11 ms·

The rise of judgement over technical skill

278 points by kohlhofer 1y ago

deleted 1y ago
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crabl 1y ago
As the marginal cost of writing code decreases, the opportunity cost associated with writing the "right" code increases dramatically
mehulashah 1y ago
I would argue that this is already true in roles where one supervises the work of another person with skill. Great leaders, for example, were once practitioners. Over time their skills may fade, but their judgment makes them effective and able to the scale their impact.
- drewcoo 1y ago
  In software, we promote good engineers to management, effectively accelerating the Peter Principle. It doesn't have to be that way. Management skills are not an outgrowth of the skills of the managed, but orthogonal to them. This is similar to the lesson many PhD candidates I've known learn: expertise in their field is not pedagogical expertise. Companies who promoted from within used to provide training for new managers.
  - apwell23 1y ago
    > In software, we promote good engineers to management i've not seen this. Infact its the opposite.
    - paulluuk 1y ago
      You've seen good managers promoted to engineers? ;) I have seen this happening, usually the engineers with the best technical AND people skills are first made lead developer, and eventually "team lead". After team lead they can climb the corporate ladder with titles like "junior vice president" or "senior director".
ben30 1y ago
This echoes my experience with Claude Code. The bottleneck isn't the code generation itself—it's two critical judgment tasks: 1. Problem decomposition: Taking a vague idea and breaking it down into well-defined, context-bounded issues that I can effectively communicate to the AI 2. Code review: Carefully evaluating the generated code to ensure it meets quality standards and integrates properly Both of these require deep understanding of the domain, the codebase, and good software engineering principles. Ironically, while I can use AI to help with these tasks too, they remain fundamentally human judgment problems that sit squarely on the critical path to quality software. The technical skill of writing code has been largely commoditized, but the judgment to know what to build and how to validate it remains as important as ever.
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- gherkinnn 1y ago
  That matches my experience. Decomposing a problem so that it is solvable with ease is what I enjoy most about programming and I am fine with no longer having to write as much code myself, but resent having to review so much more. Now, how do we solve the problem of people blindly accepting what an LLM spat out based on a bad prompt. This applies universally [0] and is not a technological problem. 0 - https://www.theverge.com/policy/677373/lawyers-chatgpt-hallucinations-ai https://www.theverge.com/policy/677373/lawyers-chatgpt-hallu...
  - ben30 1y ago
    Agreed on the review burden being frustrating. Two strategies I've found helpful for managing the cognitive load: 1. Tight issue scoping: Making sure each issue is narrowly defined so the resulting PRs are small and focused. Easier to reason about a 50-line change than a 500-line one. 2. Parallel PR workflow: Using git worktrees to have multiple small PRs open simultaneously against the same repo. This lets me break work into digestible chunks while maintaining momentum across different features. The key insight is that smaller, well-bounded changes are exponentially easier to review thoroughly. When each PR has a single, clear purpose, it's much easier to catch issues and verify correctness. Im finding these workflow practices help because they force me to engage meaningfully with each small piece rather than rubber-stamping large, complex changes.
bravesoul2 1y ago
Does the technical skill give you better judgement though? Can a masterchef make better Star Trek replicator meals?
- kusokurae 1y ago
  I think the reality is that, this notion of "democratising" various technical mediums is used to gloss over that, as countless studies have now evidenced, humans primarily learn and remember well thing by doing things, not merely passively consuming them. Fine-precision decision-making will likely always be the domain of dedicated tooling designed to better correspond with the particular medium or task -- that is, manual testing and experimentation, not relying on logocentric prompt idolatry. When we get into literature, visual art etc. it becomes more of a problem. You can't get Cormac McCarthies or Mars Voltas from software designed to give you perfect statistical 50% grey, and people who try and hack it without doing the reading, are going to end up writing gibberish. People who actually enjoy and like art, music whatever are going to grow Very bored with the overwhelming majority of work reliant of primarily generative methods, save for those who already have discretion learned through experience of many tools and other means of expression.
- 12112521312 1y ago
  Yes, really good pianist often compose music that is interesting, that other composers don't make ( e.g. Listz, Alkan ). In jazz, nothing can replace practicing your improv skills.
  - drewhk 1y ago
    Also, judgement alone might not be enough. Judgement can take you to "something is off", but not necessarily further. I mix music as a hobby and it takes a good amount of practice to step up from recognizing the presence of a problem to actually know where and how to fix it. If you don't know where you should look, you just aimlessly try various things, and it is not unusual to make the problem worse. Eventually you learn to properly recognize the problems, not just their presence, but their actual nature and implications. But this takes practice.
smitty1e 1y ago
Grok3: "The phrase "There is no royal road to geometry" is attributed to the ancient Greek mathematician Euclid. According to historical accounts, particularly from the philosopher Proclus, Euclid reportedly said this to Ptolemy I Soter, the ruler of Egypt, when the king asked if there was a shorter or easier way to learn geometry. Euclid's response emphasized that geometry, like any rigorous discipline, requires effort and dedication, with no shortcuts even for royalty." You can use AI as a royal road, but it may or may not prove an effective substitute for the learning required to provide judgement.
monero-xmr 1y ago
Nothing stopped anyone from hiring 10 to 100 offshore devs for every American software dev for the last 20 years. Yet Google, Amazon, Microsoft, and so on paid top dollar for the Americans. And American business still pays top dollar. Even more than before. The judgement was always the problem. If the issue was bodies in seats the problem was already solved. The #1 cause of layoffs in America is offshoring caused by Zoom and other telework tools perfected during COVID. AI is a convenient excuse. Pop music is mostly not about music quality - hits are always passable - but about celebrity. The rare song that elevates a new artist quickly converts them into celebrity, which converts future songs in their style into further hits 100,000x easier than before. Maybe even 1 billion times easier than before given the amount of songs created every year. Yet AI is supposedly an expert at generating music, and images, and video, and code, and on and on. I’m not seeing the evidence of layoffs from AI. I’m seeing evidence of better productivity from existing employees, which is the same result of every groundbreaking technology since all time.
- MangoToupe 1y ago
  > Pop music is mostly not about music quality - hits are always passable - but about celebrity. Interesting and bold statement. How do you distinguish the two?
  - kusokurae 1y ago
    Worth mentioning here that historically a lot of the famous pop hits have had plenty of interesting technical decisions typically only a mature composer would come up with. Weird short bars, time signature stuff, temporary key changes, weird jazz chords etc. You don't notice them because they're refined choices.
  - monero-xmr 1y ago
    Whatever schlock Taylor Swift manufactures next will be a global hit. Doesn’t matter the quality
    - triceratops 1y ago
Fr3dd1 1y ago
