Essential Skills for Low-Code Developers in 2025

Low-code development is reshaping how software is built. To thrive in 2025, developers need to master these key skills:

• AI Integration: Learn to embed AI tools like ChatGPT and machine learning models for automation and analytics.

• Platform Migration: Gain expertise in transitioning between platforms like Mendix and OutSystems to keep up with evolving technologies.

• Industry-Specific Development: Tailor low-code solutions for sectors like healthcare, manufacturing, and finance.

• Modern Architectures: Embrace serverless computing, microservices, and blockchain for scalable and secure applications.

Quick Overview

These skills are critical as 75% of new apps will use low-code tools by 2026. Start integrating AI, practicing migrations, and specializing in industry solutions to stay ahead.

7 Best Low Code Development Platforms 2025

Working with AI in Low-Code

Developers working in low-code environments need to stay ahead of the curve when it comes to using AI tools. These tools are now a core part of low-code platforms, driving automation and analytics. In fact, a recent study found that over 87% of IT professionals and CIOs believe that adding AI and automation to low-code platforms boosts development efficiency [3].

AI Tools in Low-Code Platforms

Today's low-code platforms come equipped with advanced AI features designed to simplify development. For example, Walmart uses Microsoft's Power Platform to integrate AI-powered image recognition for real-time inventory tracking [4]. Some standout AI features include:

• Natural language processing (NLP): Converts text or speech into actionable commands.

• Predictive analytics: Helps forecast trends and understand user behavior.

• Automated code generation: Handles repetitive coding tasks.

• Performance optimization: Detects and resolves bottlenecks in applications.

These tools also make it easier to incorporate machine learning (ML) models into applications.

Adding ML Models to Applications

Low-code platforms now simplify ML integration. Take Mendix, for instance - it offers a secure, drag-and-drop feature for embedding AI models directly into applications [7].

"Mendix is the first platform that enables developers to easily drag and drop ML models into the application's logic and deploy it without the need to use an outside service." – Amir Piltan, Mendix's senior product manager for AI [7]

Similarly, OutSystems provides a ChatGPT connector that allows insurance companies to analyze uploaded policy documents and create smart policy comparison tools [5].

AI Automation Guidelines

To get the most out of AI automation, consider these strategies:

• Process Analysis: Identify repetitive tasks that could benefit from automation. For example, KPMG worked with Appian to use NLP for automating client services. Employees could even create applications using simple voice commands [4].

• Gradual Integration: Roll out AI tools step by step. Goldman Sachs took this approach for their high-frequency trading applications, which helped them quickly pinpoint and fix performance issues [4].

• Quality Controls: Monitor AI performance closely. Since nearly 90% of machine learning models never make it to production [6], pairing ML models with human oversight during early deployment is crucial.

Using pre-built connectors and integrations from your low-code platform can save time and ensure strong security and performance standards [7].

Up next, we’ll dive into migration strategies that align with these AI advancements.

Platform Migration Steps

Switching low-code platforms requires detailed planning to maintain functionality and improve performance [8].

Mendix vs. OutSystems: Platform Comparison

Mendix and OutSystems have distinct features that play a critical role in migration decisions:

Mendix emphasizes accessibility for developers, while OutSystems focuses on improving productivity. However, keep in mind that OutSystems 11 apps cannot be directly migrated to ODC - they need to be rebuilt from scratch [9].

Now that the key differences are clear, here’s how to plan your migration effectively.

Migration Planning Checklist

• Pre-Migration Assessment
  Take stock of your legacy applications and perform a SWOT analysis to ensure the migration makes sense [10].

• Technical Planning
  Create a detailed migration roadmap, breaking it down module by module. Include plans for data mapping and any necessary integrations [10].

• Risk Mitigation
  Prepare for potential issues by setting up backup and rollback strategies. As Eric Goebelbecker wisely pointed out:

  "You can't move code to a new platform if you don't know what it does" [10].

Industry-Specific Development

Siemens Manufacturing Tools

Siemens' Mendix low-code platform is designed to tackle complex challenges in manufacturing environments [12]. With its Industrial Edge Plugin for Mendix Studio Pro, developers can deploy applications directly to the Industrial Edge Environment, streamlining processes in manufacturing [11].

