Setbacks

In the mid-eighties, I was very excited about the potential of computers. Little personal computers were disrupting those massive, expensive beasts lurking in basements. It seemed like computers could integrate into our daily lives, change the world, and make it better.

Computer Science and Informatics were having a heyday; innovation was overflowing. There seemed to be monthly progress.

But over the decades, that progress was plagued by some pretty bad setbacks.

The first one I really saw was the rise of Microsoft.

They had been the David that took down the IBM Goliath, but the moment that they got traction, they got nasty. Over and over again we’d watch as some small group of people would labour to prove some new innovative technology was viable. But just before they could stabilize, Microsoft would swoop in with an army of kids and eat their business.

I was horrified, often quite angry. Instead of software progressing, any new buds were quickly snuffed out by products of far lesser quality, but way more senseless features. Microsoft then applied the rest of its growing monopoly to crush these small competitors.

Just before this era, the heart of innovation had shifted from academics into a small group of energetic people trying to get established. They had good intentions. Mostly these were wiped out. Innovation quickly died as a result; it was too risky, and after all that pain you’d just lose anyway.

That only changed when the next setback took hold.

The Internet had been around for a while, but the Web on top exploded into a huge bubble.

On the plus side, it brought most consumers to software, but it also embraced chaos. If Microsoft killed innovation, the Web killed quality. Whacking out crude software at high speeds was favoured. The ideas shifted from helping people to just exploiting them. The product was no longer software, but a cut of the money, control over people and surveillance. Software was created as fast and crude.

In a quick tumble, we switched from empathy to pure snake oil. If you could trick a million or more people into your broken product, you were famous.

Almost as a counter to the corruption of the Web, mobile apps nearly reversed that trend. For a while, but then everyone else took a page from the Microsoft warbook and quickly bought or crushed anything even mildly innovative or decent quality.

As the mobile dust settled, another setback had been quietly brewing since the dotcom bomb took hold.

Forget quality and innovation, Agile preached mindless coding at high speed.

If you just grind out enough code this week for whatever reactive drama was dominating, the belief was that your chaos would somehow converge into something useful. That lack of direction and foresight was misguided. You can’t randomly build an apartment building; it would obviously collapse, so why would people think that might work for any large technology structure?

Instead of learning from the mistakes of the past, the software industry doubled down on its madness.

Innovative sites vanished, replaced by grungy interfaces that only captured sellable data. People seem to just adjust to a steady flow of disruptive bugs. Using computers got insanely complicated, buttressed by a flood of questionable how-to pages.

Instead of software becoming more intuitive, people just followed opaque, incoherent recipes as if they were magic spells. This produced a mountain of incomprehensible code piled high on mountains of incomprehensible code. It kinda worked, but only if you stayed very close to the magic recipes. Deviate even a little bit at your own risk. Underlying knowledge of how things worked got decimated.

For a while there, it seemed like we’d finally get enough breathing room to be able to fix the industry’s problems. Maybe this time we’d be able to figure out how to build stuff that isn’t crap, but then LLMs appeared, and it started all over again.

Now we live in an era where we are totally dependent on the messes we’ve created but no longer understand. No longer just a house of cards, we suffer from skyscrapers of cards.

And a new generation of people thinks, again, that doubling down on our lack of understanding and handling that over to random traversals of illegally compiled huge lumps of questionable data will fix our problems. But it’s really just another repeat of the same mistakes.

We keep getting distracted from trying to actually figure out how to engineer massive systems that are both reliable and trustworthy. So long as we keep avoiding that, we’ll keep tumbling over the cliffs.