Today, if someone uses LLMs for code generation, he/she will probably question the generated code and will put his own judgement above it. I am curious how fast that will change, especially for juniors. When will they start to question their own judgement and just go with the generated code becuase its "more safe"?
- kusokurae 1y ago
  At present, when juniors do this at my company, they usually get fired within the month. The onboarding docs now explicitly state that though code review is a joint-responsibility process, you as the submitter are responsible for understanding it, ensuring it all works, and being aware of the broader scope and consequences. Maybe many companies have placed more responsibility on the reviewier to catch problems in the past?
  - Fr3dd1 1y ago
    I would go a step further and dont let juniors use LLMs for code generation. The purpose and your role as a junior is to not only work but also to learn. When using genrated code, you miss a lot of opportunities to do so. Of course you could learn of some other methods or stuff from the frameworks you are using but imho thats not that big of an advantage.
- Animats 1y ago
  Probably when the generated code is, on average, better than human-generated code. Somewhere between 1 and 10 years out.
- chasd00 1y ago
  LLMs are very good at sounding right. I’m sure the code generated from them are rarely reviewed by junior developers. Even if they did question it i bet they give the LLM the benefit of the doubt. “Well the computer said this so it must be right otherwise it would be a bug and I bet Anthropic has caught all the bugs…”
roenxi 1y ago
Human judgement is like a house built on sand, it is basically provably feeble [0]. I've literally never in practice seen a human update their beliefs using Bayes' formula. I suspect we'll find that at some point fairly soon AIs will just have better judgement than us because they can be programmed to incorporate formal statistical concepts while humans have to rely on evolving grey goop which we haven't quite mastered. I imagine it'll be almost comical watching human experts going up against a system that can actually intuit the difference between a 60% and 70% chance of something happening in their risk calculations. Humans will still have a role expressing preferences and subjective questions though. Questions like "how much risk do you want your investments to take?" or "does this look good?" ultimately can't be answered by AIs because they depend on the internal state of a human. [0] See also, the academic field of psychology
- bsder 1y ago
  > I've literally never in practice seen a human update their beliefs using Bayes' formula. Then you've never debugged anything genuinely difficult. Moving from "Where did I screw up in my code?" to "Is this library broken?" to "Wait, that's not possible. Let's look at the compiler output on Godbolt." to "Are you kidding me? The SPI system returns garbage in the last bit for transactions of 8n+1 bits?" (BTW, Espressif, please fix that in the C6. Kthxbye.) is all about establishing ground truth and adjusting your Bayesian priors as you gather evidence.
- Corey_ 1y ago
  Humans may not update like Bayesians, but we read context, shift priorities, and act under pressure. Judgment isn't just math — it's lived experience, intuition, and meaning in motion. That’s still hard to replicate.
- ookdatnog 1y ago
  If there is one thing AI is currently shockingly bad at, it's updating its assumptions when it is confronted with evidence that they are incorrect. It will tirelessly spin its wheels (seemingly) forever laboring under a false assumption, running into dead end after dead end without ever coming to the conclusion that it should reexamine its assumptions.
CleverLikeAnOx 1y ago
This blog post shows how not to use AI. The author would have been unlikely to write such a uselessly redundant conclusion if they had to type it themselves. Edit: I like the post, but it didn't need to be padded with fluff.
- Veen 1y ago
  We shouldn't be too quick to jump to "AI did it." People write redundant paragraphs and sentences in articles all the time because they're led to believe that every article needs a conclusion that sums up what's already been said. Ironically, including one in this article showed a lack of good judgment, which isn't confined to AIs.
  - QuadmasterXLII 1y ago
    It does show an interesting second order downside of publicly using an LLM for anything: it raises everyone else’s suspicion that the rest of your work is LLM generated.
  - SoftTalker 1y ago
    A certain amount of redundancy can be helpful. If you explain the same thing two different ways, one way might make more sense than the other to a particular reader. The judgement comes in because you should not just be doing this by rote or because you were "lead to believe" it was necessary, but in consideration of who you are writing for.
- wiseowise 1y ago
  Where do you think LLMs learn to write “uselessly redundant conclusion”?
westcoast49 1y ago
Music was never an issue of skill. You might have needed skill in order to get to the point where you could use your judgement, but skill was never the deciding factor. So, I don't agree with Brian Eno's point that there has been some kind of seismic shift when it comes to this. Rather, it's just a matter of a shift in the type of skill that you need to have. The same is probably true when it comes to AI tools within the field of programming.
- drewcoo 1y ago
  Getting a seat in a symphony involves skill. Brian Eno didn't just do rock.
  - Tarq0n 1y ago
    Ever seen a photoshop expert at work? Every human endeavor has a skill distribution. Hammering in a nail takes skill.
  - westcoast49 1y ago
    I'm just arguing that there has been no qualitative shift. The skills you need to produce pop music today are different than the skills that you needed before. Now you need to be able to operate a MIDI sequencer or a program like Ableton, which is not necessarily easier in and off itself, than for instance learning how to play a guitar. I think it's the same with AI tools and programming. We're just talking about a different set of skills that you need in order to be competitive. I don't think there has been any real shift from "skill needed" to "judgement needed". I think this relationship remains the same, both for pop music and programming, but also for the example of playing an instrument in a symphony orchestra.
Corey_ 1y ago
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physicsguy 1y ago
A similar debate has happened in education where people seem to think that having ability to critically analyse texts is more important than knowledge. and to some degree that’s true but personally I think that without building on some decent level of foundational level of knowledge and having a mental model of a subject, you can’t tackle thorny questions because you don’t have enough to draw upon as examples and counterpoints about how to proceed. My current employer is currently going on a top down driven “one tech” mission and trying to rationalise the technology stacks across diverse product lines. Which is all fine but the judgement is a poor one because the biggest developer bottleneck that comes up in internal developer surveys is the corporate mandated IT things and a relatively hostile setup without even local admin rights, which make sense for general office workers and don’t make sense at all for software developers.
- Wololooo 1y ago
  Reminds me of that concept that I saw pop up in HEP in recent years between "users" and "experts". This distinction in that case is so dumb I cannot wrap my head around it: You first encounter the code, are unfamiliar with it but very quickly you become expert in order to solve your problem and advance the thing forward. It does not matter which codebase you start on, what matters is that you understand what the actual stack does and what is involved in there because people are supposed to understand deeply what they are doing. But this comes from the "corporatisation" of every single entity, where random metrics are used in order to assess performance instead of asking the simple question of "does it work" or "does it need fixing" or "will this thing break". There is a clear disconnect between the manager type people that are removed from the work and the managers still doing things practically, which understand what the stressors are and where some work of deep understanding and extra contextualisation of the systems, is required, in order to not mess the whole thing up. This being said, this is coming from a very peculiar perspective and with a very specific tech stack which is and is not industry standard at many levels...
