[HN Gopher] I'm dialing back my LLM usage
       ___________________________________________________________________
        
       I'm dialing back my LLM usage
        
       Author : sagacity
       Score  : 337 points
       Date   : 2025-07-02 12:48 UTC (10 hours ago)
        
 (HTM) web link (zed.dev)
 (TXT) w3m dump (zed.dev)
        
       | Nedomas wrote:
       | two weeks ago I started heavily using Codex (I have 20y+ dev xp).
       | 
       | At first I was very enthusiastic and thought Codex is helping me
       | multiplex myself. But you actually spend so much time trying to
       | explain Codex the most obvious things and it gets them wrong all
       | the time in some kind of nuanced way that in the end you spend
       | more time doing things via Codex than by hand.
       | 
       | So I also dialed back Codex usage and got back to doing many more
       | things by hand again because its just so much faster and much
       | more predictable time-wise.
        
         | nsingh2 wrote:
         | Same experience, these "background agents" are powered by
         | models that aren't yet capable enough to handle large, tangled
         | or legacy codebases without human guidance. So the background
         | part ends up being functionally useless in my experience.
        
       | seanw444 wrote:
       | This is pretty much the conclusion I've come to as well. It's not
       | good at being an autocomplete for entire chunks of your codebase.
       | You lose the mental model of what is doing what, and exactly
       | where. I prefer to use it as a personalized, faster-iterating
       | StackOverflow. I'll ask it to give me a rundown of a concept I'm
       | not familiar with, or for a general direction to point me in if
       | I'm uncertain of what a good solution would be. Then I'll make
       | the decision, and implement it myself. That workflow has worked
       | out much better for me so far.
        
         | solomonb wrote:
         | I use it the same way but cursor is constantly insisting on
         | making code changes. Is there a trick to get it to introspect
         | on the codebase without wanting to modify it?
        
           | haiku2077 wrote:
           | In Zed you can toggle between read-only and write modes at
           | any point when using the agent. You can also create custom
           | modes that allow the use of specific tools, editing only
           | specific files, etc. Does cursor have a similar feature?
        
           | nsingh2 wrote:
           | In Cursor, there is an 'ask' mode that isn't as over-eager to
           | make edits as the default agent mode.
        
           | furyofantares wrote:
           | I say something like "without making any code changes right
           | now, investigate blah blah blah" and if I want more than just
           | info "and propose a direction that I can look at", or
           | sometimes give it a file to write a proposal into.
        
         | rane wrote:
         | I don't have this experience. The mental mode might not be
         | quite as strong, but if you always review the code given
         | carefully, you will have a good pretty idea what is where and
         | how things interact.
        
       | travisgriggs wrote:
       | This parrots much of my own experience.
       | 
       | I don't have it write of my Python firmware or Elixir backend
       | stuff.
       | 
       | What I do let it rough in is web front end stuff. I view the need
       | for and utility of LLMs in the html/css/tailwind/js space as an
       | indictment of complexity and inconsistency. It's amazing that the
       | web front end stuff has just evolved over the years, organically
       | morphing from one thing to another, but a sound well engineered
       | simple-is-best set of software it is not. And in a world where my
       | efforts will probably work in most browser contexts, no surprise
       | that I'm willing to mix in a tool that will make results that
       | will probably work. A mess is still a mess.
        
       | quaintdev wrote:
       | LLMs have limits. They are super powerful but they can't make the
       | kind of leap humans can. For example, I asked both Claude and
       | Gemini below problem.
       | 
       | "I want to run webserver on Android but it does not allow binding
       | on ports lower than 1000. What are my options?"
       | 
       | Both responded with below solutions
       | 
       | 1. Use reverse proxy
       | 
       | 2. Root the phone
       | 
       | 3. Run on higher port
       | 
       | Even after asking them to rethink they couldn't come up with the
       | solution I was expecting. The solution to this problem is HTTPS
       | RR records[1]. Both models knew about HTTPS RR but couldn't
       | suggest it as a solution. It's only after I included it in their
       | context both agreed it as a possible solution.
       | 
       | [1]: https://rohanrd.xyz/posts/hosting-website-on-phone/
        
         | _flux wrote:
         | TIL. I knew about the SRV reconds--which almost nobody uses I
         | think?--but this was news to me.
         | 
         | I guess it's also actually supported, unlike SRV that are more
         | like supported only by some applications? Matrix migrated from
         | SRV to .well-known files for providing the data. (Or I maybe it
         | supports both.)
        
           | bravetraveler wrote:
           | You'd be surprised at how many games use SRV records.
           | Children struggle with names; let alone _ports_ and modifier
           | keys.
           | 
           | At least... this was before multiplayer discovery was
           | commandeered. Matchmaking and so on largely put an end to
           | opportunities.
        
           | remram wrote:
           | See also SVCB
        
           | Arathorn wrote:
           | Matrix supports both; when you're trying to get Matrix
           | deployed on someone's domain it's a crapshoot on whether they
           | have permission to write to .well-known on the webroot (and
           | if they do, the chances of it getting vaped by a CMS update
           | are high)... or whether they have permission to set DNS
           | records.
        
         | GoToRO wrote:
         | Classic problem of "they give you the solution once you ask
         | about it".
        
         | capt_obvious_77 wrote:
         | Off-topic, but reading your article about hosting a website on
         | your phone inspired me a lot. Is that possible on a non-jail-
         | broken phone? And what webserver would you suggest?
        
           | quaintdev wrote:
           | Yes, no root required. I asked Claude to write Flutter app
           | that would serve a static file from assets. There are plenty
           | of webserver available on play store too.
        
           | bird0861 wrote:
           | Just use termux.
        
         | danielbln wrote:
         | I'm not sure I would measure LLMs on recommending a fairly
         | obscure and rather new spec that isn't even fully supported by
         | e.g. Chrome. That's a leap that I, a human, wouldn't have made
         | either.
        
           | mandevil wrote:
           | On the other hand, I find that "someone who has read all the
           | blogs and papers and so can suggest something you might have
           | missed" is my favorite use case for LLM, so seeing that it
           | can miss a useful (and novel to me) idea is annoying.
        
             | Hackbraten wrote:
             | Which is easier for you to remember: facts you've seen a
             | hundred times in your lifetime, or facts you've seen once
             | or twice?
             | 
             | For an LLM, I'd expect it to be similar. It can recall the
             | stuff it's seen thousands of times, but has a hard time
             | recalling the niche/underdocumented stuff that it's seen
             | just a dozen times.
        
               | gtsop wrote:
               | > Which is easier for you to remember: facts you've seen
               | a hundred times in your lifetime, or facts you've seen
               | once or twice?
               | 
               | The human brain isn't a statistical aggregator. If you
               | see a psychologically socking thing once in your
               | lifetime, you might remember it even after dementia hits
               | when you're old.
               | 
               | On the other hand, you pass by hundrends of shops every
               | day and receive the data signal of their signs over and
               | over and over, yet you remember nothing.
               | 
               | You remeber stuff you pay attention to (for whatever
               | reason)
        
           | gtsop wrote:
           | So is the expectation for it to suggest obvious solutions
           | that the majority of people already know?
           | 
           | I am fine with this, but let's be clear about what we're
           | expecting
        
             | jeremyjh wrote:
             | All it can do is predict the next token. So, yes.
        
             | pdabbadabba wrote:
             | > So is the expectation for it to suggest obvious solutions
             | that the majority of people already know?
             | 
             | Certainly a majority of people don't know this. What we're
             | really asking is whether an LLM is expected to more than
             | (or as much as) the average domain expert.
        
         | ramses0 wrote:
         | I'm adding this tidbit of knowledge to my context as well...
         | :-P
         | 
         | Only recently have I started interacting with LLM's more (I
         | tried out a previous "use it as a book club partner"
         | suggestion, and it's pretty great!).
         | 
         | When coding with them (via cursor), there was an interaction
         | where I nudged it: "hey, you forgot xyz when you wrote that
         | code the first time" (ie: updating an associated data structure
         | or cache or whatever), and I find myself INTENTIONALLY giving
         | the machine at least the shadow of a benefit of the doubt that:
         | "Yeah, I might have made that mistake too if I were writing
         | that code" or "Yeah, I might have written the base case first
         | and _then_ gotten around to updating the cache, or decrementing
         | the overall number of found items or whatever".
         | 
         | In the "book club" and "movie club" case, I asked it to discuss
         | two movies and there were a few flubs: was the main character
         | "justly imprisoned", or "unjustly imprisoned" ... a human might
         | have made that same typo? Correct it, don't dwell on it, go
         | with the flow... even in a 100% human discussion on books and
         | movies, people (and hallucinating AI/LLM's) can not remember
         | with 100% pinpoint accuracy every little detail, and I find
         | giving a bit of benefit of the doubt to the conversation
         | partner lowers my stress level quite a bit.
         | 
         | I guess: even when it's an AI, try to keep your interactions
         | positive.
        
         | ctippett wrote:
         | Huh, that's a neat trick. Your comment is the first I'm
         | learning of HTTPS RR records... so I won't pass judgement on
         | whether an AI should've known enough to suggest it.
        
         | pimlottc wrote:
         | To be fair, the question implies the port number of the local
         | service is the problem, when it's more about making sure users
         | can access it without needing to specify a port number in the
         | URL.
         | 
         | Yes, an experienced person might be able to suss out what the
         | real problem was, but it's not really the LLMs fault for
         | answering the specific question it was asked. Maybe you just
         | wanted to run a server for testing and didn't realize that you
         | can add a non-standard port to the URL.
        
           | lcnPylGDnU4H9OF wrote:
           | It's not really an LLM being "faulty" in that we kinda know
           | they have these limitations. I think they're pointing out
           | that these models have a hard time "thinking outside the box"
           | which is generally a lauded skill, especially for the
           | problem-solving/planning that agents are expected to do.
        
           | causal wrote:
           | Yeah LLMs are generally going to pursue a solution to the
           | question, not figure out the need behind the ask.
           | 
           | Not to mention the solution did end up being to use a higher
           | port number...
        
         | pdabbadabba wrote:
         | If you specify your goals and constraints more fully, ChatGPT
         | o3 does, in fact, identify this solution, but it correctly
         | notes that it only works for modern browsers:
         | https://chatgpt.com/share/6865a0e8-1244-8013-8b4b-a58446bccb...
        
       | furyofantares wrote:
       | I've gone the other way and put a lot of effort into figuring out
       | how to best utilize these things. It's a rough learning curve and
       | not trivial, especially given how effortless stuff looks and
       | feels at first.
        
       | MrGilbert wrote:
       | My point of view: LLMs should be taken as a tool, not as a source
       | of wisdom. I know someone who likes to answer people-related
       | questions through a LLM. (E.g.: "What should this person do?"
       | "What should we know about you?" etc.) More than once, this leads
       | to him getting into a state of limbo when he tries to explain
       | what he means with what he wrote. It feels a bit wild - a bit
       | like back in school, when the guy who copied your homework, is
       | forced to explain how he ended up with the solution.
        
