6 ms·

How useful the various tools will be depends on the person and the problem. Take two hypothetical people working on different problems and consider if, for exam

How useful the various tools will be depends on the person and the problem. Take two hypothetical people working on different problems and consider if, for example, Cursor would be useful. IF you're a: * 10 year python dev * work almost entirely on a very large, complex python code base * have a pycharm IDE fine tuned over many years to work perfectly on that code base * have very low tolerance for bugs (stable product, no room for move fast, break things) THEN: LLMs aren't going to 10x you. An IDE like Cursor will likely make you slower for a very long time until you've learned to use it. IF you're a: * 1 year JS (react, nextjs, etc.) dev * start mostly from scratch on new ideas * have little prior IDE preference * have high tolerance for bugs and just want to ship and try stuff THEN: LLMs will to 10x you. An IDE like Cursor will immediately make you way faster.

emseetech 1y ago
Agreed but the 1 year JS dev should know they're making a deal with the devil in terms of building their skillset long term.
- StefanBatory 1y ago
  From workplace perspective, they don't have a reason to care. What they'll care about is that you're productive right now - if you won't become better dev in the future? Your issue.
- whiplash451 1y ago
  The jury is still out on that one. Having a tool that’s embedded into your workflow and shows you how things can be done based on tons of example codebases could help a junior dev quite a lot to learn, not just to produce.
  - _heimdall 1y ago
    Like anything else with learning, that will be heavily dependent on the individual's level of motivation. Based on the classmates I had in college who were paying to get a CS degree, I'd be surprised if many junior devs already working a paid job put much effort into learning rather than producing.
    - whiplash451 1y ago
      I wouldn't dismiss the implicit/subconscious aspect of learning by example that occurs when you are "just" producing.
      - _heimdall 1y ago
        That still comes back to motivation in my opinion. Using an LLM to generate code and using it without studying the code and understanding it will teach you very little. I'd still expect most junior Deva that use an LLM to get their job done won't be motivated to study the generated code enough to really learn it. A student is also only as good as the teacher, though that's a whole other can of works with LLMs.
- deleted 1y ago
  [deleted]
- diggan 1y ago
  I basically learned programming by ExpertSexchange, Google (and Altavista...), SourceForge and eventually StackOverflow + GitHub. Many people with more experience than me at the time always told me I was making a deal with the devil since I searched so much, didn't read manuals and asked so many questions instead of thinking for myself. ~15 years later, I don't think I'm worse off than my peers who stayed away from all those websites. Doing the right searches is probably as important as being able to read manuals properly today.
  - GeoAtreides 1y ago
    >I basically learned programming by ExpertSexchange, Google (and Altavista...), SourceForge and eventually StackOverflow + GitHub. Many people with more experience than me at the time always told me I was making a deal with the devil since I searched so much, didn't read manuals and asked so many questions instead of thinking for myself. no they didn't, no one said that i know that because i was around then and everyone was doing the same thing also, maybe there's a difference between searching and collating answers and just copy and pasting a solution _without thinking_ at all
    - diggan 1y ago
      > no they didn't, no one said that You're right, probably hallucinated memory of much more senior people telling me exactly that. > i know that because i was around then and everyone was doing the same thing Damn, we worked together in the same company at that time? Nice to meet you again after all these years. Still thinking of picking up farming once you get out of prison?
  - andrekandre 1y ago
    > ExpertSexchange maybe should have added a space somewhere in there?
    - diggan 1y ago
      I thought explicitly using wrong caps would be enough for most people to get it regardless :)
- aqme28 1y ago
  Maybe. But I also think that ignoring AI tools will hamper your long-term skillsets, as our profession adapts to these new tools.
  - bccdee 1y ago
    Why would that be the case? If anything, each successive generation of AI tools gets easier to use and requires less prompt fiddling. I picked up Cursor and was comfortable with it in 20 minutes. I'm not sure there's much of a skillset to speak of for these tools, beyond model-specific tricks that evaporate after a few updates.
maccard 1y ago
I’ve found the biggest thing LLMs and agents let me do are build the things that I really suck at to a prototype level. I’m not a frontend engineer, and pitching feature prototypes without a fronted is tough. But with aider/claude/bolt/whatever your tool of choice is, I can give it a handful of instructions and get a working page to demo my feature. It’s the difference between me pitching the feature or not, as opposed to pitching it with or without the frontend.
ekianjo 1y ago
> THEN: LLMs will to 10x you. An IDE like Cursor will immediately make you way faster. they will make you clueless about what the code does and your code will be unmaintanable.
diggan 1y ago
Taking your "to 10x you" as hyperbole and to actually mean "more productive", if you replace "Python" with "Programming" and "IDE" with Neovim, that's basically me. And I'm way more productive with LLMs than without them. Granted, I stay far away from "vibe coding", only use LLMs for some parts and don't use "agentic LLMs" or whatever, just my own programmed "Human creates issue on GitHub, receive N PRs back with implementations" bot. Basically, use LLMs as a tool for specific things, don't let them do whatever and everything.
infecto 1y ago