  - kragen 1y ago
    High-energy physics?
wg0 1y ago
The problem is - you can't judge if you're not skilled. So still, get skilled. Learn everything first hand. Try to master it. That's how our species prevailed in the first place.
- hinkley 1y ago
  CERT advisories are evidence that skill is necessary but insufficient. There’s a lot of code. We get ping ponged between various sections of the code every few weeks. Other people are contributing. There’s a ton of ways code can look like it’s probably correct and not be. There are non obvious bugs everywhere, and there’s an element of luck to whether you’re in the right headspace to catch them all.
TrackerFF 1y ago
AI works great for providing you a starting point, and giving a big picture view of how certain things work, and how you should structure them. Sometimes, even if you're a really seasoned software engineer, you'll encounter something you haven't seen before. Maybe to the point that you don't really even know what to search for to get started. So instead of spending half a day scrounging various forums, e-books, etc. you can ask the model, in somewhat vague terms, what you're looking for - and some of the LLMs are quite good at just that. Now, the implementation of such things, not quite there yet. My experience has been that the more obscure the problems you deal with, the more obsolete code the model will spit out - with dead and unsupported libraries etc.
dwoldrich 1y ago
AI enables me to gold plate _everything_ I do, which feels exhilarating, if a bit exhausting. Having decent taste and being able to continuously test and verify my work allows me to smooth over the occasional hallucinations and elicit towering, mind-bending solutions. AI's no replacement for experience; garbage in-garbage out. When AI gets too good, I figure people will cloister to stop feeding the beast. It can only lead to ignorance and misery, I fear.
- kragen 1y ago
  Can you elaborate? What kinds of things are you doing, maybe something related to programming? What part of the job do you delegate?
  - dwoldrich 1y ago
    Not delegating, just tricking everything I develop out far more than I would have in the past. I'm on yet another hodgepodge project in a looong, decades long series of hodge and podge. AI is letting me begin to answer to my own satisfaction, "what does it look like to do everything to the best of my ability?" In my current gig, I have an on-prem database and legacy application that is human-powered software, where parts of the business process never touch the computer and a human does the work (mostly support stuff), (and for no good reason other than this system never had real engineering support.) So, I joined the team, and started to wrangle the system. First thing I was asked to do was get their database code and schema into source control with managed releases. The gold plating process that I never would have entertained in the past led me to get a migration tool installed, get a unit test engine installed in the database and writing new code with tests, figure out even how to refactor the big ball of mud and coming up with patterns there, doing github workflows to run the tests and deploy to multiple environments, linters, Slack alerts. It's not that I wasn't aware of all these things, I just never would have done all of them _to the extent_ that I did because the time needed to research it all traditionally and spike the solutions would have been too great. And I documented it all! After the databases were basically under control and I had gained the team's trust, I moved the team to start automating the human-powered parts of the software. We started an admin console webapp project. Again, I was heavy into AI all along the way, even during requirements elicitation. Our data is a rube goldberg machine of cloud and on-prem, but the majority of what we need to get under control is legacy/on-prem. We want the webapp to eventually be hosted in the cloud, but to be close to our databases and not have to fuss with private links, we decided for starters to deploy the webapp on-prem next to them. So, that meant figuring out how to get our github builds deployed on-prem. There was this huge saga in figuring out how to provision an on-prem GitHub Runner and use Powershell Remoting to fan out our deployments from there to all of the on-prem servers. Never EVER would I have been able to figure out the permissions and powershell provisioning steps needed to pull that off. It's all very gross, Windows is gross, but what we've built works dependably and is secure. I probably would have just used Samba or some other cheesy way to move files around and trigger deployments if I didn't have AI to bounce all these ideas off of. Another example: we wanted our BFF microservices to eventually deploy as Azure Functions, so gold plating meant we had to figure out how to build and deploy functions on-prem. It ended up being very productive, but again I would have never entertained doing such a thing unless I could bounce my ideas off AI and get credible directions on how to proceed. Instead, I would have written the service as trusty/crusty old Express 4.x and ported the code to Functions once we made the jump to cloud. I am saving future me a ton of work and heartburn! At every step AI is giving me the latitude to ask, given whatever nasty situation I'm in, what would be the best code/most secure/nicest architecture in that case? It's arduous to continually pepper it with questions and spend many days zeroing in on a final solution with it. But, it beats the guessing game of searching DuckDuckGo, StackOverflow, and software vendors' documentation - those are now the _last_ places I look for answers. (For ill, I'm sure.)
overfl0w 1y ago
This reminds me of Asimov's Jokester story where the same themes are explored - there is an all-knowing computer but someone needs to ask the correct questions. "Early in the history of Multivac, it had become apparent that the bottleneck was the questioning procedure. Multivac could answer the problem of humanity, all the problems, if it were asked meaningful questions. But as knowledge accumulated at an ever-faster rate, it became ever more difficult to locate those meaningful questions. Reason alone wouldn't do. What was needed was a rare type of intuition; the same faculty of mind (only much more intensified) that made a grand master at chess. A mind was needed of the sort that could see through the quadrillions of chess patterns to find the one best move, and do it in a matter of minutes."
- stopthe 1y ago
  That chess metaphor didn't age well
  - Jensson 1y ago
    That is the goal post moving, its done by AI optimists that thinks "we just need something that can solve X and it will be as smart as a human expert". Wasn't true for chess, wasn't true for Go, we will see when its true, but they are constantly moving the goalposts and then arguing its others who are moving it.
layer8 1y ago
When your judgement tells you “this is wrong”, you may need the technical skill to know what instead is right. The real question is when AI will surpass the average human in both judgement and technical skill.
k__ 1y ago
I think, the argument would make more sense if software like Cubase came with unlicenced samples from all songs out of the box. Artists sued and won when someone used their samples without permission. If you use AI to create art, it's like that.
- CuriouslyC 1y ago
  There's a difference between a sample and something inspired by something but also significantly different. The copyright laws around music are kind of draconian so it's not a good analogy for code anyhow, imagine a world where a fundamental do while loop had 90 year copyright protection, and that's the sort of world we'd be living in if code copyright was like music copyright.
  - k__ 1y ago
    If you see the generated content as "the music that's created with unlicenced samples" that's true. However, if you see the trained models as "the music that's created with unlicenced samples" it isn't true.
lordnacho 1y ago
