A Commentary On GenAI Inspected Through Different Lenses

Rapid adoption of generative AI in software engineering, arguing that it undermines code quality, developer ownership, and craftsmanship by encouraging the acceptance of "slop" code. The author analyzes GenAI from four perspectives—software engineer, teacher, creativity researcher, and concerned civilian—and warns that it shifts developers from creators to quality control overseers, leading to burnout and loss of pride in work. The piece concludes that humans, as *Homo Faber*, desire to build and take responsibility for their creations, a value rejected by the open source community's stance against AI-generated code.

The amount of concerning reports related to generative AI is rising at an alrming rate, yet all we do is make ourselves more dependent on the brand new technology. Why? It’s not just that we’re lazy—we are —there are many more variables involved. As part of my quest to try and understand what the heck is going on and what is becoming of one of my prime professional fields: software engineering, I read and read and read. And then I read and read and read. And then I became disappointed and depressed. I see colleagues jumping the gun, others being more prudent. I see industry discovering there’s yet another buck to be made. I see students forgoing learning at all. I wanted to try to form my own judgement of genAI in its modern form by looking at it from four different viewpoints: that of the software engineer, that of the teacher, that of the creativity researcher, and that of the concerned civilian living in this capitalist world.. References can be found at the end of this article. Does anyone remember Dan North’s Programming is not a craft post from 2011? I do, and I often think about it. With the advent of genAI, North’s port might be even more polarising: Well, congrats to you, you’ve won the lottery: here’s a tool that immediately can add customer value. If you don’t care about the inner code quality, you can have genAI generate slop code faster than you can think. If you love the impact of software itself, you’ll love Claude Code et al. Are you perhaps an enterprise software engineer? In that case you’ll be able to scaffold and generate CRUD crap even faster, hooray But wait a minute. You obviously won’t take true ownership of this code: you’ll want to impress your clients with the results, but keep the lid closed at all times. The less ownership and feeling of responsibility, the easier it comes to completely let go of all the breaks and just accept any future changes without code reviewing at all. People who are now claiming they will keep themselves in the loop as an architectural reviewer don’t need to lie to themselves. After the nth time pressing the green button, and as the technology further evolves, you’ll wind up eventually accepting the slop anyway. Verification burnout will pop up next: because it’s not your own code you’re attempting to so carefully review, it actually takes more instead of less effort, increasing your stress level instead of reducing it Does the code quality really matter if all clients see is the end product? As a gamer, I just want the game to run smoothly, I don’t care about the spaghetti. Or do I? I do, implicitly—the more spaghetti, the less smoothly it’ll run. The more holes, the more soft locks and crashes. So programming might or might not be a craft, but as Cal Newport and Robert M. Pirsig say: the concept of Quality is important Maybe it’s time to become a goose farmer instead. The only thing left for you to do is to move to a depressing quality control position instead of crafting something yourself. No more “I built this”, but “I managed its orchestration”. Depending on how you view this, It’s either a promotion or demotion. I tend to agree with the latter. Why? Because we humans are the Homo Faber, the ones who like to control their fate and environment with the use of tools. Yes, genAI certainly is a tool, but it’s a tool that takes away all other tools. Instead of kneading dough by hand, feeling it, knowing when to ferment and when to bake, we’re forced to oversee the industrial Wonder Bread production process. Instead of manipulating leather to create a pair of shoes, we’re being employed by Nike to watch shoes being made by machines. This somehow reminds me of David Graeber’s bullshit jobs where useless paper pushing is prevalent but also called a “revolution” when it comes to a professional purpose. I beg to differ. Humans want to make things. They want to be proud of the things they made. The fact that the open source community rejects this slop code is a telling sign: if you’re programming in the open, your peers who also think highly of software development will keep you in check. But when it’s “for enterprise work”, we don’t care, generate away, I’m not the true owner anyway. If programming is a craft, then the recently leaked Claude Code CLI source code will be a big joke to you, where constructs are endlessly repeated, and spaghetti is topped up with more spaghetti. Code that is being generated doesn’t even seem to be made to be re read: how then, are we expecting to maintain it, or guarantee its security? By letting the agent maintain it and guarantee its security, I can hear you say? What is there left to say? I’ve already asserted that genAI tools are worse than Stack Overflow. Sure, mindless copy-pasting has long existed before this AI storm, but not on this scale. GenAI is able to provide a working solution to an assignment faster than I can come op with the assignment itself. Suddenly, all our traditional evaluation systems and grading workflows became useless: scoring high on a checklist is just a matter of pasting the requirements into Claude. We try to adapt by requiring oral defences, having students explain what they did and why, and asking them to walk us through a small imaginative change. The result is a spectacular fall in grades from previous years: they are just not able 1 to explain the code they did not make but generated and 2 to make small adjustments as they skipped the hard part: the learning and understanding. Yet in the hallways, I hear lots of students bragging to each other about how they let ChatGPT do their homework. Congrats. We’ll see each other