I'm excited to read the first cogent piece making this point that doesn't devolve to gatekeeping, a detached and vaguely hostile professional software developer telling people with a newfound capability to solve practical problems for themselves with new software that they don't or shouldn't want the thing that they want, because whatever it is they come up with won't be "fit for purpose" until blessed by the guild, which has bylaws extrapolated from Brooks about the fundamental "limitations of LLMs".

I think you've misread the article, specifically the purpose of the Brooks quotes. They're clearly not to denigrate anyone for wanting a more useful or convenient way of generating software--they're specifically about the "LLMs will obliterate software engineering as a profession" claims put forth by many LLM marketers. In fact, Brooks is never once mentioned in the "Power to the people?" section of the essay.

Generally, the whole point of the "Power to the people?" (and to some extent the "On being left behind") section(s) is to underscore the two antithetical claims made by many LLM marketers: 1. LLMs are so powerful and so natural and easy that someone with no experience can create amazing software, and 2. LLM usage is a core skill, one that if you don't begin training now you'll be left behind.

Obviously, both of these can't be simultaneously 100% true--either it's easy enough for the non-programming layperson to successfully generate software for an intentional purpose, or, LLM assisted programming is a skill you need to train to avoid professional obsolescence in modern society. So, the article disagrees with the majority of both claims, and accepts a weakened/minor portion of each: 1. LLM output is easy to generate but accurate prompting matters, and 2. when used for software development professionally, some amount of skilled human intervention does indeed seem necessary. And now these two claims do align.

However, if professional software engineers who work with and read code constantly, armed with the best software practices to aid LLMs we can determine, cannot use modern AI tools without shooting their feet off at relatively frequent rates, certainly you'd expect the layperson who must put an even greater amount of undue faith in the validity of the results to be at extremely high-risk of foot-shooting. It's not "gatekeeping" to forewarn people against unwarranted trust in LLM output, nor is it "gatekeeping" to suggest that modern tech communicators/marketers describing an overly flowery LLM tooling landscape might be doing people a disservice.

I am less sure about his argument about democratising software indeed. The only problem in my own life that I solve with software is a problem of getting paid, so what do I know. If someone can generate a piece of code for their needs, and they don't risk harming anyone but themselves, then it's a great application of LLMs.

The unfortunate reality is that a lot of software does have hard constraints. And a lot of these constraints are "gatekept" by regulators, compliance policies, insurance companies, etc. If someone slops together a medical record system, and leaks a bunch of PHI, there will be consequences, even in the US. Similarly, good luck getting insurance against cyber attacks without a SOC2 audit or equivalent.

I've had this conversation with managers in multiple organizations this year: "Yes, you could totally vibe code that instead of paying for a SaaS. But you have strict contractual and professional obligations about data security. Do you want to be deposed and asked, 'So, did you really just vibe code the system that led to the data leak? Did the vibe coders have any professional qualifications? Did they even look at the code?'"

Similarly, a backend server that handles 8 million users a day is expected to stay up.

Now, there are 10,000 things that have less demanding requirements. I'm actually really delighted that people are able to vibe code their own tools with minimal knowledge of software engineering! We have been chronically underproducing niche software all along.

But if your software already has on-call shifts (and SLAs, etc) like the GP, then I think you want to be smart about how you combine human expertise with LLMs.

Nailed it