Judgement and technical skill go hand in hand. Technology merely moves the boundary of what is considered judgement, and what is considered technical skill. I know someone who wrote programs in the punch-card era. Back then, technical skill meant being diligent and thoughtful enough that you avoided most bugs when writing the program. If you screwed this up, you had to wait for another time slot. What does this mean for the complexity of programs you could write? Well, it means you are quite limited. You can't build judgement about things above what is now considered a very basic program. I learned to program before the AI era that seems to be nascent. Technical skill means things like being able to write programs in python and c++, getting many computers to work together, being able to find hints when something goes wrong, and so on. Judgement now covers things like how a large swarm of programs interact, which was not really in scope for punch-card guy. Now AI arrives, and it appears that we are free from technical skill problems. Indeed, it does fix a lot of my little syntax issues, but actually it just moves the goalposts. There's soon going to be no excuse for spending time working out the syntax for a lambda function, you'll be expected to generate a much more complicated product, for which you will need an even higher overview to say you are providing judgement.
4b11b4 1y ago
Yeah but, you can't make a judgement in these technical areas without the technical skill... No?
deleted 1y ago
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red_admiral 1y ago
And what is that judgement based on? Jobs that an AI can't do yet, like designing a system architecture and drawing boundaries (which features go in the same service), need someone with experience. We can apply this to all points in the Future of Work section. Even the conclusion "What should you do, and why?" is basically a disguised "What domain-specific knowledge do you have to make an informed opinion on the 'why' anyway?"
giordanol 1y ago
The tooling problem is 90% solved. The new technical bottleneck is human judgment.
somewhereoutth 1y ago
"Anyone with access to AI tools can now produce work that, _at least superficially_, resembles professional output." Key quote, emphasis mine.
z3t4 1y ago
It takes skill to see the beauty
0x445442 1y ago
Writing musical notation doesn't strike me as technically difficult but I'm unaware of any musical composers who weren't proficient in at least one instrument. Good judgement is only accessible to those who've invested considerable time in the rudiments.
curtisszmania 1y ago
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financypants 1y ago
Have people noticed the ai-assisted code "creep"? Cursor now by default applies its changes before you've even hit accept, and the tab autocomplete is getting out of control. Sometimes I'll have my cursor resting on some block of code, then suddenly Cursor suggests I delete the whole thing.
tingle 1y ago
Chap. CCCLXIV. — On the Judgment of Painters. When the work is equal to the knowledge and judgment of the painter, it is a bad sign; and when it surpasses the judgment, it is still worse, as is the case with those who wonder at having succeeded so well. But when the judgment surpasses the work, it is a perfectly good sign ; and the young painter who possesses that rare disposition, will, no doubt, arrive at great perfection. He will produce few works, but they will be such as to fix the admiration of every beholder. Leonardo da Vinci, "A Treatise on Painting.", p. 225 https://archive.org/details/davincionpainting00leon/page/224/mode/2up https://archive.org/details/davincionpainting00leon/page/224...
- gavmor 1y ago
  > Nobody tells this to people who are beginners, I wish someone told me. All of us who do creative work, we get into it because we have good taste. But there is this gap. For the first couple years you make stuff, it’s just not that good. It’s trying to be good, it has potential, but it’s not. But your taste, the thing that got you into the game, is still killer. And your taste is why your work disappoints you. A lot of people never get past this phase, they quit. Most people I know who do interesting, creative work went through years of this. We know our work doesn’t have this special thing that we want it to have. We all go through this. And if you are just starting out or you are still in this phase, you gotta know its normal and the most important thing you can do is do a lot of work. Put yourself on a deadline so that every week you will finish one story. It is only by going through a volume of work that you will close that gap, and your work will be as good as your ambitions. And I took longer to figure out how to do this than anyone I’ve ever met. It’s gonna take awhile. It’s normal to take awhile. You’ve just gotta fight your way through. (Ira Glass)
  - ChrisMarshallNY 1y ago
    I like to do a good job on small stuff. It works nicely for me, but doesn't really bring accolades (but a hell of a lot of folks actually rely on stuff I authored; they just don't know it, or care -which is just fine).
    - 1y ago
smithkl42 1y ago
This doesn't actually sound encouraging. Judgment is not actually independent of skill, and the sort of music that this approach produces (i.e., nearly everything you hear on the radio these days) is a pretty solid proof of that.
metalrain 1y ago
I think what and how are so tightly linked, you need to know how to make a thing so you better know what thing to make. Let's say you want to build worlds fastest car. You can order the pieces and maybe build a car from someones instructions. But to know what makes car fast and how to build it you need to know more and more intricate details. Physics, material science, 3D printing, engineering. How do you measure traction? What shapes increase downforce? That is how I see AI tools. You can get "off the shelf" ideas on different things, even complete small things, but you really need to be or grow to match the challenge you are facing.
nluken 1y ago
A side note to the general point of the article, but I hate how the tech industry uses the word "democratization" to mean "lowering the barrier to entry". These concepts differ from each other but many use the former term because in doing so they justify their actions as driven by some sort of moral imperative when in reality, the development of LLMs is morally neutral, not inherently bad by any stretch, but as much a wealth and power play as any other technology of the last 25 years.
- greg7gkb 1y ago
  I agree with you however I've also not found a better substitute. Any candidates?
  - neochief 1y ago
    Commoditization.
scj 1y ago
AI can draw blueprints of a house. The house may look aesthetically pleasing, but if it can't hold it's own weight, the design is flawed. There's a difference between an executed image and a display-only image. At a certain point, judgment requires technical knowledge.
- aaron695 1y ago
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keybored 1y ago
Very thin article. The thesis might as well be that technical competence is gone and judgement is all that’s left. I file this under the category of AI musings on the inevitable massively changed landscape that AI has wrought.[1] I get the feeling that the content itself is secondary (again: the thesis is thin) to the motivation of writing about how AI has supposedly changed everything forever. In this case: now technical competence is dead, hail the king (judgement or whatever). [1] “I’m learning that every topic that people read should be about AI.” : https://news.ycombinator.com/item?id=44082683 https://news.ycombinator.com/item?id=44082683
dcre 1y ago
The Eno quote is good, but the post adds nothing to it! If anything, I think the sections after the quote make the post worse. This shows poor judgment on the part of the author.
catigula 1y ago
I love these little anecdotes because they always pre-suppose that everyone - the writer, of course, but also the reader - themselves are the people who don't lack judgment, which is a role they relegate to, perhaps, a particularly incompetent co-worker, or even unknown and faceless "drudge". Which is to say that there's an obvious affliction of narcissism at work that precludes good judgment.
gwd 1y ago
I agree with the premise; but the lists sound suspiciously AI-like. "Understanding what's worth making in the first place": Pretty good "Evaluating quality": Could be a lot better.
ashley1121 1y ago
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278 points by kohlhofer 1y ago

