You can discover why applications built with AI-assisted and low-code platforms often stall before production.
Low-code and AI-assisted platforms promise speed and simplicity, but real-world deployments reveal recurring challenges. This whitepaper explores the most common pitfalls and explains why human expertise is essential to push the applications.
The objective of this whitepaper is to critically examine the limitations and recurring problems in applications generated using low-code and AI-assisted platforms such as Replit, Lovable, and Base44. While these platforms accelerate prototyping and reduce entry barriers, they often produce applications that struggle with scalability, maintainability, security, and user experience.
Identify the most common technical and design challenges encountered in AI-generated applications and platforms.
Highlight the gaps that automated platforms cannot fully address, particularly in production environments.
Demonstrate the indispensable role of human developers in refining, debugging, and ensuring compliance.
Provide actionable recommendations for organizations to balance automation with human expertise.
The top technical limitations of Replit, Lovable, and Base44-generated apps
Why scalability and performance bottlenecks emerge in production
Hidden security and compliance risks that automated tools miss
How UX and design flaws impact adoption
The critical role of human developers in debugging, refining, and productionizing apps
Get practical insights and actionable strategies to ensure your AI-assisted applications succeed in real-world environments.
