LLMs, Dread, and Good Enough Software (Fast and Cheap)
June 11, 2025
Just a dinobaby and no AI: How horrible an approach?
More philosopher programmers have grabbed a keyboard and loosed their inner Plato. A good example is the essay “AI: Accelerated Incompetence” by Doug Slater. I have a hypothesis about this embrace of epistemological excitement, but that will appear at the end of this dinobaby post.
The write up posits:
In software engineering, over-reliance on LLMs accelerates incompetence. LLMs can’t replace human critical thinking.
The driver of the essay is that some believe that programmers should use outputs from large language models to generate software. Doug does not focus on Google and Microsoft. Both companies are convinced that smart software can write good enough code. (Good enough is the new standard of excellence at many firms, including the high-flying, thin-air breathing Googlers and Softies.)
The write up identifies three beliefs, memes, or MBAisms about this use of LLMs. These are:
- LLMs are my friend. Actually LLMs are part of a push to get more from humanoids involved in things technical. For a believer, time is gained using LLMs. To a person with actual knowledge, LLMs create work in order to catch errors.
- Humans are unnecessary. This is the goal of the bean counter. The goal of the human is to deliver something that works (mostly). The CFO is supposed to reduce costs and deliver (real or spreadsheet fantasy) profits. Humans, at least for now, are needed when creating software. Programmers know how to do something and usually demonstrate “nuance”; that is, intuitive actions and thoughts.
- LLMs can do what humans do, especially programmers and probably other technical professionals. As evidence of doing what humans do, the anecdote about the robot dog attacking its owner illustrates that smart software has some glitches. Hallucinations? Yep, those too.
The wrap up to the essay states:
If you had hoped that AI would launch your engineering career to the next level, be warned that it could do the opposite. LLMs can accelerate incompetence. If you’re a skilled, experienced engineer and you fear that AI will make you unemployable, adopt a more nuanced view. LLMs can’t replace human engineering. The business allure of AI is reduced costs through commoditized engineering, but just like offshore engineering talent brings forth mixed fruit, LLMs fall short and open risks. The AI hype cycle will eventually peak10. Companies which overuse AI now will inherit a long tail of costs, and they’ll either pivot or go extinct.
As a philosophical essay crafted by a programmer, I think the write up is very good. If I were teaching again, I would award the essay an A minus. I would suggest some concrete examples like “Google suggests gluing cheese on pizza”, for instance.
Now what’s the motivation for the write up. My hypothesis is that some professional developers have a Spidey sense that the diffident financial professional will license smart software and fire humanoids who write code. Is this a prudent decision? For the bean counter, it is self preservation. He or she does not want to be sent to find a future elsewhere. For the programmer, the drum beat of efficiency and the fife of cost reduction are now loud enough to leak through noise reduction head phones. Plato did not have an LLM, and he hallucinated with the chairs and rear view mirror metaphors.
Stephen E Arnold, June 11, 2025
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