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Let's properly analyze an AI article for once
- righthand 1y agoThis was excellent!
- croes 1y agoThe statistics part will also be relevant for the rest of Trump‘s presidency
- ma73me 1y agoI'll never judge an article by its HN header again
- vunderba 1y agoSpot on critical analysis of the blog post "Developers reinvented" by Github Thomas Dohmke which includes such quotes as: > Many Computer Science (CS) programs still center around problems that AI can now solve competently. Yeah. No they do not. Competent CS programs focus on fundamentals not your ability to invert a binary tree on a whiteboard. [1] Replacing linear algebra and discrete mathematics with courses called "Baby's First LLM" and "Prompt Engineering for Hipster Doofuses" is as vapid as proposing that CS should include an entire course on how to use git. [1] https://x.com/mxcl/status/608682016205344768 https://x.com/mxcl/status/608682016205344768
- charcircuit 1y ago>not your ability to invert a binary tree on a whiteboard. Knowing how to swap 2 variables and traverse data structures are fundamentals.
- kubb 1y agoI’m surprised that the creator of Homebrew didn’t know how to do that.
- meindnoch 1y agoIf you spend enough time with Homebrew, it's actually not that surprising.
- josephg 1y agoOf course, lots of people are employed despite giant holes in their knowledge of CS fundamentals. There’s more to being an effective developer than having good fundamentals. A lot more. But there’s still a lot of very important concepts in CS that people should learn. Concepts like performance engineering, security analysis, reliability, data structures and algorithms. And enough knowledge of how the layers below your program works that you can understand how your program runs and write code which lives in harmony with the system. This knowledge is way more useful than a lot of people claim. Especially in an era of chatgpt. If you’re weak on this stuff, you can easily be a liability to your team. If your whole team is weak on this stuff, you’ll collectively write terrible software.
- meindnoch 1y agoAlso, what people fail to realize is that the whiteboard coding interview was never about testing skills that are necessary for your day to day work. Most fighter pilots don't fly missions that require superhuman reaction time or enduring 9.5g acceleration either. Whiteboard coding exercises are just a proxy for certain thinking skills, a kind of je ne sais quoi that successful engineers tend to have.
- nradov 1y agoAlternatively, whiteboard coding exercises are a hazing mechanism to weed out candidates who have certain forms of anxiety or can't perform well under extreme scrutiny and time pressure. Which could be valid selection criteria for certain jobs. But let's be honest and admit that whiteboard coding exercises aren't actually a proxy for anything else, or at least we have no scientific evidence on that point.
- QuadmasterXLII 1y ago
- funcDropShadow 1y agoThe goal of teaching binary trees is not that you can write binary trees in your sleep, the goal is that you train your ability to derive algorithms and data structures. If you look at what a world class soccer player does during training, most of it will never be applied identically during games. The same is true for university studies, if they focus on fundamentals.
- thrown-0825 1y agoComputer Science in academia is pretty out of line with a lot of skills that are actually used on a daily basis by professional software developers. You can teach fundamentals all day long, but on their first day of work they are going to be asked adhere to some internal corporate process that is so far removed from their academic experience that they will feel like they should have just taught themselves online.
- meindnoch 1y ago>Computer Science in academia is pretty out of line with a lot of skills that are actually used on a daily basis by professional software developers. 80% of software development boils down to: 1. Get JSON(s) from API(s) 2. Read some fields from each JSON 3. Create a new JSON 4. Send it to other API(s) Eventually people stopped pretending that you need a CS degree for this, and it spawned the coding bootcamp phenomenon. Alas it was short-lived, because ZIRP was killed, and as of late, we realized we don't even need humans for this kind of work!
- thrown-0825 1y agoAnd they were right. We no longer hires junior engineers because it just wasn't worth the time to train them anymore.
- Esophagus4 1y agoI’ll challenge that assumption. All of my rock star engineers have CS degrees OR are absolute savants of computer science who taught themselves. They solve problems, not just write CRUD apps. I don’t want people who only have surface level knowledge of calling JSON APIs. They tend to be a serious drag on team productivity, and high performers don’t want to work with them.
- SilasX 1y agoI would also include: 5. Debug why the API's don't behave as documented and figure out a workaround.
- astrobe_ 1y ago
- Gigachad 1y agoSchools still make you manually understand math even though calculators have been perfect for decades. Because it turns out having some magic machine spit out an answer you can’t understand isn’t good and you’ll have no ability to understand when and why the answer is incorrect.
- jacquesm 1y agoI think until the third year of high school you should do without a calculator. There really is no substitute for being able to do basic math in your head. It also helps you to later on spot order of magnitude errors and such, as well as to do good first order of approximation estimates.
- dleeftink 1y agoI'm a bit different then, maths only started to make sense well after picking up a calculator; Wolfram notebooks, Excel and SQL were much easier for me to grok than attempting the equivalent by heart/head/hand. Nowadays, math concepts or papers only makes sense when I can properly implement them as query, it's somehow a basic translation step I need.
- wrs 1y agoIn my ninth grade physics class we had to use a slide rule to do calculations for the first three months to help develop that intuition for orders of magnitude. Also because our teacher was just tired of people reporting results to nine significant figures for measurements they made with a meter stick.
