What we learned testing multiple no-code AI platforms on real client projects

The promise being sold everywhere: just chat with an AI agent and it will build a robust application to solve your business problems. 

The reality? It’s not quite there yet. 

You might get simple sites or basic apps, but anything requiring complex logic and system integrations still needs people with actual coding skills.

There’s massive hype around codeless development and dramatically increased development speed. After implementing and testing multiple platforms on real projects, here’s what we found: no-code tools excel at rapid prototyping and connecting services together. 

We built a framework for a complex workflow with a simple interface in just 2 days to demonstrate a solution concept. But converting that proof-of-concept into a robust, properly tested system? That took 2 months, which is about a third to a half the time it used to take a couple of years back without the AI assist. 

The AI got us started fast, but human expertise finished the job.

Breaking down the development process reveals where AI actually helps: Business analysis and solution architecture benefit from AI assistance, but you still need significant time gathering specifications and ensuring architectural soundness. Coding itself is genuinely faster with AI tools. Testing and client feedback? That takes the same time it always has – because humans still need to verify that solutions actually work in real business conditions.

AI accelerates development, but it doesn’t eliminate the need for skilled implementation. The tools are getting better rapidly, but for now, the magic is in combining AI speed with human expertise.

What’s been your experience with AI development tools? Have you found similar gaps between the marketing promises and practical results?