When Anyone Can Build Software, Who Decides What Not to Build?
Generative AI has made software generation cheap, but the real bottleneck is no longer building—it's deciding what deserves to become permanent. Drawing on twenty years of experience, the author argues that enterprise architecture's enduring value lies in judgment before commitment: the ability to see across domains and arbitrate before capital, data, and organizational behavior lock in. As production costs fall, incoherence becomes more expensive, and the scarce input is coherent decision-making.
The cheaper software becomes to create, the more expensive incoherence becomes.
- deminature
Building quality software with LLMs is still very time-consuming. The vast majority of people are not going to bother, regardless of how low the bar to entry is, because time is not free. That and making software is not interesting to most people, for the same reason assembling electronics is not interesting to most people. It's a niche interest with limited mass appeal. For those two reasons, the software profession will survive AI.
- OakNinja
This problem is not new. The new thing is that anyone can understand the core problem they’re trying to solve without involving a dev team by quick ideation and rapid prototyping.
Just as always, it’s then up to the company to prioritize what to focus on - Just like how it’s always been.
* Don't hold onto an idea or prompt output just because you spent time on it.
* Writing code is easy. Maintaining it is hard.
* If it doesn’t save time or generate revenue, it’s just an expense.
* Output does not equal value.
- CurleighBraces
I feel it's more nuanced than this, at least for now.
It's true to say anyone can build software, but that doesn't make the software good and it's not true to say that's specifically reliant on taste.
As an example I am working with an Entrepreneur right now who has no coding experience but have successfully made a product which they have also already sold to a mid sized company.
However without my involvement and knowing the right levers to craft the AI the software just wasn't performing how it needed to despite the latest frontier models trying their hardest to achieve what he was stating.
At least for now there's still a need for experienced devs.