deleted 1y ago

[deleted]

As the marginal cost of writing code decreases, the opportunity cost associated with writing the "right" code increases dramatically

mehulashah 1y ago

I would argue that this is already true in roles where one supervises the work of another person with skill. Great leaders, for example, were once practitioners. Over time their skills may fade, but their judgment makes them effective and able to the scale their impact.

drewcoo 1y ago
In software, we promote good engineers to management, effectively accelerating the Peter Principle. It doesn't have to be that way. Management skills are not an outgrowth of the skills of the managed, but orthogonal to them. This is similar to the lesson many PhD candidates I've known learn: expertise in their field is not pedagogical expertise. Companies who promoted from within used to provide training for new managers.
- apwell23 1y ago
  > In software, we promote good engineers to management i've not seen this. Infact its the opposite.
  - paulluuk 1y ago
    You've seen good managers promoted to engineers? ;) I have seen this happening, usually the engineers with the best technical AND people skills are first made lead developer, and eventually "team lead". After team lead they can climb the corporate ladder with titles like "junior vice president" or "senior director".

ben30 1y ago

This echoes my experience with Claude Code. The bottleneck isn't the code generation itself—it's two critical judgment tasks: 1. Problem decomposition: Taking a vague idea and breaking it down into well-defined, context-bounded issues that I can effectively communicate to the AI 2. Code review: Carefully evaluating the generated code to ensure it meets quality standards and integrates properly Both of these require deep understanding of the domain, the codebase, and good software engineering principles. Ironically, while I can use AI to help with these tasks too, they remain fundamentally human judgment problems that sit squarely on the critical path to quality software. The technical skill of writing code has been largely commoditized, but the judgment to know what to build and how to validate it remains as important as ever.

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gherkinnn 1y ago
That matches my experience. Decomposing a problem so that it is solvable with ease is what I enjoy most about programming and I am fine with no longer having to write as much code myself, but resent having to review so much more. Now, how do we solve the problem of people blindly accepting what an LLM spat out based on a bad prompt. This applies universally [0] and is not a technological problem. 0 - https://www.theverge.com/policy/677373/lawyers-chatgpt-hallucinations-ai https://www.theverge.com/policy/677373/lawyers-chatgpt-hallu...
- ben30 1y ago
  Agreed on the review burden being frustrating. Two strategies I've found helpful for managing the cognitive load: 1. Tight issue scoping: Making sure each issue is narrowly defined so the resulting PRs are small and focused. Easier to reason about a 50-line change than a 500-line one. 2. Parallel PR workflow: Using git worktrees to have multiple small PRs open simultaneously against the same repo. This lets me break work into digestible chunks while maintaining momentum across different features. The key insight is that smaller, well-bounded changes are exponentially easier to review thoroughly. When each PR has a single, clear purpose, it's much easier to catch issues and verify correctness. Im finding these workflow practices help because they force me to engage meaningfully with each small piece rather than rubber-stamping large, complex changes.

bravesoul2 1y ago

Does the technical skill give you better judgement though? Can a masterchef make better Star Trek replicator meals?

kusokurae 1y ago
I think the reality is that, this notion of "democratising" various technical mediums is used to gloss over that, as countless studies have now evidenced, humans primarily learn and remember well thing by doing things, not merely passively consuming them. Fine-precision decision-making will likely always be the domain of dedicated tooling designed to better correspond with the particular medium or task -- that is, manual testing and experimentation, not relying on logocentric prompt idolatry. When we get into literature, visual art etc. it becomes more of a problem. You can't get Cormac McCarthies or Mars Voltas from software designed to give you perfect statistical 50% grey, and people who try and hack it without doing the reading, are going to end up writing gibberish. People who actually enjoy and like art, music whatever are going to grow Very bored with the overwhelming majority of work reliant of primarily generative methods, save for those who already have discretion learned through experience of many tools and other means of expression.
12112521312 1y ago
Yes, really good pianist often compose music that is interesting, that other composers don't make ( e.g. Listz, Alkan ). In jazz, nothing can replace practicing your improv skills.
- drewhk 1y ago
  Also, judgement alone might not be enough. Judgement can take you to "something is off", but not necessarily further. I mix music as a hobby and it takes a good amount of practice to step up from recognizing the presence of a problem to actually know where and how to fix it. If you don't know where you should look, you just aimlessly try various things, and it is not unusual to make the problem worse. Eventually you learn to properly recognize the problems, not just their presence, but their actual nature and implications. But this takes practice.

smitty1e 1y ago

Grok3: "The phrase "There is no royal road to geometry" is attributed to the ancient Greek mathematician Euclid. According to historical accounts, particularly from the philosopher Proclus, Euclid reportedly said this to Ptolemy I Soter, the ruler of Egypt, when the king asked if there was a shorter or easier way to learn geometry. Euclid's response emphasized that geometry, like any rigorous discipline, requires effort and dedication, with no shortcuts even for royalty." You can use AI as a royal road, but it may or may not prove an effective substitute for the learning required to provide judgement.

monero-xmr 1y ago

Nothing stopped anyone from hiring 10 to 100 offshore devs for every American software dev for the last 20 years. Yet Google, Amazon, Microsoft, and so on paid top dollar for the Americans. And American business still pays top dollar. Even more than before. The judgement was always the problem. If the issue was bodies in seats the problem was already solved. The #1 cause of layoffs in America is offshoring caused by Zoom and other telework tools perfected during COVID. AI is a convenient excuse. Pop music is mostly not about music quality - hits are always passable - but about celebrity. The rare song that elevates a new artist quickly converts them into celebrity, which converts future songs in their style into further hits 100,000x easier than before. Maybe even 1 billion times easier than before given the amount of songs created every year. Yet AI is supposedly an expert at generating music, and images, and video, and code, and on and on. I’m not seeing the evidence of layoffs from AI. I’m seeing evidence of better productivity from existing employees, which is the same result of every groundbreaking technology since all time.