       | atonse wrote:
       | These seem like good checkpoints (and valid criticisms) on the
       | road to progress.
       | 
       | But it's also not crazy to think that with LLMs getting smarter
       | (and considerable resources put into making them better at
       | coding), that future versions would clean up and refactor code
       | written by past versions. Correct?
        
         | bwfan123 wrote:
         | nope, there are limits to what next-token predictions can do,
         | we we have hit those limits. cursor and the like are great for
         | some usecases - for example a semantic search for relevant code
         | snippets, and autocomplete. But beyond that, they only bring
         | frustration in my use.
        
           | bunderbunder wrote:
           | Arguably most of the recent improvement in AI coding agents
           | didn't exactly come from getting better at next token
           | prediction in the first place. It came from getting better at
           | context management, and RAG, and improvements on the usable
           | context window size that let you do more with context
           | management and RAG.
           | 
           | And I don't really see any reason to declare we've hit the
           | limit of what can be done with those kinds of techniques.
        
             | bwfan123 wrote:
             | I am sure they will continue to improve just as the static-
             | analyzers and linters are improving.
             | 
             | But, fundamentally, LLMs lack a theory of the program as
             | intended in this comment
             | https://news.ycombinator.com/item?id=44443109#44444904 .
             | Hence, they can never reach the promised land that is being
             | talked about - unless there are innovations beyond next-
             | token prediction.
        
               | bunderbunder wrote:
               | They do lack a theory of program. But also, if there's
               | one consistent theme that you can trace through my 25 of
               | studying and working in ML/AI/whateveryouwanttocallit,
               | it's that symbolic reasoning isn't nearly as critical to
               | building useful tools as we like to think it is.
               | 
               | In other words, I would be wrong of me to assume that the
               | only way _I_ can think of to go about solving a problem
               | is the only way to do it.
        
         | yard2010 wrote:
         | LLM doesn't get smarter. An LLM is just a statistical tool for
         | text generation, not a form of an AI. Since language is so
         | inherent to intelligence and knowledge, it correlates. But LLM
         | is just a tool for predicting what the average internet person
         | would say.
        
         | bunderbunder wrote:
         | Maybe. But there's also an argument to be made that an ounce of
         | prevention is worth a pound of cure.
         | 
         | Maybe quite a few pounds, if the cure in question hasn't been
         | invented yet and may turn out to be vaporware.
        
       | alexvitkov wrote:
       | I've found the Cursor autocomplete to be nice, but I've learned
       | to only accept a completion if it's byte for byte what I would've
       | written. With the context of surrounding code it guesses that
       | often enough to be worth the money for me.
       | 
       | The chatbot portion of the software is useless.
        
         | cornfieldlabs wrote:
         | For me it's the opposite. Autocomplete suggests the lines I
         | just deleted and also suggests completely useless stuff. I have
         | a shortcut to snooze (it's possible!) it. It interrupts flow my
         | flow a lot. I would rather those stuff myself.
         | 
         | Chat mode on the other hand follows my rules really well.
         | 
         | I mostly use o3 - it seems to be the only model that has
         | "common sense" in my experience
        
       | x187463 wrote:
       | Am I spending too much time on HN or is every post/comment
       | section filled with this same narrative? Basically, LLMs are
       | exciting but they produce messy code for which the dev feels no
       | ownership. Managing a codebase written by an LLM is difficult
       | because you have not cognitively loaded the entire thing into
       | your head as you do with code written yourself. They're okay for
       | one-off scripts or projects you do not intend to maintain.
       | 
       | This is blog post/comment section summary encountered many times
       | per day.
       | 
       | The other side of it is people who seem to have 'gotten it' and
       | can dispatch multiple agents to plan/execute/merge changes across
       | a project and want to tell you how awesome their workflow is
       | without actually showing any code.
        
         | fridder wrote:
         | Trying to wade through the hype or doom is bit of a challenge
        
         | noodletheworld wrote:
         | > want to tell you how awesome their workflow is
         | 
         | Or, often, sell you something.
        
           | dkubb wrote:
           | A lot of the time they are selling themselves as influencers
           | on the subject. It's often a way to get views or attention
           | that they can use in the future.
        
         | totalperspectiv wrote:
         | I think you hit the nail on the head with the mental model
         | part. I really like this method of thinking about programming
         | "Programming as Theory Building"
         | https://gist.github.com/onlurking/fc5c81d18cfce9ff81bc968a7f...
         | 
         | I don't mind when other programmers use AI, and use it myself.
         | What I mind is the abdication of responsibility for the code or
         | result. I don't think that we should be issuing a disclaimer
         | when we use AI any more than when I used grep to do the log
         | search. If we use it, we own the result of it as a tool and
         | need to treat it as such. Extra important for generated code.
        
           | zeta0134 wrote:
           | Even putting aside the ethical issues, it's rare that I want
           | to copy/paste code that I find into my own project without
           | doing a _thorough_ review of it. Typically if I 'm working
           | off some example I've found, I will hand-type it in my
           | project's established coding style and add comments to
           | clarify things that are not obvious to me in that moment.
           | With an LLM's output, I think I would have to adopt a similar
           | workflow, and right now that feels slower than just solving
           | the problem myself. I already have the project's domain in my
           | mental map, and explaining it to the agent is tedious and a
           | time waste.
           | 
           | I think this is often overlooked, because on the one hand
           | it's really impressive what the predictive model can
           | sometimes do. Maybe it's super handy as an autocomplete, or
           | an exploration, or for rapidly building a prototype? But for
           | real codebases, the code itself isn't the important part.
           | What matters is documenting the business logic and setting it
           | up for efficient maintenance by all stakeholders in the
           | project. That's the actual task, right there. I spend more
           | time writing documentation and unit tests to validate that
           | business logic than I do actually writing the code that will
           | pass those tests, and a lot of that time is specifically
           | spent coordinating with my peers to make sure I understand
           | those requirements, that they were specified correctly, that
           | the customer will be satisfied with the solution... all stuff
           | an LLM isn't really able to replace.
        
           | skeeter2020 wrote:
           | Isn't this what Brooks describes, stating more than 50 years
           | ago that there's a fundamental shift when a system can no
           | longer be held in a single mind, and the communication &
           | coordination load that results from adding people? It seems
           | with a single person offloading the work to an LLM right at
           | the start they give up this efficiency before even beginning,
           | so unless you're getting AI to do all the work it will
           | eventually bite you...
        
             | transpute wrote:
             | Indeed. Speedrunning an LLM variation of
             | https://en.wikipedia.org/wiki/Conway's_law.
             | Organizations which design systems (in the broad sense used
             | here) are constrained to produce designs which are copies
             | of the communication structures of these organizations.
             | -- Melvin E. Conway, How Do Committees Invent?
             | 
             | _> there 's a fundamental shift when a system can no longer
             | be held in a single mind_
             | 
             | Should LLM users invest in both biological (e.g. memory
             | palace) and silicon memory caches?
        
               | JohnMakin wrote:
               | This law took several years to understand for me. Early
               | on, I'd come into an infra situation and kind of
               | incredulously say stuff like "Why not do (incredibly
               | obvious thing)?" and be frustrated by it quite often.
               | 
               | Usually it's not because people think it can't be done,
               | or shouldn't be done, it's because of this law. Like yes
               | in an ideal world we'd do xyz, but department head of
               | product A is a complete anti-productive bozo that no one
               | wants to talk to or deal with, so we'll engineer around
               | him kind of a thing. It's incredibly common once you see
               | it play out you'll see it everywhere.
        
               | transpute wrote:
               | _> no one wants to talk to or deal with, so we 'll
               | engineer around him_
               | 
               | Sometimes, forking product lines, departments or budgets.
        
               | sunrunner wrote:
               | I'm compelled to make sure any comment mentioning
               | Conway's Law has a reply linking the following video (and
               | perhaps I should create a bot to do this):
               | 
               | https://www.youtube.com/watch?v=5IUj1EZwpJY
               | 
               | This analysis of the real-world effects of Conway's Law
               | seems deeply horrifying, because the implication seems to
               | be that there's nothing you can do to keep communication
               | efficiency and design quality high while also growing an
               | organisation.
        
               | transpute wrote:
               | _> horrifying_
               | 
               | Self-regulating.
        
               | sunrunner wrote:
               | Self-regulating in a way that is designed to favour
               | smaller independent groups with a more complete
               | understanding and ownership of whatever <thing> that team
               | does?
        
               | exceptione wrote:
               | I think you better link to a good article instead. Good
               | grief, what a horror _. A talking head rambling on for 60
               | minutes.
               | 
               | ---
               | 
               | _ disclaimer: if low information density is your thing,
               | then your mileage may vary. Video's are for
               | documentaries, not for reading out an article in the
               | camera.
        
               | sunrunner wrote:
               | Okay, so you didn't even bother to take a few seconds to
               | step through the video to see if there was anything other
               | than the talking head (I'll help you out a bit, there
               | is).
               | 
               | Either way, it's a step-by-step walk through of the ideas
               | of the original article that introduced Conway's Law and
               | a deeper inspection into ideas about _why_ it might be
               | that way.
               | 
               | If that's not enough then my apologies but I haven't yet
               | found an equivalent article that goes through the ideas
               | in the same way but in the kind of information-dense
               | format that I assume would help you hit your daily
               | macros.
               | 
               | Edit: Accidentally a word
        
               | brulard wrote:
               | Man, I don't know what kind of world you live in, but an
               | hour long video is a little too much to swallow when
               | reading HN comments. I even gave it a chance, but had to
               | close the tab after the guy just prepared you for
               | something and then steered away to explain "what is a
               | law". That's absurd.
        
               | photonthug wrote:
               | > A talking head rambling on for 60 minutes.
               | 
               | And probably a few minutes of commercials too. I get the
               | impression this is an emerging generational thing, but
               | unless it's a recorded university course or a _very_
               | interesting and reputable person.. no thanks. What is
               | weird is that the instinct to prefer video seems
               | motivated by laziness, and laziness is actually an
               | adaptive thing to deal with information overload.. yet
               | this noble impulse is clearly self-defeating in this
               | circumstance. Why wait and /or click-through ads for
               | something that's low-density in the first place, you
               | can't search, etc.
               | 
               | Especially now that you can transcript the video and
               | quickly get AI to clean it up into a post,
               | creating/linking a video potentially telegraphs stuff
               | like: nothing much to say but a strong desire to be in
               | the spotlight / narcissism / an acquisitiveness for
               | clicks / engagement. Patiently enduring infinite ads
               | while you're pursuing educational goals and assuming
               | others are willing to, or assuming other people are
               | paying for ad-free just because you do, all telegraphs a
               | lack of respect for the audience, maybe also a lack of
               | self-respect. Nothing against OP or this video in
               | particular. More like a PSA about how this might come
               | across to other people, because I can't be the only
               | person that feels this way.
        
