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2/19/2025 In this article we break down why low-code no longer works, how AI changed the market and what it means for developers.
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Four years ago, low-code was a trend in the IT industry and helped develop integrations quickly through ESB buses.
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But the world is changing, and AI is taking over development.
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According to the 2024 Menlo Ventures report, writing code is the most popular use of AI. And GitHub reports that 92% of US developers already use AI in their work.
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AI's popularity is easy to explain: it takes over the routine and frees up time for important tasks — for example, strategic meetups and finding new solutions for projects. In this article we'll discuss whether AI has really displaced the low-code concept, how it affects the development process and whether there's a risk of being left without a job in the future.
Low-code is dead: how the world of IT development has changed
How AI is reshaping low-code and IT development, automating routine work, and changing the roles of developers.
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- What Happened to the Low-Code Concept
- What changed when AI entered development
- Is AI dangerous for developers
What Happened to the Low-Code Concept
We defended low-code platforms for a long time: we wrote articles, addressed objections and misconceptions. The reason was simple: low-code used to help businesses because it simplified and stabilized development through ready-made templates and built-in integrations.
However, years later it became clear that the concept has problems: — the number of integrations only grows — which means the time spent building and reworking them grows too; — juniors take a long time to train so they can understand existing integrations and build something on their own without errors; — seniors burn out on repetitive tasks — simply "maintaining" old integrations is a fairly monotonous and dull thing.
What changed when AI entered development
So, integrations grew, routine tasks did not decrease, and simply clicking something together on a low-code platform is no longer a solution. That is when AI entered development. Here is what made its use appealing to IT specialists.
AI writes code faster than a human
How a developer solves a task: opens StackOverflow and GitHub, writes code, edits it, tests it, and only then deploys it. This usually takes hours or even days. AI performs the same tasks in seconds: on request it analyzes thousands of repositories, makes corrections, and delivers a finished result. GitHub even ran an experiment: it split developers into two groups, asked them to write an HTTP server in JavaScript, and timed them. One group used AI, while the other did everything on its own.
The result: developers assisted by AI completed the task 55% faster.
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AI assembles front-end files faster than a human
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Take the AI tool Bolt as an example.
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It can not only generate code but also assemble front-end files on its own.
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A task like this takes it ten minutes, while a human developer needs a couple of days at best.
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What's more, you can work in Bolt right from the browser. ESB buses are already embedding AI assistants into their tools. For example: the integration platforms Mendix, Milesoft, or Apache Camel.
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The trend for the coming year is obvious: developers will have to learn to use AI assistants, just as they once had to learn to use low-code tools and GitHub.
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If you fail to do this, you risk being left behind.
AI has a positive impact on developer productivity
The DORA.dev team ran a survey and found that more than 75% of developers are more productive when they use AI assistance. The GitHub team got almost identical results. In their study, most developers reported feeling more productive, getting distracted less, and solving tasks faster.
Is AI dangerous for developers
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Moreover, developers will not lose their jobs or disappear, because: — code is not just lines, but logic; — AI does not know the business context, it only generates solutions; — it is the developer who is responsible for the code logic and the business context.
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In other words, as long as the developer's main job is to think, there's no danger. AI will remain a useful tool that takes control of routine and monotonous tasks. And now for the "but" — the fly in the ointment.
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If a developer can't generate ideas and think ahead, if they're used to only handling small tasks — AI will outperform them.
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Simply because it handles the day-to-day grind faster.
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A company is better off with AI that writes the code in two minutes than with a developer who spends two days on it and can do nothing else.
Key takeaways
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A few years ago, low-code platforms sped up integration development, but over time the volume of routine tasks grew.
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A need arose for a new tool that would do all the same things, only better.
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That tool turned out to be AI. AI works on the same principles as real people, but does it faster.
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This lets developers focus on more interesting tasks, feel more productive, and avoid burning out from the amount of routine work.
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The business wins too: strong specialists stay, and the budget is spent more efficiently.
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If you want to achieve the same results as in this article, get in touch — we will teach you how to build integrations with AI.
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