MangoToupe 1y ago
> Pop music is mostly not about music quality - hits are always passable - but about celebrity. Interesting and bold statement. How do you distinguish the two?
- kusokurae 1y ago
  Worth mentioning here that historically a lot of the famous pop hits have had plenty of interesting technical decisions typically only a mature composer would come up with. Weird short bars, time signature stuff, temporary key changes, weird jazz chords etc. You don't notice them because they're refined choices.
- monero-xmr 1y ago
  Whatever schlock Taylor Swift manufactures next will be a global hit. Doesn’t matter the quality
  - triceratops 1y ago

Fr3dd1 1y ago

Today, if someone uses LLMs for code generation, he/she will probably question the generated code and will put his own judgement above it. I am curious how fast that will change, especially for juniors. When will they start to question their own judgement and just go with the generated code becuase its "more safe"?

kusokurae 1y ago
At present, when juniors do this at my company, they usually get fired within the month. The onboarding docs now explicitly state that though code review is a joint-responsibility process, you as the submitter are responsible for understanding it, ensuring it all works, and being aware of the broader scope and consequences. Maybe many companies have placed more responsibility on the reviewier to catch problems in the past?
- Fr3dd1 1y ago
  I would go a step further and dont let juniors use LLMs for code generation. The purpose and your role as a junior is to not only work but also to learn. When using genrated code, you miss a lot of opportunities to do so. Of course you could learn of some other methods or stuff from the frameworks you are using but imho thats not that big of an advantage.
Animats 1y ago
Probably when the generated code is, on average, better than human-generated code. Somewhere between 1 and 10 years out.
chasd00 1y ago
LLMs are very good at sounding right. I’m sure the code generated from them are rarely reviewed by junior developers. Even if they did question it i bet they give the LLM the benefit of the doubt. “Well the computer said this so it must be right otherwise it would be a bug and I bet Anthropic has caught all the bugs…”

roenxi 1y ago

Human judgement is like a house built on sand, it is basically provably feeble [0]. I've literally never in practice seen a human update their beliefs using Bayes' formula. I suspect we'll find that at some point fairly soon AIs will just have better judgement than us because they can be programmed to incorporate formal statistical concepts while humans have to rely on evolving grey goop which we haven't quite mastered. I imagine it'll be almost comical watching human experts going up against a system that can actually intuit the difference between a 60% and 70% chance of something happening in their risk calculations. Humans will still have a role expressing preferences and subjective questions though. Questions like "how much risk do you want your investments to take?" or "does this look good?" ultimately can't be answered by AIs because they depend on the internal state of a human. [0] See also, the academic field of psychology

bsder 1y ago
> I've literally never in practice seen a human update their beliefs using Bayes' formula. Then you've never debugged anything genuinely difficult. Moving from "Where did I screw up in my code?" to "Is this library broken?" to "Wait, that's not possible. Let's look at the compiler output on Godbolt." to "Are you kidding me? The SPI system returns garbage in the last bit for transactions of 8n+1 bits?" (BTW, Espressif, please fix that in the C6. Kthxbye.) is all about establishing ground truth and adjusting your Bayesian priors as you gather evidence.
Corey_ 1y ago
Humans may not update like Bayesians, but we read context, shift priorities, and act under pressure. Judgment isn't just math — it's lived experience, intuition, and meaning in motion. That’s still hard to replicate.
ookdatnog 1y ago
If there is one thing AI is currently shockingly bad at, it's updating its assumptions when it is confronted with evidence that they are incorrect. It will tirelessly spin its wheels (seemingly) forever laboring under a false assumption, running into dead end after dead end without ever coming to the conclusion that it should reexamine its assumptions.

CleverLikeAnOx 1y ago

This blog post shows how not to use AI. The author would have been unlikely to write such a uselessly redundant conclusion if they had to type it themselves. Edit: I like the post, but it didn't need to be padded with fluff.

Veen 1y ago
We shouldn't be too quick to jump to "AI did it." People write redundant paragraphs and sentences in articles all the time because they're led to believe that every article needs a conclusion that sums up what's already been said. Ironically, including one in this article showed a lack of good judgment, which isn't confined to AIs.
- QuadmasterXLII 1y ago
  It does show an interesting second order downside of publicly using an LLM for anything: it raises everyone else’s suspicion that the rest of your work is LLM generated.
- SoftTalker 1y ago
  A certain amount of redundancy can be helpful. If you explain the same thing two different ways, one way might make more sense than the other to a particular reader. The judgement comes in because you should not just be doing this by rote or because you were "lead to believe" it was necessary, but in consideration of who you are writing for.
wiseowise 1y ago
Where do you think LLMs learn to write “uselessly redundant conclusion”?

westcoast49 1y ago

Music was never an issue of skill. You might have needed skill in order to get to the point where you could use your judgement, but skill was never the deciding factor. So, I don't agree with Brian Eno's point that there has been some kind of seismic shift when it comes to this. Rather, it's just a matter of a shift in the type of skill that you need to have. The same is probably true when it comes to AI tools within the field of programming.

drewcoo 1y ago
Getting a seat in a symphony involves skill. Brian Eno didn't just do rock.
- Tarq0n 1y ago
  Ever seen a photoshop expert at work? Every human endeavor has a skill distribution. Hammering in a nail takes skill.
- westcoast49 1y ago
  I'm just arguing that there has been no qualitative shift. The skills you need to produce pop music today are different than the skills that you needed before. Now you need to be able to operate a MIDI sequencer or a program like Ableton, which is not necessarily easier in and off itself, than for instance learning how to play a guitar. I think it's the same with AI tools and programming. We're just talking about a different set of skills that you need in order to be competitive. I don't think there has been any real shift from "skill needed" to "judgement needed". I think this relationship remains the same, both for pop music and programming, but also for the example of playing an instrument in a symphony orchestra.

Corey_ 1y ago

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physicsguy 1y ago

A similar debate has happened in education where people seem to think that having ability to critically analyse texts is more important than knowledge. and to some degree that’s true but personally I think that without building on some decent level of foundational level of knowledge and having a mental model of a subject, you can’t tackle thorny questions because you don’t have enough to draw upon as examples and counterpoints about how to proceed. My current employer is currently going on a top down driven “one tech” mission and trying to rationalise the technology stacks across diverse product lines. Which is all fine but the judgement is a poor one because the biggest developer bottleneck that comes up in internal developer surveys is the corporate mandated IT things and a relatively hostile setup without even local admin rights, which make sense for general office workers and don’t make sense at all for software developers.

