More and more people are saying that you can now build products without writing code.
That statement is not wrong, but it is often presented as if the hard part has already disappeared.
What really matters is not whether AI can produce code. What matters is whether you can take a vague goal and turn it into a clear sequence of steps.
Many projects fail for reasons that have little to do with raw model strength:
- the scope was never defined
- the minimum viable version was never identified
- the validation method was never designed
These problems stay the same no matter which model you use.
That is why, in our work, AI automation is never treated as a slogan. It has to stay tied to requirement analysis, process design, and implementation planning.
If you already have an idea in mind, the best first step is usually not asking a model to build a system for you. The better first step is to make the business goal clear.