- cratermoon 1y agoOh yeah learning to use slide rule is like a superpower when it comes to understanding orders of magnitude and significant figures. It's also a great way to become very comfortable with logarithms.
- xg15 1y agoI found Factorio being a good paradigm for that. The core game loop is essentially: "Do a task manually, then automate it; then do a higher-level task manually that only became feasible through the automation; then automate that as well, etc etc". But throughout the game, you often drop back down into the lower level tasks, e.g. to understand problems or change the workflow. So in the end an understanding of the entire "stack" of tasks on different abstraction levels is necessary to make progress. This always felt like a good analogy to programming, or really scientific knowledge in general.
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- fspeech 1y agoUnfortunately the writer's own understanding of statistics is flawed. For example sample size has not much to do with population size but a lot to do with effect size. For example to demonstrate that a chemical is fatal often a sample size of 1 is sufficient. Population comes into play if there is a large variance of the effect relative to the average size of the effect. You need a good statistical sampling of the population to study the variance but even here sample size if not determined by population size.
- sixhobbits 1y ago> The sample size is 22. According to this sample size calculator I found, a required sample size for just one thousand people would be 278 I'm all for criticizing a lack of scientific rigor, but this bit pretty clearly shows that the author knows even less about sample sizes than the GitHub guy, so it seems a bit pot calling the kettle black. You certainly don't need to sample more than 25% of any population in order to draw statistical information from it. The bit about running the study multiple times also seems kinda random. I'm sure this study of 22 people has a lot of room for criticism but this criticism seems more ranty than 'proper analysis' to me.
- foma-roje 1y ago> You certainly don't need to sample more than 25% of any population in order to draw statistical information from it. Certainly? Now, who is ranting?
- brabel 1y agoIt’s a basic property of statistics. You need an extremely varied population to need a sample of 25%, and almost no human population is that varied in practice. Humans are actually very uniform in fact.
- integralid 1y agoWhat if the group is 8 people
- astrobe_ 1y ago> The bit about running the study multiple times also seems kinda random. Reproducibility? But knowing it comes from the CEO of Github, who has vested interests in that matter because AI is one of the things that will allow to maintain Github's position on the market (or increase revenue of their paid plans, once everyone is hooked on vibe coding etc.), anyone would anyway take it with a grain of salt. It's like studies funded by big pharma.
- pcwelder 1y ago>I found, a required sample size for just one thousand people would be 278 It's interesting to note that for a billion people this number changes to a whopping ... 385. Doesn't change much. I was curious, with 22 sample size (assuming unbiased sample, yada yada), while estimating the proportion of people satisfying a criteria, the margin of error is 22%. While bad, if done properly, it may still be insightful.
- HarHarVeryFunny 1y ago> This helps explain the – perhaps unintuitive at first – observation that many of the developers we interviewed were paying for top-tier subscriptions. It doesn't sound like an unbiased sample.
- ethan_smith 1y agoSample size requirements are primarily determined by desired confidence level and margin of error rather than population size, which explains why the required sample barely changes between 1,000 and 1 billion people.
- NoahZuniga 1y agoIt's a bit annoying that this article on AI is hallucinating itself: > To add insult to injury, the image seems to have been created with the Studio Ghibli image generator, which Hayao Miyazaki described as an abomination on art itself. He never said this. This is just false, and it seems like the author didn't even fact check if Hayao Miyazaki ever said this.
- tough 1y agoRight it was an out of context presentation of their own company and some very rough AI generated content and years ago before the existence of LLMs but yeah sensationalism and all and people don't do research so unless you remember well and also lost in translation from Japanese to English, the work sampled by their engineers, it depicted some kinda of zombie like pictures in a very rough form, thus the -insult to life- as in literally
- meindnoch 1y agoContext: https://youtu.be/ngZ0K3lWKRc https://youtu.be/ngZ0K3lWKRc Miyazaki is repulsed by an AI-trained zombie animation which reminded him of a friend with disabilities. So the oft quoted part is about that zombie animation. When he the team tells him that they want to build a machine that can draw pictures like humans do, he doesn't say anything just stares.
- vemv 1y ago> Said person does not give a shit about whether things are correct or could even work, as long as they look "somewhat plausible". Spot on, I think this every time I see AI art on my Linkedin feed.
- pacifika 1y agoIsn’t this just the digital version of hand waving / guesswork? People not checking assumptions have long since been a leading cause of weak software delivery.
- Gigachad 1y agoI’ve become super sensitive to spotting it now. When I see a restaurant using AI food pictures I don’t want to eat there. Why would I want to do business with people who are so dishonest to lie about the basics?
- thrown-0825 1y agousing food pics as an example is hilarious, food photos in advertising have been "faked" for about as long as photography has existed
- Gigachad 1y agoSure, they went through a long process of dressing them up as nice as possible. But they were still just ideal versions of the thing you actually receive. While the AI food looks pretty much nothing like what the restaurant is actually making. And outside of mega chains like McDonalds, most restaurants used fully real images.
