Low-Code, No-Code Platforms Fail When It’s Time to Scale

With tools like Cursor, Claude, and ChatGPT canvas are on the boom, allowing users to build software using natural language, it feels highly reminiscent of the times when LC/NC platforms also lowered the barrier to entry for app development and made it easier for companies to teach their developers the existing solutions within the companies.

The community is now questioning the relevance of low-code/no-code (LC/NC) platforms in the AI era. How do these platforms continue to stay relevant in a landscape dominated by artificial intelligence?

While these tools were a great choice for prototyping an idea or starting a project, LC/NC platforms are a nightmare when considering scaling a project, which seems to be the same for modern AI coding tools. Not much has changed.

Amidst the challenges and shift towards AI coding tools, is there still a role for low-code, no-code platforms, like Bubble and Webflow, in today’s landscape, and are they able to coexist with emerging AI solutions?

No code is dead

Relevance of LC/NC Tools in the AI Era

According to a Reddit user, even when he got help from AI to write a custom function for the no-code platform, it failed terribly. Two days later, he started writing the code himself and it worked out pretty well.

“When building an app you want to own with popular low-code/no-code platforms, even if they mention that you legally own an IP to your app, what meaning does it hold if you cannot run it on-premise?” Andreas Møller, the co-founder of toddle, told AIM. This seems to be a common reason why the adoption of low-code no-code platforms took some time.

We witness the same with AI tools, given the hallucinations and other privacy issues. But in certain cases, they are able to do the job a lot quicker than any no-code platforms that ever existed.

For example, Meghana Jagadeesh, the founder & CEO of GoCodeo, mentioned at Cypher 2024 that LC/NC tools will still be relevant and will grow in the future, but with an AI twist in them.

“When AI capabilities are added to LC/NC platforms, it gets easier for non-tech guys to build specific functions. These tools are a great choice to get started before scaling it for a large user base,” she said, suggesting that we should not confuse LC/NC tools with traditional development as they cater to different user needs.

“If you don’t have Git, a version-controlling system, I’m obviously not going to build a big project on your platform. That is a deal breaker for every developer,” said Møller while explaining why it is necessary for every developer to have a version-control system to build a SaaS application.

Due to these issues, we saw companies like Klarna drop solutions built on top of LC/NC platforms and create in-house solutions using AI for better scalability and profit.

This is the reason we are seeing tools like toddle and Apptile, which are a little different from the traditional LC/NC platforms. Samyam Annappa, founder and CTO at Apptile, told AIM that coding typically makes up less than 25% of the total project cost. Most of the time goes into setting up the infrastructure—analytics pipelines, payment gateways, notifications, device testing, and managing both iOS and Android versions.

“That is where tools like Apptile simplify this by taking care of the heavy lifting behind the scenes. Additionally, our architecture supports real-time content updates, unlike tools like Cursor, which necessitate code changes, App Store reviews, and App Store rejection handling for content updates,” he added, further suggesting that to stay relevant in the AI era, LC/NC platforms must overcome traditional issues and offer streamlined solutions.

Similarly to Apptile, tools like toddle, which is not entirely an LC/NC platform but something in between LC/NC and traditional platforms, allows users to build specific functions and host your infrastructure, and has plans to go open source by the end of 2025, so you can actually own your software.

Will LLMs replace LC/NC Platforms?

LC/NC platforms have to adapt to the changes all developers are going through – the AI change. Jinen Dedhia, the founder of DronaHQ mentioned on HackerNews that he also believes that LLMs can remove the need for LC/NC platforms and the only way to stay relevant is to tightly integrate AI capabilities to LC/NC platforms.

“But I do see the merit in this thinking that LLMs can eat LCNC platforms for breakfast. However, I am excited to see how with time near perfect applications can be churned out with about 80-90% work done and engineers can figure the last few miles and reach the finish line but 50x faster,” he added further.

In fact, the LC/NC platforms produce very well-structured code behind the scenes and they can train LLMs to build apps following their well defined structure, which means their apps can still take advantage of the LLMs but will have less bugs than just letting the LLMs produce a stand-alone app.

While LC/NC platforms may provide a simplified interface for creating applications, they do not eliminate the need for a foundational understanding of programming concepts, same as the AI tools like Cursor, ChatGPT, or GitHub Copilot.

Of course, the LLMs can produce more versatile apps than LC/NC platforms but considering LLMs as a competitor to LC/NC platforms might not be a correct idea.

The post Low-Code, No-Code Platforms Fail When It’s Time to Scale appeared first on AIM.

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