               | sunrunner wrote:
               | > a very interesting and reputable person
               | 
               | Always and entirely subjective of course, but I find
               | Casey Muratori to be both interesting and reputable.
               | 
               | > What is weird is that the instinct to prefer video
               | seems motivated by laziness, and laziness is actually an
               | adaptive thing to deal with information overload...
               | 
               | What's even weirder is the instinct to not actually
               | engage with the content of the linked video and a
               | discussion on Conway's Law and organisational efficiency
               | and instead head straight into a monologue about some
               | kind of emerging generational phenomenon of laziness
               | highlighted by a supposed preference for long video
               | content, which seems somewhat ironic itself as ignoring
               | the original subject matter to just post your preferences
               | as 'PSA' is its own kind of laziness. To each their own I
               | guess.
               | 
               | Although I do think the six-hour YouTube 'essays' really
               | could do with some serious editing, so perhaps there's
               | something there after all...
        
               | zahlman wrote:
               | After opening the "transcript" on these kinds of videos
               | (from a link in the description, which may need to be
               | expanded), a few lines of JavaScript can extract the
               | actual transcript text without needing to wrestle with
               | browser copy-and-paste. Presumably the entire process
               | could be automated, without even visiting the link in a
               | browser.
        
           | bwfan123 wrote:
           | Thanks for sharing this beautiful essay which I have never
           | come across. The essay and its citations are thought-
           | provoking reading.
           | 
           | IMO, LLMs of today are not capable of building theories
           | (https://news.ycombinator.com/item?id=44427757#44435126).
           | And, if we view programming as theory building, then LLMs are
           | really not capable of coding. They will remain useful tools.
        
           | swat535 wrote:
           | LLMS are great at generating scaffolding and boilerplate code
           | which then I can iterate upon. I'm not going write
           | 
           | describe User do ... it ".."
           | 
           | for the thousand time.. or write the controller files with
           | CRUD actions..
           | 
           | LLMS can do these. I can then review the code, improve it and
           | go from there.
           | 
           | They are also very useful for brain storming ideas, I treat
           | it as a better google search. If I'm stuck trying to model my
           | data, I can ask it questions and it gives me recommendations.
           | I can then think about it and come up with an approach that
           | makes sense.
           | 
           | I also noticed that LLMs really lack basic comprehension. For
           | example, no matter how many times you provide the Schema file
           | for it (or a part of it) , it still doesn't understand that a
           | column doesn't exist on a model and will try to shove it in
           | the suggested code.. very annoying.
           | 
           | All that being said, I have an issue with "vibe coding"..
           | this is where the chaos happens as you blindly copy and paste
           | everything and git push goodbye
        
             | exe34 wrote:
             | If you need to do something for a thousand times, why don't
             | you write a template?
        
               | satvikpendem wrote:
               | Templates aren't as flexible as LLMs especially when
               | seeing and utilizing the context of certain files.
        
               | pferde wrote:
               | Yes, but at least they're reliable and predictable. Two
               | things you desperately want in software development.
        
             | lenkite wrote:
             | We need to invent better languages and frameworks.
             | Boilerplate code should be extremely minimal in the first
             | place, but it appears to have exploded in the last decade.
        
         | pier25 wrote:
         | > _Managing a codebase written by an LLM is difficult because
         | you have not cognitively loaded the entire thing into your head
         | as you do with code written yourself._
         | 
         | I don't think that's the main reason. Well written code is
         | easier to follow even when you haven't written it yourself (or
         | maybe you did but forgot about it).
        
           | skeeter2020 wrote:
           | I argue you still need to cognitively load the solution, it's
           | just that well written code allows you to (a) segment the
           | code base effectively and (b) hold it at a higher level of
           | abstraction.
        
             | pier25 wrote:
             | Absolutely. The comment I was responding to argued the
             | difficulty was that LLM code wasn't loaded cognitively. I'm
             | arguing the problem is actually the code produced by LLMs
             | tends to be messy and hard to follow beyond trivial
             | examples.
        
         | jimbokun wrote:
         | Of course it's the main topic because it's an existential
         | question for almost all our careers.
        
           | xpe wrote:
           | And AI in general* poses existence-level questions (that
           | could go either way: good or bad) regarding military
           | applications, medical research, economic benefits, quality of
           | life, human thriving, etc.
           | 
           | The idea that the future is going to "more or less be
           | predictable" and "within the realm of normal" is a pretty
           | bold claim when you look at history! Paradigm shifts happen.
           | And many people think we're in the middle of one -- people
           | that don't necessarily have an economic interest in saying
           | so.
           | 
           | * I'm not taking a position here about predicting what
           | particular AI technologies will come next, for what price,
           | with what efficiency and capabilities, and when. Lots of
           | things could happen we can't predict -- like economic cycles,
           | overinvestment, energy constraints, war, popular pushback,
           | policy choices, etc. But I would probably bet that LLMs are
           | just the beginning.
        
           | seadan83 wrote:
           | I believe it's the main topic because VCs have been trying to
           | solve the problem of "expensive software developers" for a
           | long time. The AI start-up hype train is real simply because
           | that is how you get VC money these days. VC money contracted
           | with the economy and post-Covid severely, and seemingly what
           | is available is going to AI something-or-other. Somehow, the
           | VC-orientated startup hype-train seems to have become the
           | dominant voice in the zeitgeist of software development.
        
         | alonsonic wrote:
         | Yes, it's very polarized. That being said, people have shown a
         | lot of code produced by LLMs so I don't understand the
         | dismissive argument you make at the end.
         | 
         | Below is a link to a great article by Simon Willison explaining
         | an LLM assisted workflow and the resulting coded tools.
         | 
         | [0] https://simonwillison.net/2025/Mar/11/using-llms-for-code/
         | [1] https://github.com/simonw/tools
        
           | OtherShrezzing wrote:
           | While I greatly appreciate all of Simon Willson's publishing,
           | these tools don't meet the criteria of the OP's comment in my
           | opinion. Willson's tools archive all do useful, but
           | ultimately small tasks which mostly fit the "They're okay for
           | one-off scripts or projects you do not intend to maintain"
           | caveat from OP.
           | 
           | Meanwhile, it's not uncommon to see people on HN saying
           | they're orchestrating multiple major feature implementations
           | in parallel. The impression we get here is that Simon
           | Willson's entire `tools` featureset could be implemented in a
           | couple of hours.
           | 
           | I'd appreciate some links to the second set of people. Happy
           | to watch YouTube videos or read more in-depth articles.
        
             | hedgehog wrote:
             | There's a third category I'd place myself in which is doing
             | day to day work in shipping codebases with some history,
             | using the tools to do a faster and better job of the work
             | I'd do anyway. I think the net result is better code, and
             | ideally on average less of it relative to the functionality
             | because refactors are less expensive.
        
             | tptacek wrote:
             | Many big systems are comprised of tools that do a good job
             | at solving small tasks, carefully joined. That LLMs are not
             | especially good at that joinery just means that's a part of
             | the building process that stays manual.
        
           | graemep wrote:
           | its really not that different.
           | 
           | "f you assume that this technology will implement your
           | project perfectly without you needing to exercise any of your
           | own skill you'll quickly be disappointed."
           | 
           | "They'll absolutely make mistakes--sometimes subtle,
           | sometimes huge. These mistakes can be deeply inhuman--if a
           | human collaborator hallucinated a non-existent library or
           | method you would instantly lose trust in them"
           | 
           | "Once I've completed the initial research I change modes
           | dramatically. For production code my LLM usage is much more
           | authoritarian: I treat it like a digital intern, hired to
           | type code for me based on my detailed instructions."
           | 
           | "I got lucky with this example because it helped illustrate
           | my final point: expect to need to take over. LLMs are no
           | replacement for human intuition and experience. "
        
           | unshavedyak wrote:
           | I've been experimenting with them quite a bit for the past
           | two weeks. So far the best productivity i've found from them
           | is very tight hand-holding and clear instructions,
           | objectives, etc. Very, very limited thinking. Ideally none.
           | 
           | What that gets me though is less typing fatigue and less
           | decisions made partly due to my wrists/etc. If it's a large
           | (but simple!) refactor, the LLM generally does amazing at
           | that. As good as i would do. But it does that with zero wrist
           | fatigue. Things that i'd normally want to avoid or take my
           | time on it bangs out in minutes.
           | 
           | This coupled with Claude Code's recently Hook[1] introduction
           | and you can help curb a lot of behaviors that are difficult
           | to make perfect from an LLM. Ie making sure it tests,
           | formats, Doesn't include emojis (boy does it like that lol),
           | etc.
           | 
           | And of course a bunch of other practices for good software in
           | general make the LLMs better, as has been discussed on HN
           | plenty of times. Eg testing, docs, etc.
           | 
           | So yea, they're dumb and i don't trust their "thinking" at
           | all. However i think they have huge potential to help us
           | write and maintain large codebases and generally multiplying
           | out productivity.
           | 
           | It's an art for sure though, and restraint is needed to
           | prevent slop. They will put out so. much. slop. Ugh.
           | 
           | [1]: https://docs.anthropic.com/en/docs/claude-code/hooks
        
         | furyofantares wrote:
         | We're going through something.
        
         | generalizations wrote:
         | It feels like a bell curve:
         | 
         | - one big set of users who don't like it because it generates a
         | lot of code and uses its own style of algorithms, and it's a
         | whole lot of unfamiliar code that the user has to load up in
         | their mind - as you said. Too much to comprehend, and quickly
         | overwhelming.
         | 
         | And then to either side
         | 
         | - it unblocks users who simply couldn't have written the code
         | on their own, who aren't even trying to load it into their
         | head. They are now able to make working programs!
         | 
         | - it accelerates users who _could_ have written it on their
         | own, given enough time, but have figured out how to treat it as
         | an army of junior coders, and learned to only maintain the high
         | level algorithm in their head. They are now able to build far
         | larger projects, _fast_!
        
           | danielbln wrote:
           | I'm in that last bracket. I don't really have LLMs do tasks
           | that given enough time and scouring docs I couldn't have
           | implemented myself. I set hard rules around architecture,
           | components, general design patterns and then let the LLM go
           | at it, after which review the result in multiple passes, like
           | I would a junior's code. I could not care less about the
           | minutiae of the actual implementation, as long as it conforms
           | to my conventions and style guides and instructions.
        
             | generalizations wrote:
             | Yeah. I think the trick is, you have to have been capable
             | of doing it yourself, given time. Same as a senior
             | engineer, they have to be capable of doing the tasks they
             | assign to juniors.
        