- thrown-0825 1y agoThis is provably false. There is a large industry based around faking food, you can watch some pretty interesting videos on the process and you will quickly find that they rarely use anything resembling the actual food you will be eating. Japan is an extreme example, but there they literally use wax models to advertise their food.
- bgwalter 1y ago"AI" could certainly replace Dohmke. It excels at writing such meaningless articles.
- rsynnott 1y ago> Said person does not give a shit about whether things are correct or could even work, as long as they look "somewhat plausible". This seems to be the fundamental guiding ideology of LLM boosterism; the output doesn't actually _really_ matter, as long as there's lots of it. It's a truly baffling attitude.
- Gigachad 1y agoThey always market the % of lines generated by AI. But if you are forced to use a tool that constantly inserts generations, that number is always going to be high even if the actual benefit is nil or negative. If the AI tool generates a 30 line function which doesn’t work. And you spend time testing and modifying the 3 lines of broken logic. The vast majority of the code was AI generated even if it didn’t save you any time.
- diggan 1y ago> They always market the % of lines generated by AI That's crazy, should really be the opposite. If someone releases weights that promises "X% less lines generated compared to Y", I'd jump on that in an instant, more LLMs are way too verbose by default. Some are really hard to even use prompts to get them to be more concise (looking at you, various Google models)
- 986aignan 1y agoIt is possible to take this too far, though - consider the OpenAI IMO proofs[1], for instance, and compare them to Gemini's.[2] [1] https://github.com/aw31/openai-imo-2025-proofs https://github.com/aw31/openai-imo-2025-proofs [2] https://arxiv.org/pdf/2507.15855 https://arxiv.org/pdf/2507.15855 Appendix A
- thrown-0825 1y agoAll of the crypto grifters have shifted to AI. Fundamentals don't matter anymore, just say whatever you need to say to secure the next round of funding.
- crinkly 1y agoProfessional statistician here. Not that I get to do any of that these days, bar read Significance magazine and get angry occasionally. Looking at the original blog post, it's marketing copy so there's no point in even reading it. The conclusion is in the headline and the methodology is starting with what you want to say and working back to supporting information. If it was in a more academic setting it would be the equivalent of doing a meta-analysis and p-hacking your way to the pre-defined conclusion you wanted. Applying any kind of rigour to it is pointless but thanks for the effort.
- nhinck3 1y agoThis isn't the first time Github (or it's CEO) has produced a completely garbage article about the wonders of AI and it won't be the last.
- skywhopper 1y ago“ It was reposted with various clickbait headings like GitHub CEO Thomas Dohmke Warns Developers: ‘Either Embrace AI or Get Out of This Career’ ” Is it clickbait if it’s literally quoting the author? I mean, yes, it was clickbait by Thomas Dohmke, but not by the source that used that headline.
- saulpw 1y agoApparently it's not a quote by the author, but a participant.
- quantum_state 1y agoif history is of reference, vibe coding would turn out to be the most effective tool to produce technical debt …
- tempodox 1y agoIf history is any indication, too few will care to make a difference.
- RugnirViking 1y agoA near insurmountable amount of problems and technical debt are due to be created in problems teams. Sounds like a great time to get into consulting. It's like knowing that y2k is coming up ahead of time. Learn your debuggers and your slide decks folks
- jmull 1y agoTechnical debt will have a strong negative impact on a project/product over time if left unresolved (if it doesn't, it probably isn't really something we should call technical debt). That is, technical debt matters whether anyone cares about it or not.
- righthand 1y agoAs a junior engineer I don’t care about technical debt and instead will push that we should rewrite the app so the new wave of employees can understand it. Convincing my manager and leadership of this is 100x easier with generated code. I get approval and generate a new stack of tech debt that I try to pass to the next wave of employees.
- bsenftner 1y agoThis analysis is not complete, it needs to continue with an analysis of how many people, and critically how many business owners, believe the lies and non-truths propagandized by that article and the entire marketing push of LLMs. That article is not for developers, it's for the business owner, their management, and the investor class. If they believe it, they will try to enforce it. This is serious, destroy our industry type of idiot logic.
- overgard 1y agoOne thing that seems to always get lost in the AI hype cycle is actually screening articles by the source. Maybe it's just because in this age of social media we don't have much in the way of journalism. I have zero interest in what Sam Altman, Dario Amodei, Thomas Dohmke, etc. have to say because they obviously want to sell something.
- EverydayBalloon 1y ago[dead]
- card_zero 1y agoThe Miyazaki quote get taken out of context and altered. It was "an insult to life itself", not "an abomination on art itself", and the context was creepy AI animations of zombies. He said that he won't use the technology, but the implied reason was because he saw a crass demo. "Whoever creates this stuff has no idea what pain is." https://en.wikiquote.org/wiki/Hayao_Miyazaki https://en.wikiquote.org/wiki/Hayao_Miyazaki
- nailer 1y agoOriginal video - yes the AI content looks like silent hill type visions: https://youtu.be/ngZ0K3lWKRc?si=t5uzOZDJZ5DPrRCU https://youtu.be/ngZ0K3lWKRc?si=t5uzOZDJZ5DPrRCU
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