Wololooo 1y ago
Reminds me of that concept that I saw pop up in HEP in recent years between "users" and "experts". This distinction in that case is so dumb I cannot wrap my head around it: You first encounter the code, are unfamiliar with it but very quickly you become expert in order to solve your problem and advance the thing forward. It does not matter which codebase you start on, what matters is that you understand what the actual stack does and what is involved in there because people are supposed to understand deeply what they are doing. But this comes from the "corporatisation" of every single entity, where random metrics are used in order to assess performance instead of asking the simple question of "does it work" or "does it need fixing" or "will this thing break". There is a clear disconnect between the manager type people that are removed from the work and the managers still doing things practically, which understand what the stressors are and where some work of deep understanding and extra contextualisation of the systems, is required, in order to not mess the whole thing up. This being said, this is coming from a very peculiar perspective and with a very specific tech stack which is and is not industry standard at many levels...
- kragen 1y ago
  High-energy physics?

wg0 1y ago

The problem is - you can't judge if you're not skilled. So still, get skilled. Learn everything first hand. Try to master it. That's how our species prevailed in the first place.

hinkley 1y ago
CERT advisories are evidence that skill is necessary but insufficient. There’s a lot of code. We get ping ponged between various sections of the code every few weeks. Other people are contributing. There’s a ton of ways code can look like it’s probably correct and not be. There are non obvious bugs everywhere, and there’s an element of luck to whether you’re in the right headspace to catch them all.

TrackerFF 1y ago

AI works great for providing you a starting point, and giving a big picture view of how certain things work, and how you should structure them. Sometimes, even if you're a really seasoned software engineer, you'll encounter something you haven't seen before. Maybe to the point that you don't really even know what to search for to get started. So instead of spending half a day scrounging various forums, e-books, etc. you can ask the model, in somewhat vague terms, what you're looking for - and some of the LLMs are quite good at just that. Now, the implementation of such things, not quite there yet. My experience has been that the more obscure the problems you deal with, the more obsolete code the model will spit out - with dead and unsupported libraries etc.

dwoldrich 1y ago

AI enables me to gold plate _everything_ I do, which feels exhilarating, if a bit exhausting. Having decent taste and being able to continuously test and verify my work allows me to smooth over the occasional hallucinations and elicit towering, mind-bending solutions. AI's no replacement for experience; garbage in-garbage out. When AI gets too good, I figure people will cloister to stop feeding the beast. It can only lead to ignorance and misery, I fear.

kragen 1y ago
Can you elaborate? What kinds of things are you doing, maybe something related to programming? What part of the job do you delegate?
- dwoldrich 1y ago
  Not delegating, just tricking everything I develop out far more than I would have in the past. I'm on yet another hodgepodge project in a looong, decades long series of hodge and podge. AI is letting me begin to answer to my own satisfaction, "what does it look like to do everything to the best of my ability?" In my current gig, I have an on-prem database and legacy application that is human-powered software, where parts of the business process never touch the computer and a human does the work (mostly support stuff), (and for no good reason other than this system never had real engineering support.) So, I joined the team, and started to wrangle the system. First thing I was asked to do was get their database code and schema into source control with managed releases. The gold plating process that I never would have entertained in the past led me to get a migration tool installed, get a unit test engine installed in the database and writing new code with tests, figure out even how to refactor the big ball of mud and coming up with patterns there, doing github workflows to run the tests and deploy to multiple environments, linters, Slack alerts. It's not that I wasn't aware of all these things, I just never would have done all of them _to the extent_ that I did because the time needed to research it all traditionally and spike the solutions would have been too great. And I documented it all! After the databases were basically under control and I had gained the team's trust, I moved the team to start automating the human-powered parts of the software. We started an admin console webapp project. Again, I was heavy into AI all along the way, even during requirements elicitation. Our data is a rube goldberg machine of cloud and on-prem, but the majority of what we need to get under control is legacy/on-prem. We want the webapp to eventually be hosted in the cloud, but to be close to our databases and not have to fuss with private links, we decided for starters to deploy the webapp on-prem next to them. So, that meant figuring out how to get our github builds deployed on-prem. There was this huge saga in figuring out how to provision an on-prem GitHub Runner and use Powershell Remoting to fan out our deployments from there to all of the on-prem servers. Never EVER would I have been able to figure out the permissions and powershell provisioning steps needed to pull that off. It's all very gross, Windows is gross, but what we've built works dependably and is secure. I probably would have just used Samba or some other cheesy way to move files around and trigger deployments if I didn't have AI to bounce all these ideas off of. Another example: we wanted our BFF microservices to eventually deploy as Azure Functions, so gold plating meant we had to figure out how to build and deploy functions on-prem. It ended up being very productive, but again I would have never entertained doing such a thing unless I could bounce my ideas off AI and get credible directions on how to proceed. Instead, I would have written the service as trusty/crusty old Express 4.x and ported the code to Functions once we made the jump to cloud. I am saving future me a ton of work and heartburn! At every step AI is giving me the latitude to ask, given whatever nasty situation I'm in, what would be the best code/most secure/nicest architecture in that case? It's arduous to continually pepper it with questions and spend many days zeroing in on a final solution with it. But, it beats the guessing game of searching DuckDuckGo, StackOverflow, and software vendors' documentation - those are now the _last_ places I look for answers. (For ill, I'm sure.)

overfl0w 1y ago

This reminds me of Asimov's Jokester story where the same themes are explored - there is an all-knowing computer but someone needs to ask the correct questions. "Early in the history of Multivac, it had become apparent that the bottleneck was the questioning procedure. Multivac could answer the problem of humanity, all the problems, if it were asked meaningful questions. But as knowledge accumulated at an ever-faster rate, it became ever more difficult to locate those meaningful questions. Reason alone wouldn't do. What was needed was a rare type of intuition; the same faculty of mind (only much more intensified) that made a grand master at chess. A mind was needed of the sort that could see through the quadrillions of chess patterns to find the one best move, and do it in a matter of minutes."

stopthe 1y ago
That chess metaphor didn't age well
- Jensson 1y ago
  That is the goal post moving, its done by AI optimists that thinks "we just need something that can solve X and it will be as smart as a human expert". Wasn't true for chess, wasn't true for Go, we will see when its true, but they are constantly moving the goalposts and then arguing its others who are moving it.

layer8 1y ago

When your judgement tells you “this is wrong”, you may need the technical skill to know what instead is right. The real question is when AI will surpass the average human in both judgement and technical skill.

k__ 1y ago

I think, the argument would make more sense if software like Cubase came with unlicenced samples from all songs out of the box. Artists sued and won when someone used their samples without permission. If you use AI to create art, it's like that.