           | leptons wrote:
           | More often than not the "AI" generates a large block of code
           | that doesn't work, that I still have to read and understand -
           | and it's more difficult to understand _because it doesn 't
           | work_, which is a huge waste of my time. Then I just end up
           | writing the damn code myself, which I should have done in the
           | first place - but my boss wants me to try using the AI.
           | 
           | The _only_ thing the  "AI" is marginally good at is as a
           | fancy auto-complete that writes log statements based on the
           | variable I just wrote into the code above it. And even this
           | simple use case it gets it wrong a fair amount.
           | 
           | Overall the "AI" is a net negative for me, but maybe close to
           | break-even thanks to the autocomplete.
        
             | generalizations wrote:
             | What "AI" are you using
        
           | eikenberry wrote:
           | That last bracket is basically the same as the tech based
           | start-up story. You build the projects fast, but you build a
           | ton of tech debt into it that you'll be forced to deal with
           | unless it is a short lived project. Not that this is 100%
           | bad, but something to know going in.
        
             | generalizations wrote:
             | Depends. I think that becomes a question of the quality of
             | the programmer - if they were doing it all themselves, the
             | code quality of the (necessarily much smaller) projects
             | would still vary between programmers. Now that variation is
             | magnified, but if you're very good at what you do, I
             | suspect it is still possible to create those projects
             | without the tech debt. Though at the lower end of that
             | bracket, I'd agree you tend to end up with giant balls of
             | mud.
        
               | eikenberry wrote:
               | When you play architect and delegate all the work to
               | junior developers it won't matter how good you are, you
               | _will_ incur a lot of tech debt. You simply cannot teach
               | /guide every junior into writing good code as that would
               | take more time than writing it yourself. This fact is
               | baked into the juniors analogy.
        
         | ookblah wrote:
         | honestly my theory is part of it is people who are very caught
         | up in the "craft" part of it and now hate these LLMs for
         | producing shit that pretty much works but isn't like this
         | "perfect specimen" of coding architecture that they now have to
         | pour over.
         | 
         | honestly, the vast majority of basically CRUD apps out there we
         | are inflating our skills a bit too much here. even if the code
         | is junk you can adapt your mindset to accept what LLMs produce,
         | clean it up a bit, and come out with something maintainable.
         | 
         | like do these people ever have to review code from other people
         | or juniors? the feedback loop here is tighter (although the
         | drawback is your LLM doesn't "learn").
         | 
         | i wouldn't use it for anything super novel or cutting edge i
         | guess, but i don't know, i guess everyone on HN might be coding
         | some super secret advanced project that an LLM can't
         | handle....?
        
           | PleasureBot wrote:
           | The fundamental limitation of LLMs writing code is that
           | reading and understanding code is harder and slower than
           | writing it. With other engineers that I work with there is an
           | established level of trust where I do not need to deep dive
           | into every PR. With LLMs it is like I am constantly doing
           | code reviews for someone with whom I have zero trust. This is
           | fundamentally a slow process, especially if you need to
           | maintain this code in the long term and it is part of your
           | 'core business code' that you work on 90% of the time. It
           | also comes with all the downsides of no longer being an
           | expert in your own codebase.
           | 
           | Ultimately I am responsible for any code I check in even if
           | it was written by an LLM, so I need to perform these lengthy
           | reviews. As others have said, if it is code that doesn't need
           | to be maintained, then reviewing the code can be a much
           | faster process. This is why it is so popular for hobby
           | projects since you don't need to maintain the code if you
           | don't want to, and it doesn't matter if you introduce subtle
           | but catastrophic bugs.
           | 
           | Ultimately the tech feels like a net neutral. When you want
           | to just throw the code away after it is very fast and good
           | enough. If you are responsible for maintaining it, its slower
           | than writing it yourself.
        
             | ookblah wrote:
             | which is weird to me because i'm using in prod? literally
             | if i care about style and structure i just say, look at
             | these other few files and figure it out and it's fine.
             | 
             | if i need to work on something mission critical or new i do
             | it by hand first. tests catch everything else. or you can
             | just run it so that you review every change (like in claude
             | code) as it comes in and can still grok the entire thing vs
             | having to review multiple large files at the end.
             | 
             | thus i literally wonder what people are working on that
             | requires this 100% focused mission critical style stuff at
             | all times. i mean i don't think it's magic or AGI, but the
             | general argument is always 1) works for hobby projects but
             | not "production" 2) the LLM produces "messy code" which you
             | have to review line by line as if you wrote it yourself
             | which i've found to not be true at all.
        
             | mythrwy wrote:
             | Volume of PRs LLMs enable add to the burden.
        
         | nico wrote:
         | > Managing a codebase written by an LLM is difficult because
         | you have not cognitively loaded the entire thing into your head
         | as you do with code written yourself
         | 
         | This happens with any sufficiently big/old codebase. We can
         | never remember everything, even if we wrote it ourselves
         | 
         | I do agree with the sentiment and insight about the 2 branches
         | of topics frequently seen lately on HN about AI-assisted coding
         | 
         | Would really like to see a live/video demo of semi-autonomous
         | agents running in parallel and executing actual useful tasks on
         | a decently complex codebase, ideally one that was entirely
         | "manually" written by devs before agents are involved - and
         | that actually runs a production system with either lots of
         | users or paid customers
        
           | WD-42 wrote:
           | The difference is at the moment of writing, you understand
           | it. A LLM outputs a giant glob and you immediately don't
           | understand it.
        
           | photonthug wrote:
           | > This happens with any sufficiently big/old codebase. We can
           | never remember everything, even if we wrote it ourselves
           | 
           | The important thing about a codebase wasn't ever really size
           | or age, but whether it was a planned architecture or grown
           | organically. The same is true post-LLM. Want to put AI in
           | charge of tool-smithing inconsequential little widgets that
           | are blocking you? Fine. Want to put AI in charge of deciding
           | your overall approach and structure? _Maybe_ fine. Worst of
           | all is to put the AI in charge of the former, only to find
           | later that you handed over architectural decisions at some
           | point and without really intending to.
        
             | sunrunner wrote:
             | > planned architecture or grown organically
             | 
             | That sounds like a hard or, as if ten years of development
             | of a large codebase was entirely known up-front with not a
             | single change to the structure over time that happened as a
             | result of some new information.
             | 
             | "We build our computers the way we build our cities--over
             | time, without a plan, on top of ruins." -- Ellen Ullman
        
         | tempodox wrote:
         | > ... encountered many times per day.
         | 
         | I suspect that's at least partially because all of that doesn't
         | stop the hype from being pushed on and on without mercy. Which
         | in turn is probably because the perverse amounts of investment
         | that went into this have to be reclaimed somehow with
         | monetization. Imagine all those VCs having to realize that
         | hundreds of billions of $$$ are lost to wishful hallucinations.
         | Before they concede that there will of course be much
         | astroturfing in the vein of your last paragraph.
        
         | baq wrote:
         | > workflow is without actually showing any code.
         | 
         | an argument can be made that the code doesn't matter as long as
         | the product works as it's supposed to (big asterisk here)
        
           | Disposal8433 wrote:
           | > the code doesn't matter
           | 
           | The only goal of a code generator is the code. I don't care
           | whether it works or not (for specific scenarios and it could
           | break 90% of the time). I want to see the generated code and,
           | so far, I have never seen anything interesting besides todo
           | lists made with ReactJS.
        
             | baq wrote:
             | People who do this don't want to see the code and perhaps
             | even don't care about the code. Code is just a means to an
             | end, which is the product. It might be the wrong take from
             | a software engineer's perspective, but it is a take that
             | works in at least some cases.
        
         | GenerocUsername wrote:
         | How is that that different than working in a large codebase
         | with 25+ other devs.
         | 
         | My org has 160 engineers working on our e-commerce frontend and
         | middle tiers. I constantly dive into repos and code I have no
         | ownership of. The gitblame shows a contractor who worked here 3
         | years ago frequently.
         | 
         | Seems LLM does good in small, bad in medium, good again as
         | small modules within big.
        
           | Barrin92 wrote:
           | >How is that that different than working in a large codebase
           | with 25+ other devs.
           | 
           | Who says it is? The arguably most famous book in the history
           | of software engineering makes that point and precedes LLMs by
           | half a century
        
           | vjvjvjvjghv wrote:
           | "How is that that different than working in a large codebase
           | with 25+ other devs. "
           | 
           | It's as miserable. I hate working on large codebases with
           | multiple contributors unless there is super strong leadership
           | that keeps things aligned.
        
         | ai-christianson wrote:
         | > The other side of it is people who seem to have 'gotten it'
         | and can dispatch multiple agents to plan/execute/merge changes
         | across a project and want to tell you how awesome their
         | workflow is without actually showing any code.
         | 
         | This is a great read on the situation. Do you think these
         | people are just making it up/generating baseless hype?
        
           | WD-42 wrote:
           | I think people are rightly hesitant to share code that has
           | their name on it but for which they know nothing about.
           | 
           | I have seen a few of these full blown llm coded projects and
           | every one of them has has some giant red flashing warning at
           | the top of the README about the project being llm generated.
           | 
           | So I think it's probably a mix of avoiding embarrassment and
           | self preservation.
        
             | ai-christianson wrote:
             | Interesting, to me it's still very much a human in the loop
             | process and the person whose name is on the commit is
             | ultimately responsible for what they commit.
        
         | andrewmutz wrote:
         | I went from one camp to the other in the last month. I've been
         | blown away by whats possible and here's what's working for me:
         | - Use Cline with Sonnet 4.  Other models can work but this is
         | the best balance of price and effectiveness.       - Always use
         | "plan" mode first, and only after the plan mode looks good do
         | you switch to "act" mode.       - Treat the LLM as though you
         | are pair-programming with a junior engineer.         - Review
         | every line that gets written as it gets written.  Object or
         | change it if you don't like it for any reason.       - Do test-
         | driven development, and have the LLM always write tests first.
         | 
         | I have transitioned to using this full-time for coding and am
         | loving the results. The code is better than what I used to
         | write, because sometimes I can miss certain cases or get lazy.
         | The code is better tested. The code gets written at least twice
         | as fast. This is real production code that is being code
         | reviewed by other humans.
        
         | gpm wrote:
         | > for which the dev feels no ownership.
         | 
         | This is definitely something I feel is a choice. I've been
         | experimenting quite a bit with AI generated code, and with any
         | code that I intend to publish or maintain I've been very
         | conscious in making the decision that I own the code and that
         | if I'm not entirely happy with the AI generated output I have
         | to fix it (or force the AI to fix it).
         | 
         | Which is a very different way of reviewing code than how you
         | review another humans code, where you make compromises because
         | you're equals.
         | 
         | I think this produces fine code, not particularly quickly but
         | used well probably somewhat quicker (and somewhat higher
         | quality code) than not using AI.
         | 
         | On the flip side on some throwaway experiments and patches to
         | personalize open source products that I have absolutely no
         | intention of upstreaming I've made the decision that the "AI"
         | owns the code, and gone much more down the vibe coding route.
         | This produces unmaintainable sloppy code, but it works, and it
         | takes a lot less work than doing it properly.
         | 
         | I suspect the companies that are trying to force people to use
         | AI are going to get a lot more of the "no human ownership" code
         | than individuals like me experimenting because they think its
         | interesting/fun.
        
