Did AI Kill Low-Code Platforms?

For years, low-code iPaaS platforms promised a revolution: fast implementation, citizen development by non techies, and seamless integration. Platforms like Boomi, Lobster, and MS LogicApps were heralded as the key to empowering non-developers and accelerating digital transformation. However, as AI-powered development tools evolve, the low-code promise is beginning to falter. 

Rising costs, vendor lock-in, and scalability limitations are forcing companies to reconsider their options. Could AI-assisted coding on open-source platforms and cloud functions be the better alternative?

Low-code platforms market themselves as the bridge between business and IT. They offer drag-and-drop interfaces, pre-built connectors, and visual workflows that enable rapid application development. The idea is that business users can build solutions with minimal developer involvement, reducing IT bottlenecks and accelerating digital initiatives. 

However, reality often falls short of the promise. As highlighted in Martin Fowler’s article, “You Can’t Buy Integration”, pre-packaged solutions often fail to handle real-world complexity. Many low-code platforms struggle with: 

• Rising Costs: Licensing fees for low-code platforms have skyrocketed, especially as businesses scale. What starts as an affordable entry-level solution can quickly become a major expense. 
• Vendor Lock-In: Once applications and integrations are built on a low-code platform, migrating away can be extremely difficult. Businesses find themselves tied to specific ecosystems, limiting flexibility and innovation. 
• Customization Challenges: While low-code enables rapid prototyping, it often lacks the depth needed for complex workflows. Companies frequently hit roadblocks where custom coding is required - negating the original speed advantage. 
• Integration Limitations: Many low-code platforms offer built-in connectors, but as Fowler points out, integration is more than just connecting systems. True integration requires adaptability, which low-code platforms often struggle with. Even more, when the connector fails, it is often a black box that is difficult to troubleshoot.

Enter AI-driven development. With generative AI and automated code assistants, developers can now achieve the same—if not better—speed as low-code platforms without the associated downsides. How? 

• AI Handles the Heavy Lifting: Tools like GitHub Copilot, ChatGPT, and cloud-based AI services can generate boilerplate code, suggest optimizations, and even write complex functions, significantly reducing development time. Especially Claude.AI is right now our favorite AI to help building integrations and the platform engineering around it. 
• Open-Source Freedom: Instead of being tied to a single vendor’s platform, companies can leverage open-source frameworks or cloud-native functions (e.g., AWS Lambda, Azure Functions, Google Cloud Functions) for full control over their solutions. The point is to build the integrations in languages like Java, .Net or other languages than can run anywhere – even in your own container orchestration platforms like Kubernetes or OpenShift, which run on your chosen cloud infrastructure. 
• Lower Costs: Without expensive licensing fees, businesses can allocate resources more efficiently. Cloud-based pay-as-you-go models and open-source tools drastically reduce financial overhead. One key point is, if it still were true that you could build faster and cheaper using low code what good is that if the solution you build will run unaltered for a long time. Build cheap and run expensive – that does not compute 😊 
• True Integration: AI-powered code can be tailored to specific needs, ensuring better long-term maintainability and interoperability compared to rigid low-code connectors.

Low-code platforms aren’t dead, but they are losing their edge. Businesses looking for speed, flexibility, and cost-efficiency should increasingly turn to AI-assisted coding rather than proprietary low-code solutions. The future belongs to those who combine AI automation with open-source or cloud-native pro-code architectures, freeing themselves from vendor lock-in and unlocking true innovation. 

The question isn’t whether AI killed low-code platforms—it’s whether businesses are ready to embrace the next evolution in software development.