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I completely agree. On a side note.. ya’ll must be prompt wizards if you can actually use the LLM code. I use it for debugging sometimes to get an idea, or a
by moi2388 1y ago
I completely agree.
On a side note.. ya’ll must be prompt wizards if you can actually use the LLM code.
I use it for debugging sometimes to get an idea, or a quick sketch up of an UI.
As for actual code.. the code it writes is a huge mess of spaghetti code, overly verbose, with serious performance and security risks, and complete misunderstanding of pretty much every design pattern I give it..
- herpdyderp 1y agoThe bigger the task, the more messy it'll get. GPT5 can write a single UI component for me no problem. A new endpoint? If it's simple, no problem. The risk increases as the complexity of the task does.
- JustExAWS 1y agoI break complex task down into simple tasks when using ChatGPT just like I did before ChatGPT with modular design.
- infecto 1y agoI agree with the article but also believe LLM coding can boost my productivity and ability to write code over long stretches. Sure getting it to write a whole feature, high opportunity of risk. But getting it to build out a simple api with examples above and below it, piece of cake, takes a few seconds and would have taken me a few minutes.
- eloisius 1y agoI agree. AI is a wonderful tool for making fuzzy queries on vast amounts of information. More and more I'm finding that Kagi's Assistant is my first stop before an actual search. It may help inform me about vocabulary I'm lacking which I can then go successfully comb more pages with until I find what I need. But I have not yet been able to consistently get value out of vibe coding. It's great for one-off tasks. I use it to create matplotlib charts just by telling it what I want and showing it the schema of the data I have. It nails that about 90% of the time. I have it spit out close-ended shell scripts, like recently I had it write me a small CLI tool to organize my Raw photos into a directory structure I want by reading the EXIF data and sorting the images accordingly. It's great for this stuff. But anything bigger it seems to do useless crap. Creates data models that already exist in the project. Makes unrelated changes. Hallucinates API functions that don't exist. It's just not worth it to me to have to check its work. By the time I've done that, I could have written it myself, and writing the code is usually the most pleasurable part of the job to me. I think the way I'm finding LLMs to be useful is that they are a brilliant interface to query with, but I have not yet seen any use cases I like where the output is saved, directly incorporated into work, or presented to another human that did not do the prompting.
- nwienert 1y agoHave you tried Opus? It's what got me past using LLMs only marginally. Standard disclaimers apply in that you need to know what it's good for and guide it well, but there's no doubt at this point it's a huge productivity boost, even if you have high standards - you just have to tell it what those standards are sometimes.
- collingreen 1y agoOpus was also the threshold for me where I started getting real value out of (correctly applied) LLMs for coding.
- eatsyourtacos 1y agoSounds like you are using it entirely wrong then... Just yesterday I uploaded a few files of my code (each about 3000+ lines) into a gpt5 project and asked in assistance in changing a lot of database calls into a caching system, and it proceeded to create a full 500 line file with all the caching objects and functions I needed. Then we went section through section of the main 3000+ line file to change parts of the database queries into the cached version. [I didn't even really need to do this, it basically detected everything I would need changing at once and gave me most of it, but I wanted to do it in smaller chunks so I was sure what was going on] Could I have done this without AI? Sure.. but this was basically like having a second pair of eyes and validating what I'm doing. And saving me a bunch of time so I'm not writing everything from scratch. I have the base template of what I need then I can improve it from there. All the code it wrote was perfectly clean.. and this is not a one off, I've been using it daily for the last year for everything. It almost completely replaces my need to have a junior developer helping me.
- lubesGordi 1y agoI know, I don't understand what problems people are having with getting usable code. Maybe the models don't work well with certain languages? Works great with C++. I've gotten thousands of lines of clean compiling on the first try and obviously correct code from ChatGPT, Gemini, and Claude. I've been assuming the people who are having issues are junior devs, who don't know the vocabulary well enough yet to steer these things in the right direction. I wouldn't say I'm a prompt wizard, but I do understand context and the surface area of the things I'm asking the llm to do.
- Tiktaalik 1y agoFrom my experience the further you get from the sort of stuff that easily accessible on Stack Overflow the worse it gets. I've had few problems having an AI write out some minor python scripts, but yield severely poorer results with Unreal C++ code and badly hallucinate nonsense if asked in general anything about Unreal architecture and API.
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- uh_uh 1y agoWhich model?
- foxyv 1y agoThe one thing I've found AI is good at is parsing through the hundreds of ad ridden, barely usable websites for answers to my questions. I use the Duck Duck Go AI a lot to answer questions. I trust it about as far as I can throw the datacenter it resides in, but it's useful for quickly verifiable things. Especially stuff like syntax and command line options for various programs.