         | mentos wrote:
         | I'm currently using Cursor to complete something that would
         | have taken me about a full year in a month.
         | 
         | But I'm in no rush to invite an army of people to compete with
         | me just yet. I'll be back when I'm sipping coladas on a beach
         | to tell you what I did.
        
           | mythrwy wrote:
           | We all will be sipping coladas on the beach at that point.
           | You can just walk over to the next cabana and tell us.
        
         | crystal_revenge wrote:
         | The only way I've found LLMs to be useful for building real
         | software, which isn't included in your list of use cases, is
         | for "pseudo boiler-plate". That is there are some patterns that
         | are tedious to write out, but not quite proper boiler-plate in
         | the traditional sense, as so not as amenable to traditional
         | solutions.
         | 
         | One example I deal with frequently is creating Pytorch models.
         | Any real model is absolutely not something you want to leave in
         | the hands of an LLM since the entire point of modeling is to
         | incorporate your own knowledge into the design. But there is a
         | lot of tedium, and room for errors, in getting the initial
         | model wiring setup.
         | 
         | While, big picture, this isn't the 10x (or more) improvement
         | that people like to imagine, I find in practice I personally
         | get really stuck on the "boring parts". Reducing the time I
         | spend on tedious stuff tends to have a pretty notable
         | improvement in my overall flow.
        
         | zemo wrote:
         | I think this narrative gets recycled because it's the shallow
         | depth of reasoning afforded by thinking about technology only
         | by thinking about the instruments of that technology and one's
         | own personal experience with them, which is the perspective
         | that is prioritized on HN.
        
         | giancarlostoro wrote:
         | I've been saying this for a while. The issue is if you don't
         | intimately know your code, you can't truly maintain it. What
         | happens when the LLM can't figure out some obscure but that's
         | costing you $$$,$$$ per minute? You think being unable to have
         | the AI figure it out is an acceptable answer? Of course not.
         | LLMs are good for figuring out bugs and paths forward, but
         | don't bet your entire infrastructure on it. Use it as an
         | assistant not a hammer.
        
           | jazzyjackson wrote:
           | "Debugging is twice as hard as writing the code in the first
           | place. Therefore, if you write the code as cleverly as
           | possible, you are, by definition, not smart enough to debug
           | it."
           | 
           | - Brian Kernighan
           | 
           | So if there's a bug in code that an LLM wrote, simply wait 6
           | months until the LLMs are twice as smart?
        
             | zahlman wrote:
             | > > What happens when the LLM can't figure out some obscure
             | but that's costing you $$$,$$$ per minute?
             | 
             | > simply wait [about a quarter of a million minutes] until
             | the LLMs are twice as smart?
             | 
             | ...
        
         | jm4 wrote:
         | I think you described it much more succinctly than most people
         | do. It's been my exact experience as well. The LLM can develop
         | much faster than I can build a mental model. It's very easy to
         | get to a point where you don't know what's going on, a bunch of
         | bugs have been introduced and you can't easily fix them or
         | refactor because you're essentially the new guy on your own
         | project. I find myself adjusting by committing code very
         | frequently and periodically asking the LLM to explain it to me.
         | I often ask the LLM to confirm things are working the way it
         | says they are and it tends to find its own bugs that way.
         | 
         | I use an LLM primarily for smaller, focused data analysis tasks
         | so it's possible to move fast and still stay reasonably on top
         | of things if I'm even a little bit careful. I think it would be
         | really easy to trash a large code base in a hurry without some
         | discipline and skill in using LLM. I'm finding that developing
         | prompts, managing context, controlling pace, staying organized
         | and being able to effectively review the LLM's work are
         | required skills for LLM-assisted coding. Nobody teaches this
         | stuff yet so you have to learn it the hard way.
         | 
         | Now that I have a taste, I wouldn't give it up. There's so much
         | tedious stuff I just don't want to have to do myself that I can
         | offload to the LLM. After more than 20 years doing this, I
         | don't have the same level of patience anymore. There are also
         | situations where I know conceptually what I want to accomplish
         | but may not know exactly how to implement it and I love the LLM
         | for that. I can definitely accomplish more in less time than I
         | ever did before.
        
           | jvergeldedios wrote:
           | > you're essentially the new guy on your own project
           | 
           | Holy shit that's the best description of this phenomenon I've
           | heard so far. The most stark version of this I've experienced
           | is working on a side project with someone who isn't a
           | software engineer who vibe coded a bunch of features without
           | my input. The code looked like 6-8 different people had
           | worked on it with no one driving architecture and I had to
           | untangle how it all got put together.
           | 
           | The sweet spot for me is using it in places where I know the
           | exact pattern I want to use to solve a problem and I can
           | describe it in very small discrete steps. That will often
           | take something that would have taken me an hour or two to
           | hand code something tedious down to 5-10 minutes. I agree
           | that there's no going back, even if all progress stopped now
           | that's too huge of a gain to ignore it as a tool.
        
           | mekoka wrote:
           | > because you're essentially the new guy on your own project.
           | 
           | Wow! Lol. One sentence to rule them all.
        
             | guluarte wrote:
             | and the problem is the LLM is also the new guy on the next
             | prompt lmao, the guy(LLM) that wrote the original code is
             | long gone
        
               | transpute wrote:
               | Looking forward to amnesiac LLM coder memes!
               | 
               | https://static1.srcdn.com/wordpress/wp-
               | content/uploads/2019/...
        
           | reachableceo wrote:
           | " I'm finding that developing prompts, managing context,
           | controlling pace, staying organized and being able to
           | effectively review the LLM's work are required skills for
           | LLM-assisted coding "
           | 
           | Did you not need all these skills / approaches / frameworks
           | for yourself / coding with a team?
           | 
           | This is , I think, the key difference in those (such as
           | myself) who find LLMs to massively increase velocity /
           | quality / quantity of output and those who don't.
           | 
           | I was already highly effective at being a leader /
           | communicator / delegating / working in teams ranging from
           | small , intimate , we shared a mental model / context up to
           | some of the largest teams on the planet.
           | 
           | If someone wasn't already a highly effective
           | IC/manager/leader pre LLM, an LLM will simply accelerate how
           | fast they crash into the dirt.
           | 
           | It takes substantial work to be a highly effective
           | contributor / knowledge worker at any level. Put effort into
           | that , and LLMs become absolutely indispensable, especially
           | as a solo founder.
        
             | antonvs wrote:
             | > If someone wasn't already a highly effective
             | IC/manager/leader pre LLM, an LLM will simply accelerate
             | how fast they crash into the dirt.
             | 
             | Quite the selling point.
        
           | ymyms wrote:
           | One of my favorite ways to use AI is to get me started on
           | things. I tend to drag my feet when starting something new,
           | but LLMs can whip up something quick. Then I look at what it
           | did and usually hate it. Maybe it structured the code in way
           | that doesn't mesh with the way I think or it completely
           | failed to use some new/esoteric library I rely on.
           | 
           | That hate fuels me to just do the work myself. It's like the
           | same trick as those engagement-bait math problems that pop up
           | on social media with the wrong answer.
        
             | antonvs wrote:
             | I do the same thing, except if I hate something, I just ask
             | the LLM to fix it. I can usually get to a starting point
             | I'm pretty happy with, then I take over.
             | 
             | After that, I may ask an LLM to write particular functions,
             | giving it data types and signatures to guide it.
        
             | skydhash wrote:
             | The same. It's mostly an example generator, where you know
             | what to do, but can't take the time to build a model of the
             | language/framework/library. Then you look at the code and
             | retain only the procedure and the symbols used.
        
           | meistertigran wrote:
           | I have found that you can't let the LLM do the thinking part.
           | It's really fast at writing, but only writes acceptable code,
           | if the thinking has been done for it.
           | 
           | In some cases, this approach might even be slower than
           | writing the code.
        
         | jauntywundrkind wrote:
         | There's a lot of truth here.
         | 
         | But also. But also, LLMs are incredibly powerful and capable
         | tools at discovering and finding what the architecture of
         | things is. They have amazing abilities to analyze huge code
         | bases & to build documents and diagrams to map out the system.
         | They can answer all manners of questions, to let us probe in.
         | 
         | I'm looking for good links here. I know I have run across some
         | good stuff before. But uhh I guess this piece that I just found
         | introduces the idea well enough.
         | https://blog.promptlayer.com/llm-architecture-diagrams-a-pra...
         | 
         | And you can see an example in the ever excellent @simonw's
         | review of prompts in copilot. At the end, they briefly look at
         | testing, and it's a huge part of the code base. They ask Gemini
         | for a summary and it spits out a beautiful massive document on
         | how copilot testing works!
         | https://simonwillison.net/2025/Jun/30/vscode-copilot-chat/
         | https://github.com/simonw/public-notes/blob/main/vs-code-cop...
         | 
         | Now, whether LLMs generate well architects systems is largely
         | operator dependent. There's lots of low effort zero shot ways
         | to give LLMs very little guidance and get out who knows what.
         | But when I reflect on the fact that, for now, most code is
         | legacy code, and most code is hideously under documented, most
         | people reading code don't really have access to experts or
         | artifacts to explain the code and it's architecture, my hope
         | and belief is that LLMs are incredible tools to radically
         | increase maintainability versus where we are now, that they are
         | powerful peers in building the mental model of programming &
         | systems.
        
         | apwell23 wrote:
         | > The other side of it is people who seem to have 'gotten it'
         | and can dispatch multiple agents to plan/execute/merge changes
         | across a project and want to tell you how awesome their
         | workflow is without actually showing any code.
         | 
         | There have been grifters hopping onto every trend. Have you
         | noticed they never show you what exactly they built or if it
         | was ever useful.
        
         | xnx wrote:
         | Don't discount the number of articles that espouse a
         | provocative position not held by the poster for the purpose of
         | gaining traffic/attention/clout/influencer-points.
        
