Absolutely lovely article.
> Software development is about translating a problem into a solution that a computer can understand and automatically resolve. Preferably in a secure and scalable way.
True, meanwhile software engineering puts optional bit into the requirements bucket. (ie. Secure & Scalable)
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For the problem description and gathering requirements sentiment; I don't think we'll _ever_ have a 100% proper way of doing this. If we did, we'd basically solve any and all problems in the world.
Nevertheless, I think AI can help with investigating and exploring the problem space. Especially when the problem is an already solved thing that the prompter hasn't gained enough expertise yet.
Moreover, I think (and keep mentioning) we will see different kind of models in the near future. Those would be more specialized per industry, per language (both programming and human languages), even per field.
Those will open up newer areas for employment & job market. Something like an "AI-trainer" but more of a knowledge-worker style. Although this can also be automated with LLMs, the limits on context length/size plus amount of compute required to re-train the models to iterate faster both are quite heavy.
That last paragraph sounds like a meta vp explaining to the engineers why it is important to log all their keystrokes and eye movements. Pinky promise we wont fire you.
The trend I DO see at least based on JDs is a whole lots of “agents” which are glorified claude code but in the cloud with tools focus on a given industry or domain. If this is what you mean, then you are correct.