- oblio 1y ago> The one thing I've found AI is good at is parsing through the hundreds of ad ridden, barely usable websites for answers to my questions. One thing I can guarantee you is that this won't last. No sane MBA will ignore that revenue stream. Image hosting services, all over again.
- foxyv 1y agoYou are entirely correct. The enshittification will continue. All we can do is enjoy these things while they are still usable.
- benatkin 1y agoNope, this only applies to a small percent of content, where a relatively small number of people needs access to it and the incentive to create derivative work based on it is low, or where there's a huge amount of content that's frequently changing (think airfares). But yes, they will protect it more. For content that doesn't change frequently and is used by a lot of people it will be hard to control access to it or derivative works based on it.
- baggachipz 1y agoI don't think you're considering the enshittification route here. I'm sure it will be: Ask ChatGPT a question -> "While I'm thinking, here's something from our sponsor which is tailored to your question" -> lame answer which requires you to ask another question. And on and on. While you're asking these questions, a profile of you is built and sold on the market.
- JeremyNT 1y agoWhat tooling are you using? I use aider and your description doesn't match my experience, even with a relatively bad-at-coding model (gpt-5). It does actually work and it does generate "good" code - it even matches the style of the existing code. Prompting is very important, and in an existing code base the success rate is immensely higher if you can hint at a specific implementation - i.e. something a senior who is familiar with the codebase somewhat can do, but a junior may struggle with. It's important to be clear eyed about where we are here. I think overall I am still faster doing things manually than iterating with aider on an existing code base, but the margin is not very much, and it's only going to get better. Even though it can do some work a junior could do, it can't ever replace a junior human... because a junior human also goes to meetings, drives discussions, and eventually becomes a senior! But management may not care about that fact.
- brushfoot 1y agoI read AI coding negativity on Hacker News and Reddit with more and more astonishment every day. It's like we live in different worlds. I expect the breadth of tooling is partly responsible. What it means to you to "use the LLM code" could be very different from what it means to me. What LLM are we talking about? What context does it have? What IDE are you using? Personally, I wrote 200K lines of my B2B SaaS before agentic coding came around. With Sonnet 4 in Agent mode, I'd say I now write maybe 20% of the ongoing code from day to day, perhaps less. Interactive Sonnet in VS Code and GitHub Copilot Agents (autonomous agents running on GitHub's servers) do the other 80%. The more I document in Markdown, the higher that percentage becomes. I then carefully review and test.
- skydhash 1y ago> Personally, I wrote 200K lines of my B2B SaaS That would probably be 1000 line of Common Lisp.
- throwmeaway222 1y ago[flagged]
- oblio 1y agoWhat tech stack do you use? Betting in advance that it's JavaScript or Python, probably with very mainstream libraries or frameworks.
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- lbrito 1y agoIt's one of those you get what you put in kind of deals. If you spend a lot of time thinking about what you want, describing the inner workings, edge cases, architecture and library choices, and put that into a thoughtful markdown, then maybe after a couple of iterations you will get half decent code. It certainly makes a difference between that and a short "implement X" prompt. But it makes one think - at that point (writing a good prompt that is basically a spec), you've basically solved the problem already. So LLM in this case is little more than a glorified electric typewriter. It types faster than you, but you did most of the thinking.
- jeremyjh 1y agoRight, and then after you do all the thinking and the specs, you have to read and understand and own every single line it generated. And speaking for myself, I am no where near as good at thinking through code I am reviewing as thinking through the code I am writing. Other people will put up PRs full of code they don't understand. I'm not saying everyone who is reporting success with LLMs are doing that, but I hear it a lot. I call those people clowns, and I'd fire anyone who did that.
- flatline 1y agoIf it passes the unit tests I make it write and works for my sample manual cases I absolutely will not spend time reading the implementation details unless and until something comes up. Sometimes garbage makes its way into git but working code is better than no code and the mess can be cleaned up later. If you have correctness at the interface and function level you can get a lot done quickly. Technical debt is going to come out somewhere no matter what you do.
- bdcravens 1y agoI haven't had that experience, but I tend to keep my prompts very focused with a tightly limited scope. Put a different way, if I had a junior or mid level developer, and I wanted them to create a single-purpose class of 100-200 lines at most, that's how I write my prompts.
- IT4MD 1y agoLikewise with Powershell. It's good to give you an approach or some ideas, but copy/paste fails about 80% of the time. Granted, I may be a inexpert prompter, but at the same time, I'm asking for basic things, as a test, and it just fails miserably most of the time.
- tempodox 1y agoIt's just that being the dumbest thing we ever heard still doesn't stop some people from doing it anyway. And that goes for many kinds of LLM application.
- panny 1y agoI think it has a lot to do with skill level. Lower skilled developers seem to feel it gives them a lot of benefit. Higher skilled developers just get frustrated looking at all the errors in produces.