         | senko wrote:
         | > Am I spending too much time on HN
         | 
         | Likely (as am I).
         | 
         | > LLMs are exciting but they produce messy code for which the
         | dev feels no ownership. [...] The other side of it is people
         | who seem to have 'gotten it' and can dispatch multiple agents
         | to plan/execute/merge changes across a project
         | 
         | Yup, can confirm, there are indeed people with differing
         | opinions and experience/anecdotes on HN.
         | 
         | > want to tell you how awesome their workflow is without
         | actually showing any code.
         | 
         | You might be having some AI-news-fatigue (I can relate) and
         | missed a few, but there are also people who seem to have gotten
         | it and do want to show code:
         | 
         | Armin Ronacher (of Flask, Jinja2, Sentry fame):
         | https://www.youtube.com/watch?v=nfOVgz_omlU (workflow) and
         | https://lucumr.pocoo.org/2025/6/21/my-first-ai-library/ (code)
         | 
         | Here's one of my non-trivial open source projects where a large
         | portion is AI built: https://github.com/senko/cijene-api
         | (didn't keep stats, I'd eyeball it at conservatively 50% - 80%)
        
         | jordanb wrote:
         | Weirdly this is pretty much the story of code generators.
         | 
         | When I first got into web development there were people using
         | HTML generators based on photoshop comps. They would produce
         | _atrocious_ HTML. FE developers started rewriting the HTML
         | because otherwise you 'd end up with brittle layout that was
         | difficult to extend.
         | 
         | By the time the "responsive web" became a thing HTML generators
         | were dead and designers were expected to give developers
         | wireframes + web-ready assets.
         | 
         | Same thing pretty much happened with UML->Code generators, with
         | different details.
         | 
         | There's always been a tradeoff between the convenience and
         | deskilling involved in generated code and the long term
         | maintainability.
         | 
         | There's also the fact that coding is fundamentally an activity
         | where you try to use abstractions to manage complexity.
         | Ideally, you have interfaces that are good enough that the code
         | reads like a natural language because you're expressing what
         | you what the computer to do at the exact correct layer of
         | abstraction. Code generators tend to both _cause_ and
         | _encourage_ bad interfaces. Often the impetus to use a code
         | generator is the existing interfaces are bad, bureaucratic, or
         | obscure. But using code generators ends up creating more of the
         | same.
        
         | vjvjvjvjghv wrote:
         | Just one thought: I wonder if storing the prompt history
         | together with the LLM code would make it easier to understand
         | the thought process. I have noticed that I find it a little
         | more difficult to read LLM code vs human code (that's written
         | by decent devs)
        
         | DiggyJohnson wrote:
         | I think it's just we are at a point where many are coming to
         | this realization around the same time. You did an excellent job
         | summarizing it though.
        
         | guluarte wrote:
         | LLMs are fine with small things, such as creating or
         | refactoring a small function, adding logs, writing a test, etc.
         | But developing entire features or whole applications is stupid,
         | being statistical models, the more input you feed, the more
         | errors they accumulate
        
         | sppfly wrote:
         | > Managing a codebase written by an LLM is difficult because
         | you have not cognitively loaded the entire thing into your head
         | as you do with code written yourself.
         | 
         | Wow you really nail the point, that's what I felt but I did not
         | understand. Thanks for the comment.
        
         | teaearlgraycold wrote:
         | I am bewildered by the posts where people claim to have 20+
         | agents running at the same time on their repo. I've used o3,
         | Claude 4 Opus, Gemini 2.5 Pro, and they can't run for more than
         | 15 minutes in the best of cases without fucking up or getting
         | caught in a loop. Tasks that are slightly more complicated than
         | your average code are beyond their comprehension.
        
         | zahlman wrote:
         | > is every post/comment section [related to AI/LLMs] filled
         | with this same narrative? ... The other side of it is ...
         | 
         | I don't see why any of this should be surprising. I think it
         | just reflects a lot of developers using this technology and
         | having experiences that fall neatly into one of these two
         | camps. I can imagine a lot of factors that might pull an
         | individual developer in one direction or the other; most of
         | them probably correlate, and people in the middle might not
         | feel like they have anything interesting to say.
        
         | therealpygon wrote:
         | Laziness doesn't stop just because technology improves. This is
         | just intellectual laziness being blamed on LLMs, as usual. "I
         | don't bother to read my code anymore, so LLMs did it." "I don't
         | practice coding anymore, it's LLMs fault." Blah. Blah Blah.
         | 
         | People will always blame someone or something else for
         | laziness.
        
         | lowbloodsugar wrote:
         | I work in a team of 8. So previously I wrote 1/8th of the code.
         | Now I write 1/16th with the other 1/16th being written by an
         | LLM. Figuring out how to work effectively together as a team
         | requires solving the same problem you describe. For me, an LLM
         | is like having another junior developer on the team.
         | 
         | How you get good results as a team is to develop a shared
         | mental model, and that typically needs to exist in design docs.
         | I find that without design docs, we all agree verbally, and
         | then are shocked at what everyone else thought we'd agreed on.
         | Write it down.
         | 
         | LLMs, like junior devs, do much better with design docs. You
         | can even let the junior dev try writing some design docs.
         | 
         | So if you're a solo developer, I can see this would be a big
         | change for you. Anyone working on a team has already had to
         | solve this problem.
         | 
         | On the subject of ownership: if I commit it, I own it. If the
         | internet "goes down" and the commit has got my name on it, "but
         | AI" isn't going to cut it.
        
       | chasing wrote:
       | LLMs save me a lot of time as a software engineer because they
       | save me a ton of time doing either boilerplate work or mundane
       | tasks that are relatively conceptually easy but annoying to
       | actually have to do/type/whatever in an IDE.
       | 
       | But I still more-or-less have to think like a software engineer.
       | That's not going to go away. I have to make sure the code remains
       | clean and well-organized -- which, for example, LLMs can help
       | with, but I have to make precision requests and (most
       | importantly) know specifically what I mean by "clean and well-
       | organized." And I always read through and review any generated
       | code and often tweak the output because at the end of the day I
       | am responsible for the code base and I need to verify quality and
       | I need to be able to answer questions and do all of the usual
       | soft-skill engineering stuff. Etc. Etc.
       | 
       | So do whatever fits your need. I think LLMs are a massive
       | multiplier because I can focus on the actual engineering stuff
       | and automate away a bunch of the boring shit.
       | 
       | But when I read stuff like:
       | 
       | "I lost all my trust in LLMs, so I wouldn't give them a big
       | feature again. I'll do very small things like refactoring or a
       | very small-scoped feature."
       | 
       | I feel like I'm hearing something like, "I decided to build a
       | house! So I hired some house builders and told them to build me a
       | house with three bedrooms and two bathrooms and they wound up
       | building something that was not at all what I wanted! Why didn't
       | they know I really liked high ceilings?"
        
         | patrickmay wrote:
         | > [LLMs] save me a ton of time doing either boilerplate work
         | 
         | I hear this frequently from LLM aficionados. I have a couple of
         | questions about it:
         | 
         | 1) If there is so much boilerplate that it takes a significant
         | amount of coding time, why haven't you invested in abstracting
         | it away?
         | 
         | 2) The time spent actually writing code is not typically the
         | bottleneck in implementing a system. How much do you really
         | save over the development lifecycle when you have to review the
         | LLM output in any case?
        
           | hedgehog wrote:
           | I don't know about the boilerplate part but when you are e.g.
           | adding a new abstraction that will help simplify an existing
           | pattern across the code base something like Copilot saves a
           | ton of time. Write down what has to happen and why, then let
           | the machine walk across the code base and make updates,
           | update tests and docs, fix whatever ancillary breaks happen,
           | etc. The real payoff is making it cheaper to do exploratory
           | refactors and simple features so you can focus on making the
           | code and overall design better.
        
             | patrickmay wrote:
             | That's an interesting approach. You still have to review
             | all the changes to make sure they're correct and that the
             | code is maintainable, though. I could see this being a net
             | savings on a legacy code base or a brand new system still
             | in the "sketching" phase.
        
               | hedgehog wrote:
               | Yes, one of the reasons I like Copilot over some of the
               | terminal-based systems I've seen is the changes are all
               | staged for review in VS Code so you have all the
               | navigation etc tools and can do whatever needs to be done
               | before committing. It saves a lot of time, even on new
               | features. I think of it like a chainsaw, powerful but a
               | little bit imprecise.
        
         | emilecantin wrote:
         | I'm in a similar boat. I've only started using it more very
         | recently, and it's really helping my "white-page syndrome" when
         | I'm starting a new feature. I still have to fix a bunch of
         | stuff, but I think it's easier for me to fix, tweak and
         | refactor existing code than it is to write a new file from
         | scratch.
         | 
         | Often times there's a lot of repetition in the app I'm working
         | on, and there's a lot of it that's already been abstracted
         | away, but we still have to import the component, its
         | dependencies, and setup the whole thing which is indeed pretty
         | boring. It really helps to tell the LLM to implement something
         | and point it to an example of the style I want.
        
           | patrickmay wrote:
           | Maybe it's my Lisp background, where it's arguably easier,
           | but I find myself immediately thinking "Eliminate that
           | repetition."
        
           | extr wrote:
           | This is the killer app for LLMs for me. I used to get super
           | bogged down in the details of what I was trying to do, I
           | would go a whole afternoon and while I would have started on
           | the feature - I wouldn't have much to show for it in terms of
           | working functionality. LLMs just provide a direction to go in
           | and "get something up" before having to think through every
           | little edge case and abstraction. Later once I have a a
           | better idea of what I want, I go in and refactor by hand. But
           | at least "it works" temporarily, and I find refactoring more
           | enjoyable than writing fresh code anyway, primarily due to
           | that "white page" effect you mention.
        
       | ramon156 wrote:
       | I like Zed's way of doing stuff (Ask mode). Just ask it a
       | question and let it go through the whole thing. I still haven't
       | figured out how to form the question so it doesn't just rail off
       | and start implementing code. I don't care about code, I ask it to
       | either validate my mental model or improve it
        
         | xattt wrote:
         | This is it. This is a new paradigm and a lot of people seem to
         | think that it's authoritative. It's decision support tool, and
         | the output still has to pass an internal litmus test.
         | 
         | Whether someone's litmus test is well-developed is another
         | matter.
        
       | jjice wrote:
       | My favorite use case for LLMs in long term software production
       | (they're pretty great at one off stuff since I don't need to
       | maintain) is as an advanced boiler plate generator.
       | 
       | Stuff that can't just be abstracted to a function or class but
       | also require no real thought. Tests are often (depending on what
       | they're testing) in this realm.
       | 
       | I was resistant at first, but I love it. It's reduced the parts
       | of my job that I dislike doing because of how monotonous they are
       | and replaced them with a new fun thing to do - optimizing prompts
       | that get it done for me much faster.
       | 
       | Writing the prompt and reviewing the code is _so_ much faster on
       | tedious simple stuff and it leaves the interesting, though
       | provoking parts of my work for me to do.
        
       | noisy_boy wrote:
       | I think they are making me more productive in achieving my
       | targets and worse in my ability to program.
       | 
       | They are exactly like steroids - bigger muscles fast but tons of
       | side effects and everything collapses the moment you stop.
       | Companies don't care because they are more concerned about
       | getting to their targets fast instead of your health.
       | 
       | Another harmful drug for our brain if consumed without
       | moderation. I won't entirely stop using them but I have already
       | started to actively control/focus my usage.
        