These all-or-nothing takes on LLMs are getting tiresome. I get the point you’re trying to make, LLMs can be a force multiplier for less experienced devs, but the sweeping generalizations don’t hold up. If you’re okay with a higher tolerance for bugs or loose guardrails, sure, LLMs can feel magical. But that doesn’t mean they’re less valuable to experienced developers. I’ve been writing Python and Java professionally for 15+ years. I’ve lived through JetBrains IDEs, and switching to VS Code took me days. If you’re coming from a heavily customized Vim setup, the adjustment will be harder. I don’t tolerate flaky output, and I work on a mix of greenfield and legacy systems. Yes, greenfield is more LLM-friendly, but I still get plenty of value from LLMs when navigating and extending mature codebases. What frustrates me is how polarized these conversations are. There are valid insights on both sides, but too many posts frame their take as gospel. The reality is more nuanced: LLMs are a tool, not a revolution, and their value depends on how you integrate them into your workflow, regardless of experience level.
- mexicocitinluez 1y ago
  > I get the point you’re trying to make, LLMs can be a force multiplier for less experienced devs, but the sweeping generalizations don’t hold up. If you’re okay with a higher tolerance for bugs or loose guardrails, sure, LLMs can feel magical. But that doesn’t mean they’re less valuable to experienced developers. Amen. Seriously. They're tools. Sometimes they work wonderfully. Sometimes, not so much. But I have DEFINITELY found value. And I've been building stuff for over 15 years as well. I'm not "vibe coding", I don't use Cursor or any of the ai-based IDEs. I just use Claude and Copilot since it's integrated.
  - voidhorse 1y ago
    > Amen. Seriously. They're tools. Sometimes they work wonderfully. Sometimes, not so much. But I have DEFINITELY found value. And I've been building stuff for over 15 years as well. Yes, but these lax expectation s are what I don't understand. What other tools in software sometimes work and sometimes don't that you find remotely acceptable? Sure all tools have bugs, but if your compiler had the same failure rate and usability issues as an LLM you'd never use it. Yet for some reason the bar is so low for LLMs. It's insane to me how much people have indulged in the hype koolaid around these tools.
cbm-vic-20 1y ago
I've got over 30 years of professional development experience, and I've found LLMs most useful for * Figuring out how to write small functions (10 lines) in canonical form in a language that I don't have much experience with. This is so I don't end up writing Rust code as if it were Java. * Writing small shell pipelines that rely on obscure command line arguments, regexes, etc.
anonzzzies 1y ago
> until you've learned to use it You have the copilot mode which takes no learning at all which might give you some speedup, especially if you are doing repetitive stuff, it might even 10x+ you. You have cmdk mode which you need to prompt and seems to he a lobotomized version of chat. I find putting comments and waiting for the copilot mode to kick in better as then the way we got there is saved. Then there is agentic editing chat: that is the timewaster you speak off I believe, but what is there to learn? Sometimes it generates a metric ton of code, including in legacy massive code bases, that help, and often it just cannot do whatever. I don't think these cases you make, or at least, when the second one goes beyond the basics, are different. There is nothing to learn except that you need read all the code, decide what you want in tech detail and ask that of the agentic chat. Anything else fails beyond the basics and 'learning to use it' will be that but if you didn't know that after 5 minutes you definitely didn't do any 'fine tuned pycharm ide', ever. It is a tool that customizes code it ingested for your case specifically, if it can. That is it. If it never saw a case, it won't solve it, no matter what you 'learn to use'. And I am fine doing that in public: we use LLMs a lot and I can give you very simple cases that, besides (and often even that doesn't work) typing up the exact code, it will never fix with the current models. It just gets stuck doing meaningless changes with confidence.
- ekidd 1y ago
  > You have the copilot mode which takes no learning at all which might give you some speedup, especially if you are doing repetitive stuff, it might even 10x+ you. I have some grey hair and I've been programming since I was a kid. Using CoPilot autocompletion roughly doubles my productivity while cutting my code quality by 10%. This happens because I can see issues in autocompleted code far faster than I can type, thanks to years of reading code and reviewing other people's code. The 10% quality loss happens because my code is no longer lovingly hand-crafted single-author code. It effectively becomes a team project shared by me and the autocomplete. That 10% loss was inevitable as soon as I added another engineer, so it's usually a good tradeoff. Based on observation, I think my productivity boost is usually high compared to other seniors I've paired with. I see a lot of people who gain maybe 40% from Copilot autocomplete. But there is no world in which current AI is going to give me a 900% productivity boost when working in areas I know well. I am also quite happy to ask Deep Research tools to look up the most popular Rust libraries for some feature, and to make me a pretty table of pros and cons to skim. It's usually only 90% accurate, but it cuts my research time. I do know how to drive Claude Code, and I have gotten it to build a non-trivial web front-end and back-end that isn't complete garbage without writing more than a couple of dozen lines myself. This required the same skill set as working with an over-caffeinated intern with a lot of raw knowledge, but who has never written anything longer than 1,000 lines before. (Who is also a cheating cheater.) Maybe I would use it more if my job was to produce an endless succession of halfway decent 5,000-line prototypes that don't require any deep magic. Auto-complete plus Deep Research is my sweet spot right now.
belter 1y ago
We finally found a metric to identify the really valuable coders in my company :-)
stef25 1y ago
Recently I tried getting ChatGPT to help me build a Wordpress site (which I know nothing about), starting from an Adobe design file. It spent hours thinking, being confused and eventually failed completely. However it's great for simple "write a function that does X", which I could do myself but it would take longer, be boring and require several iterations to get it right. Having said that, blindly copying a few lines of ChatGPT code did lead to automated newsletters being sent out with the wrong content.
