We Are the Last People Who Know How It Works

The issue with this is that we don't know how it works. Generally speaking, we know how the level of abstraction that we were born with works. We might have some understanding of one or two previous levels, but that decreases the farther down you go. We might understand the next level, and some of the next after that, but eventually people will be making things that we don't have the context to understand without having to unlearn a lot of what we know now. I'm old enough to see this process in action; I used to be young and in possession of esoteric knowledge that made me infinitely in demand and now most of the things that young people have esoteric knowledge about is things that I don't particularly care about, and I'm left with a lot of finely honed skills to solve problems that have mostly been abstracted away.

It is no small feat to put in words that we are losing something almost as quickly as we are gaining something. The undertone, despite leaning into nostalgia boils down to losing control and this uneasiness I feel growing daily. It is already shocking to a certain degree seeing very young people not being able to use a computer in the narrow sense because all they ever learned was touch interfaces and apps. Curated content, curated interfaces - everything that resembles some kind of hardship ironed out in thousand steps of iterations to appease the market which means the lowest common denominator. But I also see that the people who can create the absolute most and the good things and the working things and the maintainable things nowadays are the people that have gained a tool, but not lost the knowledge of the medium we are using it on because we are tied to this old world so perfectly put under the spotlight in this blog post.

There was a sweet spot with computer technologies for some decades where hobbyists could afford to experiment and even push the envelope in the nascent field of computing - similar to genetic radiation, many niches were formed and rapidly filled. The computing biome has evolved to the point where most entities are not operating at the low-level abstractions that were once the only means of interacting with the computing environment, instead they operate now at the highest levels of abstraction we are capable, so called "natural language". "The difficulty was the knowledge. You came to know that machine the way you come to know anything that pushes back. The resistance was the whole medium. You only ever know the things that you can lose to." We who grew up in this era formed a hands-on engineer's knowledge of these systems, built from experience and practice, learning these layers of abstraction as the bleeding edge developed. Many these days have entered into a world where there are easy answers abound, they just might not be right, and one has to gauge how much they care about correctness.

I'm one of the greybeards who has the 2400 BAUD modem negotiation tone sequences emblazened in my neurons. For a while I've been meaning to set up some Wireguard connections among some of my systems. Being as busy as I am with work and family, I've relinquished that to Tailscale for now. Sure, I could have sat down and jumped through the hoops to get everything set up and working across my various hosts, including network routes, firewall rules, key pairs, systemd units, and so forth. But the "cheap and easy" alternative was right there and worked (except when it forces re-authentication). With LLM agents, I was able to effortlessly analyze my existing network and produce tailored scripts to do precisely what I wanted. All I had to do was review the scripts for potential security issues and what not. Looking at the script, there are 3 or 4 specific tweaks that needed to be made to my network routing rules given my network topology. I could have read a few man pages and iterated on the script by hand to eventually get there after maybe an hour or two of futzing. The availability and effectiveness of the agents is simply too tempting for me. I'm not sure what this means about my skillset, or if that even matters any more. I am fairly confident that, so long as my brain still works well enough, I'll always be able to RTFM and figure things like this out myself. At this rate I wonder whether my kids will have the same ability. And I also wonder how much that will matter. Regardless, I'm still helping them figure things out the "old way" without over-reliance on LLMs. One thing I'm fairly certain about is that failure to develop problem-solving skills can only put them in a worse position in life, no matter how capable AI becomes.

“The knowledge is not in danger, in fact, it has never been safer. The AI models have read every manual that no human reads.” I disagree. If you ask a model for a manual and it regurgitates that manual from its training data, it’s over-fitted. It will regurgitate something that looks like a training manual. Or whatever fits your query about training manuals. You still have to push back on them sometimes when you spot an error. And you can only spot them if you already know what you’re looking for and should expect. Otherwise you have to ignore the output and just get the links which… could be outdated or made up as well. You’ll never know until you verify the results. And this degrades with compression and time. There’s no royal road. I agree that trying and getting frustrated and having to take the effort to understand something pays off in spades. I just think it’s still worth it and vastly under appreciated in this era of “everything fast, now.”