Of course there are errors and gaffes and weird bits all over, but that helps keep me in the loop and understanding it better.
I can now (more) boldly go where I feared to tread before.
And when I need to learn something new I hate doing courses because they're always too slowly paced for me. All courses are paced for the slowest possible participant. Especially those from the US where trainers have this "training voice" where they speak slowly and articulated and usually non-skippable which makes me scream in agony. My brain can't slow down to that level, I just lose focus then. It's like driving a ferrari at 5km/hr. Especially the non-IT courses are so slow and constantly repeat everything, as if I didn't fully understand them the first time, argh. So I tend to spend my time on these awfully designed mandatory HR courses trying to fuck around in developer mode and re-enable the skip segment features :) The more boring the training the more I learn about moodle and its frameworks.
I just love to dive right in and just do something but I often skip that first analysis of what method would be best. And I tend to stick with what I know. Which is often not the best way in a greenfield project. And often the boring first steps are so awful for me that I just put it off. If I do start I often do it half-assed. Then I run into a wall, have to regroup etc. I learn from that (mistakes are always a learing experience), but it's slow going because I take the wrong direction first.
AI really helps me get past that first step meaning I actually start it instead of procrastinating the research forever and move onto the next thing. And I can do great things because I know what I want and how I want it. It's a real enabler for me especially something like cowork. It helps me widen my horizon efficiently instead of wasting my time and energy like online courses do. It picks up things that my weak points are (patience) and feeds me information in a highly dense format I can easily digest. Helped by custom prompts of course ("don't tell me I make great decisions, evaluate everything on its merits, just tell me the meat of the content, don't elaborate"). I still work along with it and take ownership of its output, I'm way too much of a control freak to let the AI do everything without understanding it. But it gets me there quicker and it avoids procrastination by skipping the boring steps. I ask it to suggest methods and techniques, compare their pros and cons so I fully understand what I'm selecting for.
I have to say this was not really the case with early simple question/answer LLMs. The hallucinations were too bad, the searches too limited. The knowledge too hit and miss. It would come up with wrong stuff or overlook the best options. But the new high-context agentic technologies like cowork that really investigate the source material for the purposes I provide, they really are a game changer for me.
For example, I recently asked it about an obscure error I'd been having. Previous simple LLMs would just collapse into a directionless troubleshooting mode, "Did you try...?". Cowork actually went and retrieved all the relevant code from github without being asked to do so, and evaluated what would have happened in the background for that message to appear. Really good to see because it's exactly what I would have done. But I would have taken much more time to do it.
So no, for me it's not making me lose savviness. It's helping me grow it in exactly the way that's efficient for me.
What's nevertheless true is that they've hardly touched hardware hacking. There are so many interesting opportunities right now in robots, drones, materials, batteries, and custom embedded systems that still demand dirty hands and physical intuition. These still reward savvy, and they're fun!
This is something I realized when I became a manager of programmers rather than doing the work myself. When I write code I do it from a position of having a deep understanding of what all the moving pieces are, when someone working for me writes code I just have to trust they had that level of understanding[1].
But being a manger, the thrill of solving the puzzle was replaced by the thrill of helping some new engineer get better at the craft of writing code. They took pride in their growing skill set and I took pride in helping them grow.
Managing consultants however was very transactional. Did they deliver what was asked of them? Did they fix the flaws I pointed out? Do I still want to pay them?[2] And I could of course fire them easily and try new ones that had a reputation for being "better" at the tasks I needed done.
If history is any judge, there have been many companies over the years where some founder/leader has a "great idea" and just needed someone technical to make it real. And the typical arc for those companies was they get founded, they spend a ton of money on consultants to build their technology, something changes (fashion, systems, something) and their product is no longer a good fit for the market so they try to hire consultants to fix it, which now costs more than 2x because first the consultants had to understand what the previous consultants did, then they have to change it in a way that leadership wants. The result is a product that got more and more brittle until there wasn't enough money to or enough consultants to anneal the product back into something people would pay enough for to support the salaries of the visionary leaders who never had any idea at all of how the product they sold actually worked.
It feels like we're going to speed run that. In the LLM era.
[1] And of course that level of trust is not always warranted but that's a different comment :-)
[2] With consultants there is a velocity vs organizational expertise equation that always needs to be balanced. Dropping people into a legacy code base they've never seen is just as hard for them as dropping them into a consultant's work product that they hadn't previously seen.
Today I had claude figure out that using SIMD would not improve performance, and it gave me an analysis of why not. So my savvy improved without having to spend days figuring that out.
Having said that, I get that using AI can also make things less fun and reduce your learning too. I guess it depends on what you use it for.
I also had a lot of ideas that I wanted to execute and I'm finally able to do so. Some of them are wild and big, unthinkable last year. I also really enjoy building product/software that people are delighted to use. So from my perspective, the net positive outweighs the losses.
My work position is less certain, I grief the years spent mastering things just to see AI doing it, but I went to software engineering because I enjoyed building products, from ideas to something people can play with, and this has never been easier.
However, when we look at the claim with a more critical eye, it becomes obvious that this view is myopic. In fact, current progress is in fact indebted to the invention various tools, which has led us to grand theories and hypotheses: things the Ancient Greeks could only dream about.
Is coding about writing assembly? Is it about writing boilerplate? About writing endless if-then statements? I would argue that it is not: it's about coming up with ideas, building products, finding customers, iterating, producing code that's easy to read, easy to understand, easy to extend.
Coding (at least the kind LLMs do) was never really the hard part, and I'd like to know specific examples of savvyness the author is losing. They've made me more critical of code and able to create better patterns, simply because I can iterate so quickly.