- larodi 1y agoI must be a prompt wizard then.
- threecheese 1y agoI hate to admit it, but it is the prompt (call it context if ya like, includes tools). Model is important, window/tokensz are important, but direction wins. Also codebase is important, greenfield gets much better results, so much so that we may throw away 40 years of wisdom designed to help humans code amongst each other and use design patterns that will disgust us.
- shaunxcode 1y ago“we”
- m3kw9 1y agoNot only a prompt wizard, you need to know what prompts are bad or good and also use bad/lazy prompts to your advantage
- platevoltage 1y agoThis is exactly how I use it.
- chrischen 1y agoThe AI agents tend to fail for me with open ended or complex tasks requiring multiple steps. But I’ve found it massively helpful if you have these two things: 1) a typed language… better if strongly typed 2) your program is logically structured and follows best practices and has hierarchical composition. The agents are able to iterate and work with the compiler until it gets it right and the combination of 1 and 2 means there’s fewer possible “right answers” to whatever problem I have. If i structure my prompte to basically fill in the blanks of my code in specific areas it saves a lot of time. Most of what I prompt is something already done, and usually 1 google search away. This saves me the time to search it up, figure out whatever syntax I need, etc.
- paulddraper 1y ago> ya’ll must be prompt wizards Thank you, but I don’t feel that way. I’d ask you a lot of details…what tool, what model, what kind of code. But it’d probably take a lot to get to the bottom of the issue.
- AIorNot 1y agoI’ve built 2 SaaS applications with LLM coding one of which was expanded and release to enterprise customers and is in good use today - note I’ve got years of dev experience and I follow context and documentation prompts and I’m using common LLM languages like typescript and python and react and AWS infra Now it requires me to fully review all code and understand what the LLM is doing at the functional, class level and api level- in fact it works better at the method or component level for me and I had a lot of cleanup work (and lots of frustration with the models) on the codebase but overall there’s no way that I could equal the velocity I have now without it
- bmcahren 1y agoI think the other important step is to reject code your engineers submit that they can't explain for a large enterprise saas with millions of lines of code. I myself reject I'd say 30% of the code the LLMs generate but the power is in being able to stay focused on larger problems while rapidly implementing smaller accessory functions that enable that continued work without stopping to add another engineer to the task. I've definitely 2-4X'd depending on the task. For small tasks I've definitely 20X'd myself for some features or bugfixes.
- conradfr 1y agoAfter all the exciting part of coding has always been code reviews.
- kstenerud 1y agoI just had Claude Sonnet 4 build this for me: https://github.com/kstenerud/orb-serde https://github.com/kstenerud/orb-serde Using the following prompt: Write a rust serde implementation for the ORB binary data format. Here is the background information you need: * The ORB reference material is here: https://github.com/kstenerud/orb/blob/main/orb.md * The formal grammar dscribing ORB is here: https://github.com/kstenerud/orb/blob/main/orb.dogma * The formal grammar used to describe ORB is called Dogma. * Dogma reference material is here: https://github.com/kstenerud/dogma/blob/master/v1/dogma_v1.0.md * The end of the Dogma description document has a section called "Dogma described as Dogma", which contains the formal grammar describing Dogma. Other important things to remember: * ORB is an extension of BONJSON, so it must also implement all of BONJSON. * The BONJSON reference material is here: https://github.com/kstenerud/bonjson/blob/main/bonjson.md * The formal grammar desribing BONJSON is here: https://github.com/kstenerud/bonjson/blob/main/bonjson.dogma Is it perfect? Nope, but it's 90% of the way there. It would have taken me all day to build all of these ceremonious bits, and Claude did it in 10 minutes. Now I can concentrate on the important parts.
- dolebirchwood 1y agoI do frontend work (React/TypeScript). I barely write my own code anymore, aside from CSS (the LLMs have no aesthetic sensibilities). Just prompting with Gemini 2.5 Pro. Sometimes Sonnet 4. I don't know what to tell you. I just talk to the thing in plain but very specific English and it generally does what I want. Sometimes it will do stupid things, but then I either steer it back in the direction I want or just do it myself if I have to.
- hn_throwaway_99 1y ago> I barely write my own code anymore, aside from CSS (the LLMs have no aesthetic sensibilities). Funnily enough, skeletoning out the CSS boilerplate is one of my favorite uses of LLMs (though, granted, I don't have much aesthetic sensibility either). I'm primarily a backend dev, though I'm competent on the front end. But I tend to be slow on the front end, because I don't do it enough to keep up with the constant churn and voodoo that is modern CSS. With LLMs I can literally just say something along the lines of "now make it pretty", and I get some CSS that is about 75% of the way there. I still have to do a bunch of tweaking/fixing, but it's a lot easier for me to fix CSS than it is to get some flexbox or whatever nonsense to work from scratch. LLMs have caused me to write a ton more personal per projects because in the past I would have thought "I'll just waste a day getting the front end to look halfway decent", but now I can zip through that part of the project.
