Manual Aspire

If only all documentation was as great as this old manual for the ZX Spectrum that Remy uncovered:

The manual is an instruction book on how to program the Spectrum. It’s a full book, with detailed directions and information on how the machine works, how the programming language works, includes human readable sentences explaining logic and even goes so far as touching on what hex values perform which assembly functions.

When we talk about things being “inspiring”, it’s rarely in regards to computer manuals. But, damn, if this isn’t inspiring!

This book stirs a passion inside of me that tells me that I can make something new from an existing thing. It reminds me of the 80s Lego boxes: unlike today’s Lego, the back of a Lego box would include pictures of creations that you could make with your Lego set. It didn’t include any instructions to do so, but it always made me think to myself: “I can make something more with these bricks”.

Manual Aspire

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HTML Is Actually a Programming Language. Fight Me | WIRED

When haters deny HTML’s status as a programming language, they’re showing they don’t understand what a language really is. Language is not instructing an interlocutor what to do in a way that leaves no room for other interpretations; it is better and richer than that. Like human language, HTML is conversational. It is remarkably adept at adapting to context. It can take a different shape on any machine, from a desktop browser or an e-reader screen to a mobile app or a screen reader for the blind (so long as that device is built to present hypertext).

Hell, yeah!

Ultimately, even as HTML has become the province of professionals, it cannot be gatekept. This is what makes so many programmers so anxious about the web, and sometimes pathetically desperate to maintain the all-too-real walls they’ve erected between software engineers and web developers.

Hell, yeeeeaaaaahhh!!!

What other programmers might say dismissively is something HTML lovers embrace: Anyone can do it. Whether we’re using complex frameworks or very simple tools, HTML’s promise is that we can build, make, code, and do anything we want.

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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.

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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.

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Beginner JavaScript Notes - Wes Bos

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

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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.

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