CuriouslyC 1y ago
16 year python dev who's done all that, lead multiple projects from inception to success, and I rarely manually code anymore. I can specify precisely what I want, and how I want it built (this is the key part), stub out a few files and create a few directories, and let an agent run wild but configured for static analysis tools/test suite to run after every iteration with the instructions to fix their mistakes before moving on. I can deliver 5k LoC in a day easily on a greenfield project and 10k if I sweat or there's a lot of boilerplate. I can do code reviews of massive multi-thousand line PRs in a few minutes that are better than most of the ones done by engineers I've worked with throughout a long career, the list just goes on and on. I only manually code stuff if there's a small issue that I see the LLM isn't understanding that I can edit faster than I can run another round of the agent, which isn't often. LLMs are a force multiplier for everyone, really senior devs just need to learn to use them as well as they've learned to use their current tools. It's like saying that a master archer proves bows are as good as guns because the archer doesn't know how to aim a rifle.
- mritchie712 1y ago
  were you immediately more productive in Cursor specifically? my point is exactly inline with your comment. The tools you get immediate value out of will vary based on circumstance. There's no silver bullet.
  - CuriouslyC 1y ago
    I use Aider, and I was already quite good at working with AI before that so there wasn't much of a learning curve other than figuring out how to configure it to automatically do the ruff/mypy/tests loop I'd already been doing manually. They key is that I've always had that prompt/edit/verify loop, and I've always leaned heavily on git to be able to roll back bad AI changes. Those are the skills that let me blow past my peers.
- mrweasel 1y ago
  Assuming that your workflow works, and the rest of us just need to learn to use LLMs equally effective, won't that plateau us at the current level of programming? The LLMs learn from examples, but if everyone uses LLMs to generate code, there's no new code to learn new features, libraries or methods from. The next generation of models are just going to be trained on the code generated by it's predecessors with now new inputs. Being an LLM maximalist is basically freeze development in the present, now and forever.
alvis 1y ago
20+ years dev here, started coding with AI when Javis was still a thing (before it became Jasper, and way before Copilot or ChatGPT). Back then, Javis wasn’t built for code, but it was a surprisingly great coding companion. Yes. It only gave you 80% working code, but because you had to get your hands dirty, you actually understand what was happening. It didn't give me 10x but I'm happy with 2x with good understanding on what's going on. Fast-forward to now: Copilot, Cursor, roo code, windsurf and the rest are shockingly good at output, but sometimes the more fluent the AI, the sneakier the bugs. They hand you big chunks of code, and I bet most of us don't have a clear picture of what's going on at ground 0 but just an overall idea. It's just too tempting to blindly "accept all" the changes. It’s still the old wisdom — good devs are the ones not getting paged at 3am to fix bugs. I'm with the OP. I'm more happy with my 2x than waking up at 3am.
jrh3 1y ago
> have high tolerance for bugs and just want to ship LOL
deleted 1y ago
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nis251413 1y ago
Even a single person may do different things that will change whether using an LLM helps or not. Much of the time I spend writing code, not thinking about the general overview etc but about the code I am about to write itself, and if I actually care about the actual code (eg I am not gonna throw it away anyway by the end of the day) it is about how to make it as concise and understandable to others (incl future me) as possible, what cases to care about, what choices to make so that my code remain maintainable after a few days. It may be about refactoring previous code and all the decisions that go with that. LLM generated code, imo, is too bloated; them putting stuff like asserts is always a hit or miss about what they will think is important or not. Their comments tend to be completely trivial, instead of stating the intention of stuff, and though I have put some effort in getting them use a coding style similar to mine, they often fail there too. In such cases, I only use them if the code they write can be isolated enough, eg write a straightforward, auxiliary function here and there that will be called in some places but does not matter as much what happens in there. There are just too many decisions at each step that LLMs are not great at resolving ime. I depend more on LLMs if I care less about maintenability of the code itself and more about getting it done as fast as possible, or if I am just exploring and do not actually care about the code at all. For example, it can be I am in a rush to get sth done and care about the rest later (granted they can actually do the task, else I am losing time). But when I tried this for my main work, it soon became a mess that would take more time to fix even if they seem like speeding me up initially. Granted, if my field was different and the languages I was using more popular/represented in training data, I may have found more uses for them, but I still think that after some point it becomes unsustainable to leave decisions to them.
palmotea 1y ago
> IF you're a: > * 1 year JS (react, nextjs, etc.) dev > * start mostly from scratch on new ideas > * have little prior IDE preference > * have high tolerance for bugs and just want to ship and try stuff > THEN: LLMs will to 10x you. An IDE like Cursor will immediately make you way faster. And also probably dead-end you, and you'll stay the bug-tolerate 1 year JS dev for the next 10 years of your career. It's like eating your seed corn. Sure you'll be fat and have it easy for a little while, but then next year...
deleted 1y ago
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emseetech 1y ago

