paradigms

In a nutshell, low-code and no-code platforms allow for the creation of software applications with minimal coding knowledge. Low-code no-code software uses visual interfaces, drag-and-drop components, and pre-built templates. These platforms democratize app development, enabling non-programmers, or citizen developers, to build applications faster and more efficiently. At the same time, C-level executives, development team leaders, and enterprise architects can focus on digital innovation, achieving a faster time-to-market. There are tools like Google Forms for simple data collection, as well as platforms like WordPress, Shopify, and App Builder for more complex solutions.

Currently, 7 in 10 developers (71.8 percent) are using low-code/no-code tools, and 90.4 percent of developers report that low-code tools are boosting developer productivity in their organization, according to a recent App Builder survey. Moreover, according to Gartner, “by 2025, 70 percent of new applications developed by organizations will use low-code or no-code technologies, up from less than 25 percent in 2020.” Meaning that low-code/no-code tools are here to stay.

AI’s Role in Programming

AI in programming enables the generation and review of code based on natural language prompts, potentially reducing the time to market for new software. Unlike the deterministic models of the low-code/no-code approach, AI can produce variable outputs, which might require more oversight for consistency. AI programming can also enhance productivity by handling repetitive tasks and providing quick solutions for prototyping or small-scale applications.

However, there is a risk of poor quality when integrating AI capabilities into common and already determined workflows. Additionally, if AI capabilities are not properly managed by skilled developers, the result could be subpar performance or low-quality outcomes.  For example, AI-generated code may not capture the full context of a large, complex system because it lacks a comprehensive understanding of the entire system, leading to integration challenges. That’s why team leaders, CTOs, CIOs, and their development teams must understand what exactly AI does so they can utilize it effectively.

According to the 2024 Stack Overflow Developer Survey, “Developers are increasingly adopting AI tools but remain skeptical about their accuracy and ability to handle complex tasks, viewing them as complementary rather than a replacement for human expertise.”

The survey found that developers learning to code (27 percent) were more uncertain about AI as a threat than seasoned coders (18 percent). Six out of 10 (62 percent) professional developers are using AI tools this year, compared to 44  percent last year. Three-quarters (76 percent) of the developers surveyed are currently using or plan to use AI tools, and 72 percent have a positive attitude towards using AI tools at work.

One of GenAI’s key promises was its ability to deliver quick solutions and speed up time-consuming processes. However, 31 percent of developers are skeptical that these tools offer accurate solutions, and 45 percent believe AI tools are not good at handling complex tasks. AI is not threatening to replace developers because it has not yet replaced humans in the development process.

Traditional Programming

Traditional programming is well-known because it has been the foundational approach to software development for decades. It involves writing code from scratch, offering the highest level of customization, and providing control over every aspect of an application, from scalability to performance.

The following development statistics illustrate the traditional development approach:

• The software development market is predicted to rise to  $858.10 billion by 2028, with a CAGR of 5.27 percent.
• About eight in ten (84.7 percent) of software development projects focus on enterprise applications.
• JavaScript is the most widely used programming language, and it is preferred by 65.82 percent of professional developers.
• About half  (54 percent) of software engineers report being more productive when working from home.
• The Internet of Things (IoT) is expected to include over 75 billion devices in 2025.
• Nearly seven in ten (69 percent) of businesses have adopted cloud computing technology.
• Approximately 15 percent of businesses utilize third-party modern frameworks, such as Ignite UI for Angular, which provide pre-built, high-performance UI components. These components simplify complex development tasks while still allowing developers the flexibility and control they need to customize applications according to their specific requirements.

The events here are likely to occur as low-code tools, such as App Builder, AI agents, and models, grow in popularity and traditional programming becomes relegated to complex, large-scale systems that require fine-tuned performance or meet specific technical requirements.

The Business Advantages and Challenges of Each Paradigm

There are three core pillars to examine when evaluating the business advantages and challenges of each software development paradigm: time to market, customization vs complexity, and skill evolution.

Time to Market

According to the App Builder’s survey, a majority (43.5 percent) of developers save up to 50  percent of their time when they use low-code tools on a project. This enables rapid prototyping and deployment, particularly for simpler applications.

When to use each method for rapid deployment:

• Low/No-Code: Ideal for businesses needing rapid deployment of simple to moderately complex apps where customization isn’t critical.
• Traditional Programming: Best for highly customized, complex systems where performance and scalability are paramount.
• AI: Useful for both prototyping and enhancing productivity in existing workflows, especially for junior developers learning best practices.

Customization vs. Complexity

While low-code/no-code platforms accelerate development, they can become challenging when trying to achieve high levels of customization or when dealing with complex systems. Custom solutions might be more cost-effective for highly specialized applications. Low-code and no-code platforms must provide clear guidance to users within a structured framework to minimize mistakes, and they may offer less flexibility compared to traditional coding.

AI tools can be easily used to generate code, suggest optimizations, or even create entire applications based on natural language prompts. However, they work best when integrated into a broader development ecosystem, not as standalone solutions.

Skill Evolution

Low-code/no-code tools help bridge the gap in skilled labor but can also lead to over-reliance. Developers will need to adapt, focusing not just on coding but also on managing low-code and AI tools and understanding how to best “prompt” them for desired outcomes. For novice developers, exposure to all these technologies is beneficial. However, it’s strongly recommended to gain hands-on coding experience before relying too much on AI or no-code/low-code solutions. Understanding the fundamentals is key to using advanced tools effectively. New developers should engage with code manually to understand its mechanics before moving to automated or visual tools.

How the App Development Sector Will Adjust to Current Trends

The future of software development appears to be a blended approach, where traditional programming, low-code/no-code platforms, and AI each play a role. The key to success in this dynamic landscape is understanding when to use each method, ensuring C-level executives, team leaders, and team members are versatile and leverage technology to enhance, rather than replace, human ingenuity.

Let me share my firsthand experience. When I asked my developers a year ago how they thought using AI tools at work would evolve, many said: “I expect that as the tools improve, I’ll shift from mostly writing code to mostly reviewing AI-generated code.” Fast forward a year, and when we posed the same question, a common theme emerged: “We are spending less time writing the mundane stuff.”

My goal is to emphasize the shift toward more inclusive development environments while also highlighting the need for in-depth technical skills to manage these systems effectively. As AI and low-code/no-code tools evolve, so must developers. Adaptation to new ways of creating software is what drives business growth, workflow efficiency, and innovation.