Weirdly, I thought the terms would be reversed… I think of a craftsman as someone who values quality over quantity, and makes everything beautiful and long lasting, while an engineer is more about productivity and tolerances and efficiency. A craftsman makes better quality but doesn’t scale the way an engineer and the factory process does, although mass produced goods sacrifice quality for quantity.

Engineering is about creating something that serves a purpose, while operating within a set of constraints. Part of that is realizing that "100% correct/reliable in all circumstances" is an unrealistic goal, since implementation time and cost is one of those constraints.

A good engineer will acknowledge this tradeoff between robustness and cost and behave accordingly. For example, if you're working on safety critical or very foundational systems like OSes, medical tech, etc you should bias very heavily in favor of robustness. If you're not, this can easily be an act of overengineering. The engineer's job is to find the right spot along the cost-correctness curve for the thing they are building.

This has always been true, and LLMs just change certain parts of the equation. For example, code writing is far less of a bottleneck than before, so "we can just try with a throwaway impl and see if this works" is suddenly economically viable. It also turns out that many things, in practice, don't need to be as correct as some of us may have believed.

We can still enjoy making quality things, but doing so is often an act of artisanship rather than engineering.

> Many gamers who defend artists and hate AI with a passion turn 180 once you mention software: suddenly LLM code is acceptable, and obviously everyone uses LLMs anyway, and AI disclaimers for code are unnecessary.

There is a big difference from a players point of view. Games are much more than code, and the code is a way to represent game mechanics instead of a product by itself. AI graphics and music are instantly recognizable as bad quality and uncreative but vibe coding only shows when the game is slow or has a lot of bugs. And if that happens players dont care if its AI or not, just that its broken.

Games dont really need to care about code quality as much as other projects. They dont have to constantly adapt to competition and developers never really need to update them, unless there are game breaking bugs or a critical security issue. That means they change a lot less than your average code.

Balatro is coded in a way that sometimes looks like a beginners first Lua script, even after the publisher got outside help to polish it before full release. But it still works and sold millions of copies. Games are built on design intuition and user testing, not technical quality.

For the ethical side, there is a perception that programmers are actively using AI for coding and would do it even if the publisher wasnt making them, but artists are getting fully replaced against their will. And there is clearly some truth to it because we dont see coders in game studios speaking out against it.

I agree with the title, but perhaps for different reasons.

Somewhere (maybe the 1960s?) the idea crept in that programming is some kind of production process, and the "engineering" happens upstream. Elsewhere, the line between engineering design and manufacturing is the transition of a set of documents to those with the skills to turn what those documents specify into real products in a reliable, repeatable manner. That repeatability is one of the hallmarks of manufacturing. For software, all the processes reliable enough to qualify are downstream of typing `make` and striking return, ending in the binaries and the computational processes that those paying the bills desire. It's our build and deployment tools that do the construction, which means that our source code is the final, detailed design.

A good chunk of engineering is putting together reliable systems from unreliable parts.

You build in safeguards, redundancy, defense in depth, recovery systems. You build models of the system and prove characteristics about it.

Software is fundamentally automation. LLMs enable automating the construction of software itself. They're much faster and cheaper than people, and they're more unreliable. (People are unreliable too!)

The immediate challenge of these times is figuring out how to reliably construct reliable software in the large, over the longer term, reliably. This is an engineering challenge, and the only way we'll get to the other side of it is by trying to do it. Things will be rough, there will be a Cambrian explosion of techniques, most approaches will fail, and many more won't survive as models improve on quality and capability. But we'll figure it out.

Making things by hand, as in the time before agentic coding, can be engineering too, but it is not the core challenge of these times, and it will soon be a hobby, or possibly a kind of luxury good. You will no more want hand-written software than you'll want a hand-made car. It will not have the precision, performance or reliability of machine-made software.

I prefer the term "classically trained programmer." :-)

Isn't there a difference between making things that code does and the code itself? Ive seen truly beautiful software with terrible to follow but effective code and I've seen beautiful code that while technically amazing didn't do anything of substance. Software is like woodworking, it includes all levels of care and product outcomes.

The vocabulary point matters: calling careful work artisanal turns reliability into a personal taste when it is often the core engineering requirement.

I find more pleasure and satisfaction by programming at a higher altitude, at the system level. This zooming out gives you a better feel for building an effective scaffold and you can iterate on ideas faster.

But can they compete with my shade grown software? It does result in a 40% markup, but there's no putting a price on being raised in a loving environment, is there.

Thank you for sharing this. This is a concern many of us had — I sure did — but I always felt like an unfortunate bystander with little control over the situation. This posts shows how we can at least start talking about this in a constructive manner.

Couldn't take an article seriously that started with the author claiming that code he writes by hand is "100% correct"

Bruh

What are the examples of artfully crafted software? What software can never be made with LLMs?

Not a loaded question but a genuine one.

Or, call yourself whatever you like.

I would call myself an artisanal programmer. Software Engineers are some of the least likable people I've ever met and being associated with them is cringe. Questions like, "Why are you using Notepad++ instead of using VSCode with 100+ plugins?" in a very condescending manner gets old very quickly. They need the title of Engineer because deep down they are very insecure.

On the plus side, they're usually promoted very quickly to management and never code again.

"I’ve seen it before, though: it’s very much part of the fascist playbook."

Holy reach

Way ahead of ya.

Fully agree with this, careful work is foundationally engineering. Slopping and not reviewing work is not.

