Designing products by intent, not code

In "The Basics of Vibe Engineering," explore how to build innovative products without diving into coding.

2 min readTowards Data Science
Designing products by intent, not code

The idea of "vibe engineering", building products without writing code, sounds like a contradiction, but it points toward a real and practical shift. We think it captures something essential: the separation of intent from implementation. For too long, the barrier between wanting to build something and actually building it has been technical skill. That barrier is finally thinning.

What this means in practice is that the act of designing a product is no longer synonymous with the act of coding it. You can describe what you want, set the parameters, and let the system handle the construction. This is framed as "building products without the coding part," and we agree with the sentiment, though we would add a nuance: you still need to know what you want. The hard work shifts from syntax to specification. Instead of wrestling with a programming language, you wrestle with your own clarity of purpose. That is a trade worth making.

For the spreadsheet user, this is familiar territory. Traditional spreadsheets already let you define logic without writing software, formulas are a kind of intent. But vibe engineering takes that further. It means you can describe a workflow, a calculation, or a data transformation in natural language, and the tool interprets and executes it. The result is a product built by your intention, not by your ability to remember a function name or debug a macro. The human-centered promise here is real: more people can build what they need, faster, and with less friction.

We see this as a natural evolution, not a revolution. The tools we use should adapt to how we think, not the other way around. The challenge for builders and users alike is to stay disciplined about what we actually want to accomplish, because the ease of expression can also lead to sloppy thinking. But that is a problem worth having. The concrete point is this: when intent becomes the primary input, the quality of the output depends on how well you understand your own problem. That is a skill worth investing in.

From Towards Data Science

Building products without the coding part

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