         | criddell wrote:
         | Your steroids comparison made me think of Cal Newport's recent
         | blog post[1] where he argues that AI is making us lazy. He
         | quotes some researchers who hooked people up to EEG machines
         | then had them work. The people working without AI assistance
         | incurred more brain "strain" and that's probably a good thing.
         | 
         | But even he doesn't think AI shouldn't be used. Go ahead and
         | use it for stuff like email but don't use it for your core
         | work.
         | 
         | [1] https://calnewport.com/does-ai-make-us-lazy/
        
           | causal wrote:
           | I haven't read the entire paper, but just looking at the
           | abstract and conclusion it ironically seems...lazy? Like
           | we're going to have some people use ChatGPT 4 times in 4
           | months and draw conclusions on long-term brain activity based
           | on that? How do you even control for noise in such a study?
           | 
           | I'm generally sympathetic to the idea that LLMs can create
           | atrophy in our ability to code or whatever, but I dislike
           | that this clickbaity study gets shared so much.
        
           | ukFxqnLa2sBSBf6 wrote:
           | Of all the things I think AI shouldn't be used for AI is one
           | of them (unless you're like completely illiterate). Whenever
           | I get a "project status update" and the section header emojis
           | show up I instantly just want to throw that garage in the
           | trash.
        
             | Tijdreiziger wrote:
             | That usage of emoji predates LLMs.
        
           | smeeth wrote:
           | It's worth noting this is the exact argument people used
           | against adopting electric calculators.
        
             | thoughtpeddler wrote:
             | Calculators are a very narrow form of intelligence as
             | compared to the general-purpose intelligence that LLMs are.
             | The muscle/steroid analogy from this same discussion thread
             | is apt here. Calculators enhanced and replaced just one
             | 'muscle', so the argument against them would be like "ya
             | but do we really need this one muscle anymore?", whereas
             | with LLMs the argument is "do we really even need a body at
             | all anymore?" (if extrapolated out several more years into
             | the future).
        
               | smeeth wrote:
               | You don't need the analogy. If you have a tool that does
               | a job for you your capacity to do the job degrades
               | alongside other associated skills.
               | 
               | Tools that do many things and tools that do a small
               | number of things are still tools.
               | 
               | > "do we really even need a body at all anymore?"
               | 
               | It's a legitimate question. What's so special about the
               | body and why do we need to have one? Would life be better
               | or worse without bodies?
               | 
               | Deep down I think everyone's answer has more to do with
               | spirituality than anything else. There isn't a single
               | objectively correct response.
        
       | jimbokun wrote:
       | I think LLMs have made a lot of developers forget the lessons in
       | "Simple Made Easy":
       | 
       | https://www.youtube.com/watch?v=SxdOUGdseq4
       | 
       | LLMs seem to be really good at reproducing the classic Ball of
       | Mud, that can't really be refactored or understood.
       | 
       | There's a lot of power in creating simple components that
       | interact with other simple components to produce complex
       | functionality. While each component is easy to understand and
       | debug and predict its performance. The trick is to figure out how
       | to decompose your complex problem into these simple components
       | and their interactions.
       | 
       | I suppose once LLMs get really good at that skill, will be when
       | we really won't need developers any more.
        
         | globular-toast wrote:
         | > I suppose once LLMs get really good at that skill, will be
         | when we really won't need developers any more.
         | 
         | I don't really get this argument. So when LLMs become "perfect"
         | software developers are we just going to have them running 24/7
         | shitting out every conceivable piece of software ever? What
         | would anyone do with that?
         | 
         | Or do you expect every doctor, electrician, sales assistant,
         | hairdresser, train driver etc. to start developing their own
         | software on top of their existing job?
         | 
         | What's more likely is a few people will make it their jobs to
         | find and break down problems people have that could use a piece
         | of software and develop said piece of software using whatever
         | means they have available to them. Today we call these people
         | software developers.
        
           | breckenedge wrote:
           | > Or do you expect every doctor, electrician, sales
           | assistant, hairdresser, train driver etc. to start developing
           | their own software on top of their existing job?
           | 
           | I started my software career by automating my job, then
           | automating other people's jobs. Eventually someone decided it
           | would be easier to just hire me as a software engineer.
           | 
           | I just met with an architect for adding a deck onto my house
           | (need plans for code compliance). He said he was using AI to
           | write programs that he could use with design software. He
           | demoed how he was using AI to convert his static renders into
           | walkthrough movies.
        
         | kraftman wrote:
         | you can tell them what to do though right? I think a lot of
         | variance between people that say LLMs are useless and people
         | that say they are useful is people that learn what they are
         | good and bad at and can predict the quality of the output based
         | on their input.
         | 
         | Like, I might ask an LLM on its opinion on the best way to
         | break something down, to see if it 'thinks' of anything i
         | havent, and then ask it to implement that. I wouldn't ask it to
         | do the whole thing from scratch with no input on how to
         | structure things.
        
           | apwell23 wrote:
           | > you can tell them what to do though right?
           | 
           | kind of.
        
         | osmsucks wrote:
         | > LLMs seem to be really good at reproducing the classic Ball
         | of Mud, that can't really be refactored or understood.
         | 
         | This, but but only for code. I've seen "leaders" at work
         | suggest that we "embrace" AI, even for handling production
         | systems and managing their complexity. That's like saying:
         | "We've built this obscure, inscrutable system, therefore we
         | need another obscure, inscrutable system on top of it in order
         | to understand it!". To me, this sounds deranged, but the amount
         | of gaslighting that's going on also makes you think you're the
         | only to believe that...
        
       | kadhirvelm wrote:
       | I wonder if this is as good as LLMs can get, or if this is a
       | transition period between LLM as an assistant, and LLM as a
       | compiler. Where in the latter world we don't need to care about
       | the code because we just care about the features. We let the LLM
       | deal with the code and we deal with the context, treating code
       | more like a binary. In that world, I'd bet code gets the same
       | treatment as memory management today, where only a small percent
       | of people need to manage it directly and most of us assume it
       | happens correctly enough to not worry about it.
        
         | rzz3 wrote:
         | Why wonder if this is "as good as LLMs can get" when we saw
         | such a huge improvement between Claude 3.7 and Claude 4,
         | released what, a couple weeks ago? Of course it isn't as good
         | as LLMs can get. Give it 3 more weeks and you'll see it get
         | better again.
        
           | kadhirvelm wrote:
           | I don't doubt LLMs will become better assistants over time,
           | as you said every few weeks. I more mean if LLMs will cross
           | the assistant to compiler chasm where we don't have to think
           | about the code anymore and can focus on just the features
        
       | e12e wrote:
       | Previous discussion on the linked blog post:
       | 
       | https://news.ycombinator.com/item?id=44003700
        
       | sarmadgulzar wrote:
       | Can relate. I've also shifted towards generating small snippets
       | of code using LLMs, giving them a glance, and asking to write
       | unit tests for them. And then I review the unit tests carefully.
       | But integrating the snippets together into the bigger system, I
       | always do that myself. LLMs can do it sometimes but when it
       | becomes big enough that it can't fit into the context window,
       | then it's a real issue because now LLMs doesn't know what's going
       | on and neither do you. So, I'll advise you to use LLMs to
       | generate tedious bits of code but you must have the overall
       | architecture committed into your memory as well so that when AI
       | messes up, at least you have some clue about how to fix it.
        
         | causal wrote:
         | What's it called when you choose a task because it's easy, even
         | if it's not what you need to do at all? I think that's what
         | LLMs have activated in a lot of us: writing code used to be
         | kinda hard, but now it's super easy, so let's just write more
         | code.
         | 
         | The hard parts of engineering have always been decision making,
         | socializing, and validating ideas against cold hard reality.
         | But writing code just got easier so let's do that instead.
         | 
         | Prior to LLMs writing 10 lines of code might have been a really
         | productive day, especially if we were able to thoughtfully
         | avoid writing 1,000 unnecessary lines. LLMs do not change this.
        
           | Velorivox wrote:
           | I'm not sure if there's a name for that specifically, but it
           | seems strongly related to the streetlight effect. [0]
           | 
           | [0] https://en.wikipedia.org/wiki/Streetlight_effect
        
             | causal wrote:
             | Yeah very apt
        
       | veselin wrote:
       | I think that people are just too quick to assume this is amazing,
       | before it is there. Which doesn't mean it won't get there.
       | 
       | Somehow if I take the best models and agents, most hard coding
       | benchmarks are at below 50% and even swe bench verified is like
       | at 75 maybe 80%. Not 95. Assuming agents just solve most problems
       | is incorrect, despite it being really good at first prototypes.
       | 
       | Also in my experience agents are great to a point and then fall
       | off a cliff. Not gradually. Just the type of errors you get past
       | one point is so diverse, one cannot even explain it.
        
       | hedgehog wrote:
       | Over the last couple months I've gone from highly skeptical to a
       | regular user (Copilot in my case). Two big things changed: First,
       | I figured out that only some models are good enough to do the
       | tasks I want (Claude Sonnet 3.7 and 4 out of everything I've
       | tested). Second, it takes some infrastructure. I've added around
       | 1000 words of additional instructions telling Copilot how to
       | operate, and that's on top of tests (which you should have
       | anyway) and 3rd party documentation. I haven't tried the fleet-
       | of-agents thing, one VS Code instance is enough and I want to
       | understand the changes in detail.
       | 
       | Edit: In concrete terms the workflow is to allow Copilot to make
       | changes, see what's broken, fix those, review the diff against
       | the goal, simplify the changes, etc, and repeat, until the
       | overall task is done. All hands off.
        
       | Const-me wrote:
       | I'm using ChatGPT (enterprise version paid by my employer) quite
       | a lot lately, and I find it a useful tool. Here's what I learned
       | over time.
       | 
       | Don't feed many pages of code to AI, it works best for isolated
       | functions or small classes with little dependencies.
       | 
       | In 10% of cases when I ask to generate or complete code, the
       | quality of the code is less than ideal but fixable with extra
       | instructions. In 25% of cases, the quality of generated code is
       | bad and remains so even after telling it what's wrong and how to
       | fix. When it happens, I simply ignore the AI output and do
       | something else reasonable.
       | 
       | Apart from writing code, I find it useful at reviewing new code I
       | wrote. Half of the comments are crap and should be ignored. Some
       | others are questionable. However, I remember a few times when the
       | AI identified actual bugs or other important issues in my code,
       | and proposed fixes. Again, don't copy-paste many pages at once,
       | do it piecewise.
       | 
       | For some niche areas (examples are HLSL shaders, or C++ with SIMD
       | intrinsics) the AI is pretty much useless, probably was not
       | enough training data available.
       | 
       | Overall, I believe ChatGPT improved my code quality. Not only as
       | a result of reviews, comments, or generated codes, but also my
       | piecewise copy-pasting workflow improved overall architecture by
       | splitting the codebase into classes/functions/modules/interfaces
       | each doing their own thing.
        
