In discussions around AI-assisted programming with LLMs, I often see two opposing camps . And since the release of Astra, it's become even more obvious...

On one hand, there's the idea that code is becoming just an implementation detail: you write the specs , add some tests, and let the models do the heavy lifting.

On the other hand, some argue we still need to scrutinize every single line , or even avoid these tools entirely to keep true mastery over our software.

I might be forcing the trait a bit, sure. But not by much. Just scroll through tech X or LinkedIn, and you'll inevitably run into these two takes in the comment sections.

This tension raises an important question:

What shape should our code take so that we can confidently delegate more of the writing process, while still actually understanding it?

Basically: can we split the difference?…