AI Trends
AI makes building software easy, but a good idea remains the real difference
Job van den Berg
February 28, 2026
3
min read
Especially now that almost anyone can build, it's more important that you have a really good idea
There is a lot of talk about how AI makes building software accessible, and that's right, because where you used to depend on developers, budgets and long journeys, you can now set up a working application yourself within a short time with tools such as Claude Code, Lovable and other AI platforms. You describe what you want, who it's intended for and how it should work, and the AI then generates the code and helps you get to a first version step by step. As a result, the technical threshold has been drastically lowered and the step from idea to prototype is smaller than ever.
But it is precisely because building has become easier that something else is becoming visible again: a good idea and a deep understanding of the underlying business problem are unchanged scarce and unchanged determine success. For a long time, technology was the limiting factor; many good ideas failed because the implementation was complex or expensive. Now that this limitation is largely removed, it appears that execution was never the real distinguishing feature. The difference still lies in the ability to clearly define a problem, to understand where processes crash, where there is customer frustration and where existing solutions fall short.
AI can write code, but it cannot independently experience how inefficient a logistics process feels in practice, how cumbersome healthcare administration works, or how a financial system delays decisions. This insight comes from years of involvement in a sector, through discussions with customers, errors and improvements in practice. Without that insight, AI will primarily become an accelerator of mediocre ideas: although many new tools are appearing, few solutions that really make a difference.
Especially now that almost everyone can build, the importance of direction is increasing. Creating an application is no longer the challenge; deciding what to build and why is. A good idea is not an empty idea, but the result of looking closely at a concrete business issue, understanding what interests are at stake, knowing where value is being created and where money is earned or lost. If you have that clear, you can use AI as a powerful performer. Those who don't have that are mainly building something that works technically but adds little business value.
So the real shift is not that technology has become unimportant, but that insight is once again key. AI democratizes implementation, but the ability to recognize a relevant problem and formulate a thoughtful solution remains the scarcest capital. And that is exactly why a good idea, rooted in a deep understanding of the business problem, remains the decisive factor.
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