again in September for your second try. We often forget something else very important: peer pressure. About a year ago, on the train I overheard a few girls on their way to a university lecture chatting about their homework. One of them complained: “I put in all that hard work, but all the others are just using ChatGPT to do it. Next time, I’m not doing all that, I’m also just using AI, that’s not fair ”. I should have gotten up to congratulate her: the only one actively learning is the one putting in the hard work There is no shortcut to becoming proficient. There is only hard work. Sure, the more you prompt your way through your curriculum, the more proficient you’ll become with the tool, but ask yourself: did you learn what you wanted to learn or did you learn to prompt? When I was an undergraduate, I used to fill A4 pages with summaries of courses to help me study. Just before the exams, I could quickly glance over these pages to remembers the core concepts. Some students sold their summaries to others. Now, genAI can generate summaries for you. But smart students will know this will only fool yourself: the purpose of the summaries is to make them: to study and gradually fill the pages. Not to acquire a summary. The journey is the destination. When my summaries were done, I could just as well throw them away: they were just a tool to help with the hard work. Yet it’s next to impossible to explain this to a student who only sees how easy it is to jump to an outcome by leveraging AI. Maybe legislation will help here? Not really; see below In case all this is not clear: students are becoming dumber yet the programming projects they hand in are becoming better than ever. As the inventor of the framework presented in The Creative Programmer, I thought it would be interesting to take a look at the seven domains and how genAI fits in these. In The Creative Programmer, I present seven distinct but heavily intertwined themes that define the way we are creative when we solve a programming problem: I might be overly focusing on the negative here and have to recognise the possible advantages of having genAI as a tool available in our creative toolbox—but only when we learn to yield it properly and with moderation, which is not exactly what we are doing lately, is it. In an interesting systematic literature review 2025 with lots of references to other academic material if that’s what you’re looking for, Holzner et al. conclude with: … human-GenAI collaboration shows small but consistent gains in creative output across tasks and contexts. However, collaboration with GenAI reduces the diversity of ideas, indicating a risk of creative outputs that could become more homogeneous. More same-ness; exactly what we need when it comes to creativity, right? The more we use genAI, the more creatively we will be able to prompt, but the less creative we will be in actually applying a solution to the problem. We no longer create: we generate. We know that genAI will do everything in its power to keep you locked within that chat box. Its tendency to talk to your mouth, agree with your statements, and serve you whatever you want to hear creates biases and dependencies. It’s not unlike a drug that slowly but surely diminished your critical thinking, and thus, creativity. Don’t take my word for it; read it for yourself: experiments with almost 1,300 subjects and found that in 80% of the cases when participants chose to consult ChatGPT, they went with wrong answers without stopping to scrutinize them. … Decision-makers overrely on AI advice in that they follow it even when said advice contradicts available context information. This is where the true nature of humans are unfolded: when it comes to earning something for themselves, ethics suddenly becomes a very malleable subject. On the morality, ethics, and privacy, everyone agrees that genAI is what Ron Gilbert calls a train wreck. This bears no further explanation from me: Microsoft slurped all GitHub repositories dry without taking any licenses into account, the book that I painstakingly produced in almost two years was ingested OpenAI’s systems in about two seconds, … Yet at the same time, everyone also consistently ignores all these topics in favour of their own self-interest. Why, I wonder? Everyone knows they should eat less meat. Yet almost nobody does. Everyone knows Microsoft and probably other big tech companies power genocide yet the adoption rate of Windows as an OS is still 95%. Why? Everyone knows the climate is going to shits yet we happily turn the other way and take the plane on a weekend trip to sip some wine and do some shopping in Italy. As Gretea Thunberg said: knowing is not enough. For GenAI, similar patterns emerge. We know it’s bad for us, yet we happily close our eyes and use it anyway. Why, I wonder? The power of a drug, the pull, the ease at which something can be done without breaking too much sweat? Here’s a possible answer I suggested before: because humans are inherently lazy. As long as Belgian supermarkets keep on stocking apples from New Zealand and Belgium, most people won’t care and just pick up whatever. As long as we keep handing out company cars and making infrastructure geared towards car drivers, most people will be driving to work instead of biking. A possible answer to the problem then might be governmental legislation to protect people living in a society from making the wrong choices. And I’m 100% sure that will work Yet legislation is always 1 either happening way too late; or 2 minimised or manipulated by the people who wield the power because they have bought out key politicians to prevent laws like this from happening. Hence my depression. In the case of GenAI, a technology that evolves at lightning speed and is taking the world by storm, legislation will be way too late. To prove my point, in an attempt to modernise, many Belgian governmental instances already “embraced” the technology and made many blunders in doing so. The EU is currently evaluating the options. Meanwhile, the San Francisco bros are laughing. Prompt engineering is the most degenerative thing that ever happened to engineering. It’s a capitalist’s way to minimise the cost of the human. Yet I don’t see genAI disappearing any time soon. Companies and decision makers smelled