         | wombat-man wrote:
         | Yeah the code review potential is big. I just started using AI
         | for this and it's pretty handy.
         | 
         | I agree it's good for helping writing smaller bits like
         | functions. I also use it to help me write unit tests which can
         | be kind of tedious otherwise.
         | 
         | I do think that the quality of AI assistance has improved a lot
         | in the past year. So if you tried it before, maybe take another
         | crack at it.
        
       | xyst wrote:
       | Just like garbage sources on search engines or trash stack
       | overflow answers. There's still plenty of junk to sift through
       | with LLM.
       | 
       | LLM will even through irrelevant data points in the output which
       | causes further churn.
       | 
       | I feel not much has changed.
        
       | turbofreak wrote:
       | Is this Zed Shaw's blog?
        
         | gpm wrote:
         | Nah, it's the people/company behind the Zed editor, who are in
         | part the people who were originally behind the Atom editor.
         | https://zed.dev/team
        
       | andy99 wrote:
       | I'm realizing that LLMs, for coding in particular but also for
       | many other tasks, are a new version of the fad dieting
       | phenomenon.
       | 
       | People really want a quick, low effort fix that appeals to the
       | energy conserving lizard brain while still promising all the
       | results.
       | 
       | In reality there aren't shortcuts, there's just tradeoffs, and we
       | all realize it eventually.
        
       | AsmodiusVI wrote:
       | Really appreciated this take, hits close to home. I've found LLMs
       | great for speed and scaffolding, but the more I rely on them, the
       | more I notice my problem-solving instincts getting duller.
       | There's a tradeoff between convenience and understanding, and
       | it's easy to miss until something breaks. Still bullish on using
       | AI for exploring ideas or clarifying intent, but I'm trying to be
       | more intentional about when I lean in vs. when I slow down and
       | think things through myself.
        
       | kamens wrote:
       | Personally, I follow the simple rule: "I type every single
       | character myself. The AI/agent/etc offers inspiration." It's an
       | effective balance between embracing what the tech can do (I'm
       | dialing up my usage) and maintaining my personal connection to
       | the code (I'm having fun + keeping things in my head).
       | 
       | I wrote about it: https://kamens.com/blog/code-with-ai-the-hard-
       | way
        
       | thimkerbell wrote:
       | We need an app to rate posts on how clickbaity their titles are,
       | and let you filter on this value.
        
       | jjangkke wrote:
       | The problem with zed's narrative is that because he failed to use
       | it in productive ways he wants to dial it back altogether but its
       | not clear what he has actually attempted and people dogpiling
       | here reminds me of artists who are hostile to AI tools, it
       | doesn't accurately reflect the true state of the marketplace
       | which actually puts a lot of value on successful LLM/AI tool use
       | especially in the context of software development.
       | 
       | If you extrapolate this blog then we shouldn't be having so much
       | success with LLMs, we shouldn't be able to ship product with
       | fewer people, and we should be hiring junior developers.
       | 
       | But the truth of the matter is, especially for folks that work on
       | agents focusing on software development is that we can see a huge
       | tidal shift happening in ways similar to artists, photographers,
       | translators and copywriters have experienced.
       | 
       | The blog sells the idea that LLM is not productive and needs to
       | be dialed down does not tell the whole story. This does not mean
       | I am saying LLM should be used in all scenarios, there are
       | clearly situations where it might not be desirable, but overall
       | the productivity hinderance narrative I repeatedly see on HN
       | isn't convincing and I suspect is highly biased.
        
         | tequila_shot wrote:
         | so, this is not from a developer called zed, but instead a
         | developer called Alberto. This is stated in the first line in
         | the article.
        
       | delusional wrote:
       | I wish there was a browser addon that worked like ublock but for
       | LLM talk. Like just take it all, every blog post, every
       | announcement, every discussion and wipe it all away. I just want
       | humanity to deal with some of our actual issues, like fascism,
       | war in Europe and the middle east, the centralization of our
       | lines of production, the unfairness in our economies.
       | 
       | Instead we're stuck talking about if the lie machine can fucking
       | code. God.
        
         | lucasluitjes wrote:
         | Ironically if you wanted to build that accurately and quickly,
         | you would probably end up having an LLM classify content as
         | being LLM-related or not. Keyword-based filtering would have
         | many false positives, and training a model takes more time to
         | build.
        
         | pmxi wrote:
         | I'm sure you could build a prototype add on to do this pretty
         | quickly with Claude Code or the like
        
       | bgwalter wrote:
       | This is still an ad that tries to lure heretics in by agreeing
       | with them. This is the new agile religion. Here are suit-
       | optimized diagrams:
       | 
       | https://zed.dev/agentic-engineering
       | 
       | "Interwoven relationship between the predictable &
       | unpredictable."
        
       | incomingpain wrote:
       | Using gemini cli, I really need to try out claude code 1 day, and
       | you ask it to make a change and it gives you the diff on what it
       | plans to change.
       | 
       | You can say no, then give it more specific instructions like
       | "keep it more simple" or "you dont need that library to be
       | imported"
       | 
       | You can read the code and ensure you understand what it's doing.
        
       | specproc wrote:
       | I spent today rewriting a cloud function I'd done with the "help"
       | of an LLM.
       | 
       | Looked like dog shit, but worked fine till it hit some edge
       | cases.
       | 
       | Had to break the whole thing down again and pretty much start
       | from scratch.
       | 
       | Ultimately not a bad day's work, and I still had it on for
       | autocomplete on doc-strings and such, but like fuck will I be
       | letting an agent near code I do for money again in the near
       | future.
        
       | obirunda wrote:
       | The dichotomy between the people who are "orchestrating" agents
       | to build software and the people experiencing this less than
       | ideal outcomes from LLMs is fascinating.
       | 
       | I don't think LLM for coding productivity is all hype but I think
       | for the people who "see the magic" there are many illusions here
       | similar to those who fall prey to an MLM pitch.
       | 
       | You can see all the claims aren't necessarily unfounded, but the
       | lack of guaranteed reproducibility leaves the door open for many
       | caveats in favor of belief for the believer and cynicism for
       | everybody else.
       | 
       | For the believers if it's not working for one person, it's a
       | skill issue related to providing the best prompt, the right
       | rules, the perfect context and so forth. At what point is this a
       | roundabout way of doing it yourself anyway?
        
       | stephendause wrote:
       | One point I haven't seen made elsewhere yet is that LLMs can
       | occasionally make you _less_ productive. If they hallucinate a
       | promising-seeming answer and send you down a path that you wouldn
       | 't have gone down otherwise, they can really waste your time. I
       | think on net, they are helpful, especially if you check their
       | sources (which might not always back up what they are saying!).
       | But it's good to keep in mind that sometimes doing it yourself is
       | actually faster.
        
       | KaiMagnus wrote:
       | I've been starting my prompts more and more with the phrase
       | ,,Let's brainstorm".
       | 
       | Really powerful seeing different options, especially based on
       | your codebase.
       | 
       | > I wouldn't give them a big feature again. I'll do very small
       | things like refactoring or a very small-scoped feature.
       | 
       | That really resonates with me. Anything larger often ends badly
       | and I can feel the ,,tech debt" building in my head with each
       | minute Copilot is running. I do like the feeling though when you
       | understood a problem already, write a detailed prompt to nudge
       | the AI into the right direction, and it executes just like you
       | wanted. After all, problem solving is why I'm here and writing
       | code is just the vehicle for it.
        
       | i_love_retros wrote:
       | Uh oh, I think the bubble is bursting.
       | 
       | Personally the initial excitement has worn off for me and I am
       | enjoying writing code myself and just using kagi assistant to ask
       | the odd question, mostly research.
       | 
       | When a team mate who bangs on about how we should all be using ai
       | tried to demo it and got things in a bit of a mess, I knew we had
       | peaked.
       | 
       | And all that money invested into the hype!
        
       | href wrote:
       | I've dialed down a lot as well. The answers I got for my queries
       | were too often plain wrong.
       | 
       | I instead started asking where I might look something up - in
       | what man page, or in which documentation. Then I go read that.
       | 
       | This helps me build a better mental map about where information
       | is found (e.g., in what man page), decreasing both my reliance on
       | search engines, and LLMs in the long run.
       | 
       | LLMs have their uses, but they are just a tool, and an imprecise
       | one at that.
        
       | dwoldrich wrote:
       | I personally believe it's a mistake to invite AI into your
       | editor/IDE. Keep it separate to the browser, keep discrete,
       | concise question and answer threads. Copy and paste whenever it
       | delivers some gold (that comes with all the copy-pasta dangers, I
       | know - oh, don't I know it!)
       | 
       | It's important to always maintain the developer role, don't ever
       | surrender it.
        
       | somewhereoutth wrote:
       | Unfortunately it seems that nobody 'dialed back' LLM usage for
       | the summary on that page - a good example of how un-human such
       | text can feel to read.
        
       | 65 wrote:
       | LLMs require fuzzy input and are thus good for fuzzy output,
       | mostly things like recommendations and options. I just do not see
       | a scenario where fuzzy input can lead to absolute, opinionated
       | output unless extremely simple and mostly done before already.
       | Programming, design, writing, etc. all require opinions and an
       | absolute output from the author to be quality.
        
       | Gepsens wrote:
       | Llms are not a magic wand you can wave at anything and get your
       | work cut out for you. What's new ?
        
       | piker wrote:
       | Credit to the Zed team here for publishing something somewhat
       | against its book.
        
       | nvahalik wrote:
       | Sounds like he shot for the moon and missed.
       | 
       | I've been allowing LLMs to do more "background" work for me.
       | Giving me some room to experiment with stuff so that I can come
       | back in 10-15 minutes and see what it's done.
       | 
       | The key things I've come to are that it HAS to be fairly limited.
       | Giving it a big task like refactoring a code base won't work.
       | Giving it an example can help dramatically. If you haven't
       | "trained" it by giving it context or adding your CLAUDE.md file,
       | you'll end up finding it doing things you don't want it to do.
       | 
       | Another great task I've been giving it while I'm working on other
       | things is generating docs for existing features and modules. It
       | is surprisingly good at looking at events and following those
       | events to see where they go and generating diagrams and he like.
        
       | cadamsdotcom wrote:
       | LLMs give you a power tool after you spent your whole career
       | using hand tools.
       | 
       | A chainsaw and chisel do different things and are made for
       | different situations. It's great to have chainsaws, no longer
       | must we chop down a giant tree with a chisel.
       | 
       | On the other hand there's plenty of room in the trade for
       | handcraft. You still need to use that chisel to smooth off the
       | fine edges of your chainsaw work, so your teammates don't get
       | splinters.
        
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