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Discussion (23 Comments)Read Original on HackerNews
I wish David the best with his new teaching direction. And I hope David will find a practical way to make these courses available for self-study.
Personally, I'm finding this kind of story lately shocking and heartbreaking.
Funny enough, a few months ago we decided to start a new project and we chose async Python. I had no clue how'd work so I decided to read the PEP and learn a bit more. Big was my surprise when I realized I "knew" all the fundamentals just by understanding how coroutines and generators worked low level, thanks to David's talks.
EDIT: His talks about the GIL are also super informative!
He's long been a fabulous teacher to adults; kids will be lucky to have him.
Best wishes to him going forward.
You start to see patterns that let you understand what input leads to what output, and so to organize your actions in a way that will generate preferred outcomes.
Will change back in 12 - 24 months.
People still learn math, despite the calculator existing. Accounts still learn accounting, despite Excel and accounting software existing.
If/when it does change in 12-24 months, I think companies need to take a serious look at the people in these “leadership” positions. If the quality of their thinking on big things like this is that bad, and so easily swayed by marketing and hype, then they don’t seem qualified for the positions they’re in.
They do, but you need far fewer or none of the original workers whose full-time job this sort of stuff was.
Raw math does not matter, but what you do with it. Similarly, you could earn a (modest) living knowing nothing but raw HTML, JavaScript and a bit of browser tech not too long ago. That is no longer possible.
Programming and software engineering will be devalued. These occupations won't disappear overnight, but you will see compensation and growth stagnate until equilibrium is reached again. Currently, supply outstrips demand, and I do think it is structural, not just hype.
I'm certainly not creative enough, but I currently do not see demand picking up sufficiently; Gen Z is bearish on social media, VR was a bust, blockchain was a bust, software has already penetrated almost all walks of live and lines of work. There is no next big thing (Internet, ...) on the horizon, to unlock the next order of magnitude of demand. There is certainly more work to do still, but it very suddenly does not require the same headcount, but something like 5%-30% less. Lots of the remaining work will be around integrating LLMs into existing software, which does not sound exciting either.
It's getting quite exhausting having to endure all these major events of the 21st century and their consequences - 9/11 and the Iraq war, the 2008 financial crisis, covid-19, and now AI.
But I guess it's better than all out war and conquest as was with most of human history.
The reason is simple: AI only gives you the information it deems necessary and semantically related to your prompt. But humans don't just dig into local details—they give you a broader map. That's what a curriculum does, in a sense.
In that regard, I think human education will shift toward cultivating macro-level insight and perspective.
p.s I'm really amazed that you're the author of the IPython Cookbook. I found that book incredibly useful. The fact that I was able to work as an assistant to data scientists was also based on what I learned from that book. I'm personally a fan of yours, so it's surprising to see you here
What I’ve found is that in the instances where I want to learn, ai teaches me now.
What I agree with is that things will come back around in 12 to 24 months.
What I don't agree with is that I also consider this to be AI.
In fact, when you use AI, the stratification of input is very clear. In the end, even in software engineering, the quality of what AI produces depends heavily on how you prompt it. And there's no way around it—AI will inevitably do better than most people. It's pointless to say to an encyclopedia, 'I know more than you.' For a human to beat AI, the only way is to dig deeper into the latest technologies, but that's something only scholars who are up to date with cutting-edge academic trends can do. Most ordinary people won't be able to win against it.
However, I think software engineering will continue to exist. The reason is the stratification of input. In the end, software skills might become something like a subset selection technique for prompting within a specific domain.