Ask HN: Where is the programming profession going?

This, to me, is the biggest differentiator. In terms of results, there's a huge yawning chasm between the person who says "Claude make me a $thing" versus the person who puts in the effort to lay down the overall architecture, gives some thoughts to libraries and dependencies, performance trade-offs etc, and only then begins prompting.

Knowing how to implement Djikstra or a linked list by heart is no longer important. Actual software engineering skills are more important than ever.

I haven't worked at a startup in over a decade, but the stories I hear now sound the same as back then. There's lots of wasted effort for mediocre to poor code destined to be rewritten or thrown away until there's enough investment to justify more work. At which point, "more work" just means more sprawling slop instead of fixing the technical debt rotting at the foundation.

AI just put a spotlight on the futility of trying to run before you can walk. Whether so many founders are going to stay in denial about it is yet to be seen. Statistics about any line of business says yes. This is how most businesses fail and most of them have to fail.

To the extent that it gets fixed or works at all, it's not because of competent developers doing rigorous analysis of the software, it's because either someone testing it or using it gets annoyed, reports an issue, and then that specific issue gets patched out.

If using LLMs to perform a similar function shocks you, then you should have been shocked already by the proliferation of pretty bad software for the better part of the last couple of decades.

So many criticisms of LLMs assume that people have been writing software very diligently, applying a high standard of engineering, subjecting the code to a battery of rigorous tests, passing it through a strict review process... and that does happen for some software, especially software that is commonly used, but it's not true for the vast majority of software developed.

Understanding the problem and the existing system well enough to design the right solution, even with AI assistance, is a higher cognitive load. I’m doing a lot more of that lately.

I’m more productive, but also more tired. This may be due in part to the breadth of what my team owns, which makes my day a bit more context-switchy than other teams.

As others in this thread have noted, the situation is still evolving. However, I worry less each day about being replaced by AI. There has always been more work than available bandwidth in my experience.

What seems clear to me is that expectations around velocity and throughput will increase (are increasing). AI use will be required to meet those expectations. Learning to use this new tool effectively will be essential for career progression (and preservation).