This is not a fair analogy. Those things are like compilers, languages, and type-checkers. They are deterministic, carefully proven, hand-crafted tools, that allow people to go safely to a higher level of abstraction and still make things in a deterministic way. The jump into the fuzzy world of LLMs is a completely different thing. It's different than the jump from assembly to a higher-level language.
Completely disagree. I've created more tools in the past 6 months than in the past 5 years. In fact, LLMs solved the being bored and "why-even-bother" problems on my side. In a couple of weeks - I ported my old game projects to the web, I built internal tools for home-automation, masked mails helper for my FastMail, and my last project is a gradle remote-caching tool that sped up our Java builds with about 25 seconds (saves us some $$$ on Atlassian).
If all one does is writing prompts and test the output, I get it - it could get boring. I inspect the output, ask the LLM why it did what it did. When I don't know something I look it up or ask it why did it do it that way. It's the opposite of boring for me.
One thing is true though: now everyone could prompt-create the tools they need. Your OSS-project on Github is probably not gathering contributors and users.
This is it for me. It’s a pretty incredible tool but it killed the vibe and challenge of building things.
Writing things down and then arguing with an agent that constantly gets things wrong is just a new kind of Rubber Duck.
Are Rubber Ducks offloading thinking?
These are more like search plus memory tools.
Memory loss is real but that has been happening for me way before agents.
Depends on your usage. A rubber duck won't upheave the entire history of written human knowledge to reach for your answer. It doesn't have inherent bias, and its purpose could also be handled by a wall, or the air infront of you if you can stretch your mind a little. What I'm going for here is that as you said, its just a hack to make your brain look for answers in a more efficient manner, by clearly underlining your thought process out loud, tricking yourself into conversation mode, yada yada. Its still you doing all the work, you're just being smarter about it.
A LLM is more akin to a senior pair programmer. It may seem like a rubber duck on the surface, in the sense that you're having a conversation, but the senior programmer may come up with ideas you wouldn't think of. They may have more innate experience in the domain which might pull you away to very different implementations from what you had in mind initially. This is all good, but a common pitfall with LLMs is that they're much more conformative than a senior engineer, much faster, much more responsive. This is where it gets dangerous: they don't tell you you're wrong 80% of the time, like a rubebr duck. They also have innate experience of a domain, like a senior engineer. The result is that your brain never gets a 'hang' signal, and it doesn't feel the need to reevaluate.
Just that an actual rubber duck doesn’t do anything. You solve the problem you have by talking, and in doing so, thinking, to come up with a solution, an idea, or gain better understanding.
After that you either implement something yourself or have learned something.
With an LLM you offload all of that, the only thing you still do is tell it what the problem is. The agentic duck does the rest and you look at the output.
Even if you have to argue, you argue without having gone through the steps to gain anything yourself.
So this idea that doing math is some kind of fully deterministic & mechanistic process is a bit misleading.
newsomix9xl•3h ago
I think you're blaming tools for what are other problems.
No carpenter ever said "I used to plane wood by hand and carve magnificent pieces, now that I have an orbital sander and power tools, the love just isn't there".
I don't buy this argument at all.
aninteger•1h ago
goodmythical•44m ago
So more of a home-gamer chainsaw? Except that I'm not positive the once/twice per year chainsaw is nearly so effective.
anon7000•31m ago
xnzakg•30m ago
and skills from building with hand tools help you judge the results, but not necessarily with actually using the tools.
klez•1h ago
Builders/makers can be roughly subdivided into two camps: some like building for the final products; others like building for the process itself.
I'm in the latter camp. OP probably too. You probably are in the former.
And that's fine. But let's just stop pretending the other side doesn't exist.
EDIT: And this goes for OP as well. They forgot a lot of "for me"s in the article.
molly0•58m ago
thot_experiment•57m ago
thot_experiment•1h ago
croo•57m ago
furyofantares•49m ago
I would guess probably lots did say that?
At the very least I have no idea why you would be able to claim otherwise, we are far removed in time from when there were carpenters straddling the introduction of power tools.
mysterydip•46m ago
titularcomment•29m ago
anon7000•32m ago
For a woodworker, I think your analogy should be a “furniture factory,” not power tools. (Power tools in software would be like a great IDE and powerful language and framework tooling; AI is… way more than that.) I bet a “woodworker” in a furniture factory (if that even exists) doesn’t much care about their output, and doesn’t love the process anymore.
And getting paid for it doesn’t make you care about your work either, it just makes you care about money you can use on other things you do care about.
It would be foolish for anyone looking at the great change happening in software, and ignore the fact that we’re crossing a line where it’s less about craft, and where developers are just managing factory-like processes. Which is very different from what most signed up for.
And of course you can still do your craft, just like there are custom woodworkers as well as factories. But the space for that in AI-driven companies is vanishing as much as we might hate it or push back against it.
And of course there are also people like you who like the opportunity that more output provides, or who use it more like a tool and less like a factory. And that’s fine.
But no, the transition happening in the industry is not deliberately trying to keep the craft of it or even to keep developers interested in the job.
The transition is turning people who input stuff into a software factory and do QA on the output, or turning people into “factory automation engineers.” Those are both very different jobs from what people who like programming signed up for.
And yeah maybe no one “deserves” to have craft in their jobs. But let’s be honest, it is very natural, and very human, to be upset when the main motivation and reason for doing your work disappears. The same thing has happened in countless industries, and people have been talking about it for decades if not hundreds of years.
E.g. small-time farming replaced by exploitative big agriculture. A farmer might have a reason and identify in the work before, owning their own bit of land they tender. And now if they’re just hired to drive a tractor, they don’t. It’s a massive difference, and no wonder our society is increasingly depressed.