Manual Aspire

Generative AI Is Not Going To Build Your Engineering Team For You - Stack Overflow

People act like writing code is the hard part of software. It is not. It never has been, it never will be. Writing code is the easiest part of software engineering, and it’s getting easier by the day. The hard parts are what you do with that code—operating it, understanding it, extending it, and governing it over its entire lifecycle.

The present wave of generative AI tools has done a lot to help us generate lots of code, very fast. The easy parts are becoming even easier, at a truly remarkable pace. But it has not done a thing to aid in the work of managing, understanding, or operating that code. If anything, it has only made the hard jobs harder.

AI isn’t the app, it’s the UI - Stack Overflow Blog

In some ways, the fervor around AI is reminiscent of blockchain hype, which has steadily cooled since its 2021 peak. In almost all cases, blockchain technology serves no purpose but to make software slower, more difficult to fix, and a bigger target for scammers. AI isn’t nearly as frivolous—it has several novel use cases—but many are rightly wary of the resemblance. And there are concerns to be had; AI bears the deceptive appearance of a free lunch and, predictably, has non-obvious downsides that some founders and VCs will insist on learning the hard way.

This is a good level-headed overview of how generative language model tools work.

If something can be reduced to patterns, however elaborate they may be, AI can probably mimic it. That’s what AI does. That’s the whole story.

There’s very practical advice on deciding where and when these tools make sense:

The sweet spot for AI is a context where its choices are limited, transparent, and safe. We should be giving it an API, not an output box.

Beginner JavaScript Notes - Wes Bos

A very handy collection of organised notes on all things JavaScript.

Let’s Not Dumb Down the History of Computer Science | Opinion | Communications of the ACM

I don’t think I agree with Don Knuth’s argument here from a 2014 lecture, but I do like how he sets out his table:

Why do I, as a scientist, get so much out of reading the history of science? Let me count the ways:

1. To understand the process of discovery—not so much what was discovered, but how it was discovered.
2. To understand the process of failure.
3. To celebrate the contributions of many cultures.
4. Telling historical stories is the best way to teach.
5. To learn how to cope with life.
6. To become more familiar with the world, and to know how science fits into the overall history of mankind.

Pseudo Code | CSS-Tricks

I find myself doing pseudo code before I write real code, sure, but I also leave it in place sometimes in code comments.

Same!