I'm reasonably sure/hopeful all of these discussions will be as important as people's discussions about whether using vim makes you a real programmer or not.

"Does it work" is what matters. We already know that "do this make no mistakes" works on some things. And then some things that are very "wide" e g "integrations for lots of different things" you basically write a new layer of software on top of the software in specs and .md and that yields a software project that you can mostly just add features by asking for them. But there's still deep narrow projects where creating that context is way more work than just implementing it. And then you have some projects where you can mix approaches and use the "metasoftware" for all the cicd and boring bits but not the core. I'd argue all of the above it's kind of meaningless to try to distinguish it as even if it's fully handrolled an llms still there as a search engine and task runner.

> LLMs just change certain parts of the equation. For example, code writing is far less of a bottleneck than before, so "we can just try with a throwaway impl and see if this works" is suddenly economically viable.

The economic costs of LLM use have been abstracted away, but they're still very much there. The ecological cost of building and running data centres will be a pretty heavy economic cost somewhere in the future. It's not obvious, but it still exists.

(I'm not dumping on LLMs — otherwise I wouldn't even be here. I'm not a glutton for punishment. I know well that HN users excited about LLM use now vocally outweigh, and are pretty intolerant of people who are more on the cautious/negative end of the spectrum. I don't want that trouble in my life).

> Engineering is about creating something that serves a purpose, while operating within a set of constraints.

A builder fits that description. Even a cook fits that description.

Engineering is something else. It's hard to describe what it is, probably why it has its own word. Dictionaries probably offer a definition.

> A good engineer will acknowledge this tradeoff between robustness and cost and behave accordingly.

An engineer will never intentionally produce something shoddy for cost reasons. They will simply refuse to do it. What you are getting at it some tasks don't require an engineer at all. You want to build a bridge to span a kilometer of water? You need an engineer. You need to occasionally cross a ditch? Anyone could lay plank across. No engineer required. The author makes this point too, with software craftsmen.

Strong agree. I think the fundamental challenge of working in fields that increasingly become AI-enabled will be the ability to understand and direct large or intricate systems without prior knowledge/the advantage of having built the model as implemented. That’s already how it works in complex domains or large businesses.

It does require a different kind of ego/abilities than before. My (negative) framing of the whiplash effect is that it’s a reckoning of “process fetishism”/a bad kind of careerism in the tech hiring market (because for the labor market to work, candidates need to be evaluable and sortable by businesses, and many people build an identity/optimize for legibility around “best practices” or very particular “technologies” which might get them a job).

Ultimately, you need to know and learn/be responsible for stuff, and be able to help people with your labor, not be “a type of person” that isn’t effective at the task of helping. But at the same time knowing things and being able to take accountability/help people remains critical, especially because that’s what people will want to pay for even as “time spent typing it in” decreases.

Personally, I think it will be a good thing because software and “tech” will become a more strongly domain-driven/enabling medium for real-world or specialized things. IE it is the end to “software for its own sake” or “willingness to type it in and play with Jira/jenkins/frameworks” and the beginning of something that is more applicable or knowledge-building rather than “being the X for Y at Z”. Harder but more fun :)

A whole bunch of assumptions and beliefs passed off for truths.

LLMs have very little to do with engineering, unless you let a pair of dice decide how you build a house.

Cars are not built by AIs, they're built by extremely precise robots, over precise instructions.

I'd VERY much want a hand-made car over an LLM-made car, thank you.

Because I do want the precision, reliability and performance that an LLM-made car won't ever be able to guarantee.

I've gone back over most of my contributions to open source using LLMs and honestly, even though it was my best work at the time, there are big gaps that they find right away.

The myth that we've been shipping perfect code for years, but you can't trust LLMs, is just subjective blindness. People can't see the issues that they can't see, definitionally.

You can absolutely use the exact techniques we used to use in "the old days" to produce reliable code with LLMs generating most of it. The issue is, it's really not a lot less conceptual and intellectual effort than in "the old days", at root. You speed up the programming part, but the rest is still a hard slog, so nobody is out here doing really thorough testing in ways we used to dream of.

I won't lie, of course my code has bugs. The difference, as I see it, is the kinds of bugs that manifest, and how well they can be avoided.

There are two steps to writing the program: building a model in your head to map understanding to algorithms, and then implementing the algorithm in code (and of course this can get recursive if the algorithm relies on other high-level mechanisms, like data structures).

I have found that most of the time, the kind of bugs that unit tests find are typos, i.e. mistakes in the second step; but the errors that actually cost time to resolve are errors in understanding, i.e. the first step.

They can't be found with testing or verification because what it means for code to be correct depends on the specification, and the error is that the specification itself is incorrect. Asking an LLM to check this one specific part of the software is thus useless, and whole-program analysis is not cheap enough to employ at this point.

So what about avoidance? When I say hand-written code is 100% correct (or at least approaches that number), I mean that with experience, I learn more about which models tend to be correct, and thus avoid bugs of the latter kind by construction. Of course typos still exist, which is why I write unit tests, and I expect LLMs to be able to find them as well; but I believe the only way to avoid incorrect models is to learn stuff by doing, failing and failing again, figuring out nitty-gritty low-level details, until at some point you become an expert in that area and know what to use.

I also write 100% correct code, it does exactly what I wrote it to do (not compile).

she*

It may not be 100%, but human code is objectively more reliable and higher quality than any LLM generated slop code.