Here’s what makes it stand out:

Solutions by Industry

Low-code platforms are reshaping industries beyond manufacturing, offering tailored solutions for diverse needs:

• Manufacturing and Logistics
  Mercury Systems showcases how low-code enables rapid innovation. As Anu Mishra, VP of Application Engineering, explains:

  "The pace of innovation is so fast that we are now having to slow down to match the business, because that's the kind of architecture we now have in place." [14]

• Energy and Utilities
  Norsk Hydro highlights large-scale adoption of low-code, spanning various business areas:

  "We started with simple applications. Then we got another project, and then we got many projects…We now have over 70 apps running with a footprint across all Hydro business areas." [14]

These examples underline how low-code platforms are driving change across industries.

IoT and Edge Computing Setup

Successfully integrating IoT and edge computing requires a strategic approach to data management, device setup, and security. Charles Cote, Chief Architect at Capgemini North America, shares:

"Once set up in the IoT platform, end users can easily create complex scripts and processes on the managed devices without any technical knowledge – enabling faster development and more reliability from a business point of view, as it is directly developed by the business owners." [15]

Key steps include:

1. Data Management
   Use techniques like data compression and filtering to optimize bandwidth and processing. Focus on critical data points that need real-time edge processing [16].

2. Edge Device Configuration
   Ensure devices meet these requirements:

   • Enough computational power for local tasks

   • Adequate memory and storage

   • Compatible operating systems

   • Reliable network connections

3. Security and Compliance
   Implement strong security measures across your IoT network. Security, governance, and testing should be handled by skilled professionals, especially for edge applications [15].

With IoT projected to generate up to $11.1 trillion annually by 2025, developing low-code skills tailored to industry needs is more important than ever [13].

New Tools and Technologies

Serverless Low-Code Apps

Serverless architecture is changing how applications are built. Microsoft Azure highlights its impact:

"Serverless computing enables developers to build applications faster by eliminating the need for them to manage infrastructure." [18]

Platforms like AppMaster take advantage of this shift, allowing developers to create apps using modern tech stacks without worrying about infrastructure [19].

Key benefits of serverless architecture include automatic scaling, event-driven execution, and no infrastructure management. These features help reduce costs and speed up deployment:

This approach supports more modular and flexible application designs.

Microservices Development

Microservices architecture is gaining traction, with 87% of implementations achieving success [20]. Low-code platforms simplify this process by abstracting technical complexities, letting developers focus on business logic instead of repetitive integration tasks. According to Gartner, by 2026, 75% of new applications will be built using low-code tools [1].

As these platforms grow, integrating stronger security measures and data validation processes becomes increasingly important.

Blockchain Implementation

Building on serverless and microservices trends, blockchain is finding its place in low-code platforms to improve security and data integrity [17]. Features like advanced encryption, secure access controls, and real-time audit trails are critical for safeguarding applications.

For businesses, ongoing monitoring and regular security audits are essential to uncover vulnerabilities and stay compliant with data protection laws [21].

Conclusion

Skills Summary

Low-code development is advancing at a rapid pace. According to industry projections, 75% of new applications will use low-code tools by 2026 [1]. To remain competitive, developers need to focus on key skills that align with this shift:

Microsoft's study of 126,000 organizations using Copilot in Power Apps showed an 80% increase in development speed and a 65% improvement in satisfaction rates [22]. These findings highlight the value of building expertise in these areas.

Next Steps

Developers should focus on these critical skills to stay ahead. Research from McKinsey shows that combining AI with low-code development can enhance productivity by up to 45% [22].

"Low-code platforms transform software development by automating key processes." [2]

To take immediate action:

• Integrate AI into Projects: Start using tools like Microsoft Copilot in current applications to get practical experience with AI-driven development.

• Master Platform Migration: Practice moving applications between platforms like Mendix and OutSystems to understand their unique features and limitations.

• Specialize in Industry Applications: Dive into sector-specific solutions, such as Barcelona's IoT-based urban management system, which optimized traffic flow and reduced pollution through low-code technology [23].

The future of low-code development calls for a mix of technical skills and strategic insight. Staying informed and continuously learning will be crucial for success [24].