My Article on Why AI Is Great (or Terrible) or How to Use It

What if I have a block of marble and a vision for the statue struggling from inside it and I use an industrial CNC lathe to do my marble carving for me. Have I sculpted something? Am I an artist?

What if I'm an architect? Brunelleschi didn't personally lay all the bricks for his famous dome in Florence --- is it not architecture? Is it not art?

Some people find software architecture and systems thinking more fun than coding. Some people find conducting more fun than playing an instrument. It's not too mysterious.

Indeed, of all the possible things to say!

AI "development" /is/ wrestling the computer. It is the opposite of the old-fashioned kind of development where the computer does exactly what you told it to. To get an AI to actually do what I want and nothing else is an incredibly painful, repetitive, confrontational process.

I don't care if you use AI but leave me alone. I'm plenty fast without it and enjoy the process this author callously calls "wrestling with computers."

Of course this isn't going to help with the whole "making me fast at things I don't know" but that's another can of worms.

I think it’s a bit like a gambling addiction. I’m riding high the few times it pays off, but most of the time it feels like it’s just on the edge of paying off (working) and surely the next prompt will push it over the edge.

It's like the articles point: we don't do assembly anymore and no one considers gcc to be controversial and no one today says "if you think gcc is fun I will never understand you, real programming is assembly, that's the fun part"

You are doing different things and exercising different skillsets when you use agents. People enjoy different aspects of programming, of building. My job is easier, I'm not sad about that I am very grateful.

Do you resent folks like us that do find it fun? Do you consider us "lesser" because we use coding agents? ("the same as saying you’re really into painting but you’re not really into the brush aspect so you pay someone to paint what you describe. That’s not doing, it’s commissioning.") <- I don't really care if you consider this "true" painting or not, I wanted a painting and now I have a painting. Call me whatever you want!

You're never really wrestling the computer. You're typically wrestling with the design choices and technological debt of decisions that were in hindsight bad ones. And it's always in hindsight, at the time those decision always seem smart.

Like with the rise of frameworks, and abstractions who is actually doing anything with actual computation?

Most of the time it's wasting time learning some bs framework or implementing some other poorly designed system that some engineer that no longer works at the company created. In fact the entire industry is basically just one poorly designed system with technological debt that grows increasingly burdensome year by year.

It's very rarely about actual programming or actual computation or even "engineering". But usually just one giant kludge pile.

Well, I'll have to take their word for it that they're passionate about maximizing shareholder value by improving key performance indicators, I know I personally didn't sign up for being in meetings all day to leverage cross functional synergies with the goal of increasing user retention in sales funnels, or something along those lines.

I'm not passionate about either that or mandatory HR training videos.

Creating software has a similar number of steps. AI tools now make some of them much (much) easier/optional.

You've got a good analogy there though, because many great and/or famous painters have used teams of apprentices to produce the work that bears their names.

I'm reminded also of chefs and sous-chefs, and of Harlan Mill's famous "chief surgeon plus assistants" model of software development (https://en.wikipedia.org/wiki/Chief_programmer_team). The difference, of course, being that the "assistants" in the current moment are mechanical ones.

(as for how fun this is or isn't - personally I can't tell yet. I don't enjoy the writing part as much - I'd rather write code than write prompts - but then I again, I don't enjoy writing grunt code, boilerplate, etc., and there's less of that now, - and I don't enjoy having to learn tedious details of some tech I'm not actually interested in in order to get an auxiliary feature that I want, and there's orders of magnitude less of that now, and then there are the projects and programs that simply would never exist at all if not for this new mechanical help in the earliest stages, and that's fun - it's a lot of variables to add up and it's all in flux. Like the French Revolution, it's too soon to tell! - https://quoteinvestigator.com/2025/04/02/early-tell/)

The “lone genius” image is largely a modern romantic invention.

I have found in my software writing experience that the majority of what I want to write is boiler plate with small modifications but most of the problems are insanely hard to diagnose edge cases and I have absolutely no desire nor is it a good use of time in my opinion to deal with structural issues in things that I do not control.

The vast majority of code you do not control because you aren’t the owner of the framework or library your language or whatever and so the Bass majority of software engineering is coming up with solutions to foundational problems of the tools you’re using

The idea that this is the only true type of software engineering is absurd

True software engineering is systems, control and integration engineering.

What I find absolutely annoying is that there’s this rejection of the highest level Hofstetter level of software architecture and engineering

This is basically sneered at over the idea of “I’m gonna go and try to figure out some memory management module because AMD didn’t invest in additional SOC for the problems that I have because they’re optimized for some Business goals.”

It’s frankly junior level thinking

Programming a system at a low-level from scratch is fun. Getting CSS to look right under a bunch of edge cases - I won't judge that programmer too harshly for consulting the text machine.

This is especially true considering it's these shallow but trivia-dominated tasks which are the least fun and also which LLMs are the most effective at accomplishing.

AI is more fun for programmers that should've gone into management instead, and prefer having to explain things in painstaking detail in text, rather than use code. In other words, AI is for people that don't like programming that much.

Why would you even automate the most fun part of this job? As a freelance consultant, I'd rather have a machine to automate the whole boring business side so I could just sit in front of my computer and write stuff with my own hands.

I am happy to accept that some people still prefer to write out their code by hand… that’s ok? Keep doing it if you want! But I would ask yourself why you are so offended by people that would prefer to automate much of that, because you seem to be offended. Or am I misreading your intention?

And hey, I still enjoy solving interesting problems with code. I did advent of code this year with no LLM assistance and it was great fun. But most professional software development doesn’t have that novelty value where you get to think about algorithms and combinatorical puzzles and graphs and so on.