- jimbo808 1y agoI've been pondering this for a while. I think there's an element of dopamine that LLMs bring to the table. They probably don't make a competent senior engineer much more productive if at all, but there's that element of chance that we don't get a lot of in this line of work. I think a lot of us eventually arrive at a point where our jobs get a bit boring and all the work starts to look like some permutation of past work. If instead of going to work and spending two hours adding some database fields and writing some tests, you had the opportunity to either: A) Do the thing as usual in the predictable two hours B) Spend an hour writing a detailed prompt as if you were instructing a junior engineer on a PIP to do it, and doing all the typical cognitive work you'd have done normally and then some, but then instead of typing out the code in the next hour, you have a random chance to either press enter, and tada the code has been typed and even kinda sorta works, after this computer program was "flibbertigibbeting" for just 10 minutes. Wow! Then you get that sweet dopamine hit that tells you you're a really smart prompt engineer who did a two hour task in... cough 10 minutes. You enjoy your high for a bit, maybe go chat with some subordinate about how great your CLAUDE.md was and if they're not sure about this AI thing it's just because they're bad at prompt engineering. Then all you have to do is cross your t's and dot your i's and it's smooth sailing from there.Except, it's not. Because you (or another engineer) will probably find architectural/style issues when reviewing the code that you explicitly told it to follow, but it ignored, and you'll have to fix those. You'll also probably be sobering up from your dopamine rush by now, and realize that you have to either review all the other lines of AI generated code, which you could have just correctly typed once. But now you have to review with an added degree of scrutny, because you know it's really good at writing text that looks beautiful, but is ever so slightly wrong in ways that might even slip through code review and cause the company to end up in the news. Alternatively, you could yolo and put up an MR after a quick smell, making some other poor engineer do your job for you (you're a 10x now, you've got better things to do anyway). Or better yet, just have Claude write the MR, and don't even bother to read it. Surely nobody's going to notice your "acceptance critera" section says to make sure the changes have been tested on both Android and Apple, even though you're building a microservice for an AI-powered smart fridge (mostly just a fridge, except every now and then it starts shooting ice cubes across the room at mach 3). Then three months later when someone, who never realized there are three different identical "authenticate," spends an hour scratching their head about why the code they're writing is not doing anything (because it's actually running another redundant function that nobody ever seems to catch in MR review because they're not reflected in a diff. But yeah, that 10 minute AI magic trick sure felt good. There are times when work is dull enough that option B sounds pretty good, and I'll dabble. But yeah, I'm not sure where this AI stuff leads but I'm pretty confident it won't taking over our jobs any time soon (an ever-increasing quota of H1Bs and STEM opt student visas working for 30% less pay, on the other hand, might).
- phatfish 1y agoI don't code every day and am not an expert. Supposedly the sort of casual coder that LLMs are supposed to elevate into senior engineers. Even I can see they have big blind spots. As the parent said I get overly verbose code that does run, but is no where near the best solution. Well, for really common problems and patterns I usually get a good answer. Need a more niche problem solved?You better brush up your Googling skills and do some research if you care about code quality.
- richardlblair 1y agoAI is really good at writing tests. AI is also pretty good if you get it to do small chunks of code for you. This means you come with the architecture, the implementation details, and how each piece is structured. When I walk AI through each unit of code I find the results are better, and it's easier for me to address issues as I progress. This may seem some what redundant, though. Sometimes it's faster to just do it yourself. But, with a toddler who hates sleep I've found I've been able to maintain my velocity... Even on days I get 3 hrs of sleep.
- dionian 1y agoCould the quality of your prompt be related to our differing outcome? I have decades of pre-AI experience and I use AI heavily. If I let it go off on its own its not as good as constraining and hand-holding it.
- Kiro 1y agoThe code LLMs write is much better than mine. Way less shortcuts and spaghetti. Maybe that means that I am a lousy coder but the end result is still better.
- burnte 1y agoI see LLM coding as hinting on steroids. I don't trust it to actually write all of my code, but sometimes it can get me started, like a template.
- gspencley 1y agoMy favourite code smell that LLMs love to introduce is redundant code comments. // assign "bar" to foo const foo = "bar"; They love to do that shit. I know you can prompt it not to. But the amount of PRs I'm reviewing these days that have those types of comments is insane.
- randomjoe2 1y agoIf you actually believe this, you're either using bad models or just terrible at prompting and giving proper context. Let me know if you need help, I use generated code in every corner of my computer every day