CuriouslyC 1y ago
There's a difference between a sample and something inspired by something but also significantly different. The copyright laws around music are kind of draconian so it's not a good analogy for code anyhow, imagine a world where a fundamental do while loop had 90 year copyright protection, and that's the sort of world we'd be living in if code copyright was like music copyright.
- k__ 1y ago
  If you see the generated content as "the music that's created with unlicenced samples" that's true. However, if you see the trained models as "the music that's created with unlicenced samples" it isn't true.

lordnacho 1y ago

Judgement and technical skill go hand in hand. Technology merely moves the boundary of what is considered judgement, and what is considered technical skill. I know someone who wrote programs in the punch-card era. Back then, technical skill meant being diligent and thoughtful enough that you avoided most bugs when writing the program. If you screwed this up, you had to wait for another time slot. What does this mean for the complexity of programs you could write? Well, it means you are quite limited. You can't build judgement about things above what is now considered a very basic program. I learned to program before the AI era that seems to be nascent. Technical skill means things like being able to write programs in python and c++, getting many computers to work together, being able to find hints when something goes wrong, and so on. Judgement now covers things like how a large swarm of programs interact, which was not really in scope for punch-card guy. Now AI arrives, and it appears that we are free from technical skill problems. Indeed, it does fix a lot of my little syntax issues, but actually it just moves the goalposts. There's soon going to be no excuse for spending time working out the syntax for a lambda function, you'll be expected to generate a much more complicated product, for which you will need an even higher overview to say you are providing judgement.

4b11b4 1y ago

Yeah but, you can't make a judgement in these technical areas without the technical skill... No?

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red_admiral 1y ago

And what is that judgement based on? Jobs that an AI can't do yet, like designing a system architecture and drawing boundaries (which features go in the same service), need someone with experience. We can apply this to all points in the Future of Work section. Even the conclusion "What should you do, and why?" is basically a disguised "What domain-specific knowledge do you have to make an informed opinion on the 'why' anyway?"

giordanol 1y ago

The tooling problem is 90% solved. The new technical bottleneck is human judgment.

somewhereoutth 1y ago

"Anyone with access to AI tools can now produce work that, _at least superficially_, resembles professional output." Key quote, emphasis mine.

z3t4 1y ago

It takes skill to see the beauty

0x445442 1y ago

Writing musical notation doesn't strike me as technically difficult but I'm unaware of any musical composers who weren't proficient in at least one instrument. Good judgement is only accessible to those who've invested considerable time in the rudiments.

curtisszmania 1y ago

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financypants 1y ago

Have people noticed the ai-assisted code "creep"? Cursor now by default applies its changes before you've even hit accept, and the tab autocomplete is getting out of control. Sometimes I'll have my cursor resting on some block of code, then suddenly Cursor suggests I delete the whole thing.

tingle 1y ago

Chap. CCCLXIV. — On the Judgment of Painters. When the work is equal to the knowledge and judgment of the painter, it is a bad sign; and when it surpasses the judgment, it is still worse, as is the case with those who wonder at having succeeded so well. But when the judgment surpasses the work, it is a perfectly good sign ; and the young painter who possesses that rare disposition, will, no doubt, arrive at great perfection. He will produce few works, but they will be such as to fix the admiration of every beholder. Leonardo da Vinci, "A Treatise on Painting.", p. 225 https://archive.org/details/davincionpainting00leon/page/224/mode/2up https://archive.org/details/davincionpainting00leon/page/224...

gavmor 1y ago
> Nobody tells this to people who are beginners, I wish someone told me. All of us who do creative work, we get into it because we have good taste. But there is this gap. For the first couple years you make stuff, it’s just not that good. It’s trying to be good, it has potential, but it’s not. But your taste, the thing that got you into the game, is still killer. And your taste is why your work disappoints you. A lot of people never get past this phase, they quit. Most people I know who do interesting, creative work went through years of this. We know our work doesn’t have this special thing that we want it to have. We all go through this. And if you are just starting out or you are still in this phase, you gotta know its normal and the most important thing you can do is do a lot of work. Put yourself on a deadline so that every week you will finish one story. It is only by going through a volume of work that you will close that gap, and your work will be as good as your ambitions. And I took longer to figure out how to do this than anyone I’ve ever met. It’s gonna take awhile. It’s normal to take awhile. You’ve just gotta fight your way through. (Ira Glass)
- ChrisMarshallNY 1y ago
  I like to do a good job on small stuff. It works nicely for me, but doesn't really bring accolades (but a hell of a lot of folks actually rely on stuff I authored; they just don't know it, or care -which is just fine).
  - 1y ago

smithkl42 1y ago

This doesn't actually sound encouraging. Judgment is not actually independent of skill, and the sort of music that this approach produces (i.e., nearly everything you hear on the radio these days) is a pretty solid proof of that.

metalrain 1y ago

I think what and how are so tightly linked, you need to know how to make a thing so you better know what thing to make. Let's say you want to build worlds fastest car. You can order the pieces and maybe build a car from someones instructions. But to know what makes car fast and how to build it you need to know more and more intricate details. Physics, material science, 3D printing, engineering. How do you measure traction? What shapes increase downforce? That is how I see AI tools. You can get "off the shelf" ideas on different things, even complete small things, but you really need to be or grow to match the challenge you are facing.

nluken 1y ago

A side note to the general point of the article, but I hate how the tech industry uses the word "democratization" to mean "lowering the barrier to entry". These concepts differ from each other but many use the former term because in doing so they justify their actions as driven by some sort of moral imperative when in reality, the development of LLMs is morally neutral, not inherently bad by any stretch, but as much a wealth and power play as any other technology of the last 25 years.

greg7gkb 1y ago
I agree with you however I've also not found a better substitute. Any candidates?
- neochief 1y ago
  Commoditization.

scj 1y ago

AI can draw blueprints of a house. The house may look aesthetically pleasing, but if it can't hold it's own weight, the design is flawed. There's a difference between an executed image and a display-only image. At a certain point, judgment requires technical knowledge.

aaron695 1y ago
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keybored 1y ago

Very thin article. The thesis might as well be that technical competence is gone and judgement is all that’s left. I file this under the category of AI musings on the inevitable massively changed landscape that AI has wrought.[1] I get the feeling that the content itself is secondary (again: the thesis is thin) to the motivation of writing about how AI has supposedly changed everything forever. In this case: now technical competence is dead, hail the king (judgement or whatever). [1] “I’m learning that every topic that people read should be about AI.” : https://news.ycombinator.com/item?id=44082683 https://news.ycombinator.com/item?id=44082683

dcre 1y ago

The Eno quote is good, but the post adds nothing to it! If anything, I think the sections after the quote make the post worse. This shows poor judgment on the part of the author.

catigula 1y ago

I love these little anecdotes because they always pre-suppose that everyone - the writer, of course, but also the reader - themselves are the people who don't lack judgment, which is a role they relegate to, perhaps, a particularly incompetent co-worker, or even unknown and faceless "drudge". Which is to say that there's an obvious affliction of narcissism at work that precludes good judgment.

gwd 1y ago

I agree with the premise; but the lists sound suspiciously AI-like. "Understanding what's worth making in the first place": Pretty good "Evaluating quality": Could be a lot better.

ashley1121 1y ago

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