Before anyone says it, sure, there is a discussion to be had about AI code quality and the negative effects of all this. A bad engineer can use it to ship slop to production. Nobody is denying that. But I think that’s a separate set of questions.

Finally, I’m not sure painting is the best analogy. Most of us are not creating works of high art here. It’s a job, to make things for people to use, more akin to building houses than painting the Sistine Chapel.

I've coded professionally for 30 years (ergh!). I'm ok at it.

But I love building things with AI. I haven't had this much fun since the early 2000s.

I like this. I'm going to see if my boss will go for me changing my title from Solutions Architect to Solutions Commissioner. I'll insist people refer to me as "Commissioner ajcp"

At home, I never had the time/will to be as thorough. Too many other things to do in life. Pre-LLMs, most of my personal scripts are just - messy.

One of the nice things with LLM assisted coding is that it almost always:

1. Gives my program a nice interface/UI

2. Puts good print/log statements

3. Writes tests (although this is a hit or miss).

Most of the time it does it without being asked.

And it turns out, these are motivation multipliers. When developing something, if it gives me good logs, and has a good UI, I'm more likely to spend time developing it further. Hence, coding is now more joyful.

And it turns out, these tend to

Development is solely to exchange labor for money.

I haven’t written a single line of code “for fun” since 1992. I did it for my degree between 1992-1996 while having fun in college and after that depending on my stage in life, dating, hanging out with friends, teaching fitness classes and doing monthly charity races with friends, spending time with my wife and (step)kids, and now enjoying traveling with my wife and friends, and still exercising

In b4 someone mentions some famous artists had apprentices under them.

But we are, even as of Opus 4.5, so wildly far away from what the author is suggesting. FWIW my experience is working in the AI/ML space at a major tech company and as a maintainer + contributor of several OSS projects.

People are blindly trusting LLMs and generating mountains of slop. And the slop compounds.

Why not output everything in C and ASM for 500x performance? Why use high level languages meant to be easier for humans? Why not go right to the metal?

If anyone's ever tried this, it's clear why: AI is terrible at C and ASM. But that cuts into what AI is at its core: It's not actual programming, it's mechanical reproduction.

Which means its incapabilities in C and ASM don't disappear when using it for higher-level languages. They're still there, just temporarily smoothed over due to larger datasets.

At work the projects are huge (200+ large projects in various languages, C#, TypeScript front-end libs, Python, Redis, AWS, Azure, SQL, all sorts of things).

AI can go into huge codebases perfectly fine and get a root cause + fix in minutes - you just need to know how to use it properly.

Personally I do "recon" before I send it off into the field by creating a markdown document explaining the issue, the files involved, and any "gotchas" it may encounter.

It's exactly the same as I would do with another senior software engineer. They need that information to figure out what is going on.

And with that? They will hand you back a markdown document with a Root Cause Analysis, identify potential fixes, and explain why.

It works amazingly well if you work with it as a peer.

Apparently, so do humans.

Recent manager quote from a CRUD shop: "I don't understand why you are so negative on AI. As far as I can tell, AI is better than our Hyderabad team, I don't have to manage it, and it's in my time zone to boot."

I was agog.

> If you can't see this, I have to seriously question your competence as an engineer in the first place tbh.

I can't agree more strongly. I work with a number of folks who say concerning things along the lines of what you describe above (or just slightly less strong). The trust in a system that is not fully trustworthy is really shocking, but it only seems to come from a particular kind of person. It's hard to describe, but I'd describe it as: people that are less concerned with the contents of the code versus the behaviour of the program. It's a strange dichotomy, and surprising every time.

I mean, if you don't get the economics of a reasonably factored codebase vs one that's full of hacks and architecturally terrible compromises - you're in for a VERY bad time. Perhaps even a company-ending bad time. I've seen that happen in the old days, and I expect we're in the midst of seeing a giant wave of failures due to unsustainably maintained codebases. But we probably won't be able to tell, startups have been mostly failing the entire time.

And I asked codex to fix them for me, first attempt was to add comments to disable the rules for the whole file and just mark everything as any.

Second attempt was to disable the rules in the eslint config.

It does the same with tests it will happily create a work around to avoid the issue rather than fix the issue.

Embedded in this, is the assumption that many SWEs can actually do those roles better than existing specialists.

If they can't - end of the line

This simply is a mediocre take, sometimes I feel like people never actually coded at all to have such opinions

You're what, 250 years behind at this point?

Since the dawn of the industrial revolution there is a general trend that fewer can make more with less. And really even bigger than AI were fast fuel based transportation and then global networks. Long before we started worrying about genAI, businesses have been consolidating down to a few corporations that make enough to supply the world from a singular large factories.

We fought the war against companies. Companies won.

Now you're just at the point where the fabric makers were, where the man with the pick axe was, where the telephone switch operator was, where the punch card operator was.

Few thoughts here.

Experience helps you "check" faster that what you asked for is actually what was delivered. You "know" what to check for. You know what a happy path is, and where it might fail. You're more likely to test outside the happy path. You've seen dozens of failure modes already, you know where to look for.

Experience also allows you to better define stuff. If you see that the output is mangled, you can make an educated guess that it's from css. And you can tell the model to check the css integration.

Experience gives you faster/better error parsing. You've seen thousands of them already. You probably know what the error means. You can c/p the error but you can also "guide" the model with something like "check that x is done before y". And so on.

Last, but not least, the "experience" in actually using the tools gives you a better understanding of their capabilities and failure modes. You learn where you can let it vibe away, or where you need to specify more stuff. You get a feeling for what it did from a quick glance. You learn when to prompt more and where to go with generic stuff like "fix this".