AI For The Skeptics: The Universal Function For Some Things Only

It’s a phrase we use a lot in our community, “Drink the Kool-Aid”, meaning becoming unreasonably infatuated with a dubious idea, technology, or company. It has its origins in 1960s psychedelia, but given that it’s popularly associated with the mass suicide of the followers of Jim Jones in Guyana, perhaps we should find something else. In the sense we use it though, it has been flowing liberally of late with respect to AI, and the hype surrounding it. This series has attempted to peer behind that hype, first by examining the motives behind all that metaphorical Kool-Aid drinking, and then by demonstrating a simple example where the technology does something useful that’s hard to do another way. In that last piece we touched upon perhaps the thing that Hackaday readers should find most interesting, we saw the LLM’s possibility as a universal API for useful functions.

It’s Not What An LLM Can Make, It’s What It Can Do

When we program, we use functions all the time. In most programming languages they are built into the language or they can be user-defined. They encapsulate a piece of code that does something, so it can be repeatedly called. Life without them on an 8-bit microcomputer was painful, with many GOTO statements required to make something similar happen. It’s no accident then that when looking at an LLM as a sentiment analysis tool in the previous article I used a function GetSentimentAnalysis(subject,text) to describe what I wanted to do. The LLM’s processing capacity was a good fit to my task in hand, so I used it as the engine behind my function, taking a piece of text and a subject, and returning an integer representing sentiment. The word “do” encapsulates the point of this article, that maybe the hype has got it wrong in being all about what an LLM can make. Instead it should be all about what it canĀ do. The people thinking they’ve struck gold because they can churn out content slop or make it send emails are missing this. Continue reading “AI For The Skeptics: The Universal Function For Some Things Only”

AI For The Skeptics: Attempting To Do Something Useful With It

There are some subjects as a writer in which you know they need to be written, but at the same time you feel it necessary to steel yourself for the inevitable barrage of criticism once your work reaches its audience. Of these the latest is AI, or more specifically the current enthusiasm for Large Language Models, or LLMs. On one side we have the people who’ve drunk a little too much of the Kool-Aid and are frankly a bit annoying on the subject, while on the other we have those who are infuriated by the technology. Given the tide of low quality AI slop to be found online, we can see the latter group’s point.

This is the second in what may become an occasional series looking at the subject from the perspective of wanting to find the useful stuff behind the hype; what is likely to fall by the wayside, and what as yet unheard of applications will turn this thing into something more useful than a slop machine or an agent that might occasionally automate some of your tasks correctly. In the previous article I examined the motivation of that annoying Guy In A Suit who many of us will have encountered who wants to use AI for everything because it’s shiny and new, while in this one I’ll try to do something useful with it myself.

Continue reading “AI For The Skeptics: Attempting To Do Something Useful With It”

AI For The Skeptics: Pick Your Reasons To Be Excited

It’s odd being a technology writer in 2026, because around you are many people who will tell you that your craft is outdated. Like the manufacturers of buggy-whips at the turn of the twentieth century, the automobile (in the form of large language model AI) is on the market, and your business will soon be an anachronism. Adapt or go extinct, they tell you. It’s an argument I’ve found myself facing a few times over the last year in my wandering existence, and it’s forced me to think about it. What are the reasons everyone is excited about AI and are those reasons valid, what is there to be scared of, and what are the real reasons people should be excited about it?

If We Gotta Take This Seriously, How Can We Do It?

A couple in a horse drawn buggy, circa 1900ish
The futures looking bright in the buggy-whip department! Public domain.

I’ll start by repeating my tale from a few weeks ago when I asked readers what AI applications would survive when the hype is over. The reaction of a friend with decades of software experience on trying an AI coding helper stuck with me; she referenced her grandfather who had been born in rural America in the closing years of the nineteenth century, and recalled him describing the first time he saw an automobile. I agree with her that this has the potential to be a transformative technology, and while it’s entertaining to make fun of its shortcomings as I did three years ago when the idea of what we now call vibe coding first appeared, it’s already making itself useful in some applications. Simply dismissing it is no longer appropriate, but equally, drinking freely of the Kool-Aid seems like joining yet another hype bandwagon that will inevitably derail. A middle way has to be found. Continue reading “AI For The Skeptics: Pick Your Reasons To Be Excited”