Agreed but the 1 year JS dev should know they're making a deal with the devil in terms of building their skillset long term.

StefanBatory 1y ago
From workplace perspective, they don't have a reason to care. What they'll care about is that you're productive right now - if you won't become better dev in the future? Your issue.
whiplash451 1y ago
The jury is still out on that one. Having a tool that’s embedded into your workflow and shows you how things can be done based on tons of example codebases could help a junior dev quite a lot to learn, not just to produce.
- _heimdall 1y ago
  Like anything else with learning, that will be heavily dependent on the individual's level of motivation. Based on the classmates I had in college who were paying to get a CS degree, I'd be surprised if many junior devs already working a paid job put much effort into learning rather than producing.
  - whiplash451 1y ago
    I wouldn't dismiss the implicit/subconscious aspect of learning by example that occurs when you are "just" producing.
    - _heimdall 1y ago
      That still comes back to motivation in my opinion. Using an LLM to generate code and using it without studying the code and understanding it will teach you very little. I'd still expect most junior Deva that use an LLM to get their job done won't be motivated to study the generated code enough to really learn it. A student is also only as good as the teacher, though that's a whole other can of works with LLMs.
deleted 1y ago
[deleted]
diggan 1y ago
I basically learned programming by ExpertSexchange, Google (and Altavista...), SourceForge and eventually StackOverflow + GitHub. Many people with more experience than me at the time always told me I was making a deal with the devil since I searched so much, didn't read manuals and asked so many questions instead of thinking for myself. ~15 years later, I don't think I'm worse off than my peers who stayed away from all those websites. Doing the right searches is probably as important as being able to read manuals properly today.
- GeoAtreides 1y ago
  >I basically learned programming by ExpertSexchange, Google (and Altavista...), SourceForge and eventually StackOverflow + GitHub. Many people with more experience than me at the time always told me I was making a deal with the devil since I searched so much, didn't read manuals and asked so many questions instead of thinking for myself. no they didn't, no one said that i know that because i was around then and everyone was doing the same thing also, maybe there's a difference between searching and collating answers and just copy and pasting a solution _without thinking_ at all
  - diggan 1y ago
    > no they didn't, no one said that You're right, probably hallucinated memory of much more senior people telling me exactly that. > i know that because i was around then and everyone was doing the same thing Damn, we worked together in the same company at that time? Nice to meet you again after all these years. Still thinking of picking up farming once you get out of prison?
- andrekandre 1y ago
  > ExpertSexchange maybe should have added a space somewhere in there?
  - diggan 1y ago
    I thought explicitly using wrong caps would be enough for most people to get it regardless :)
aqme28 1y ago
Maybe. But I also think that ignoring AI tools will hamper your long-term skillsets, as our profession adapts to these new tools.
- bccdee 1y ago
  Why would that be the case? If anything, each successive generation of AI tools gets easier to use and requires less prompt fiddling. I picked up Cursor and was comfortable with it in 20 minutes. I'm not sure there's much of a skillset to speak of for these tools, beyond model-specific tricks that evaporate after a few updates.

maccard 1y ago

I’ve found the biggest thing LLMs and agents let me do are build the things that I really suck at to a prototype level. I’m not a frontend engineer, and pitching feature prototypes without a fronted is tough. But with aider/claude/bolt/whatever your tool of choice is, I can give it a handful of instructions and get a working page to demo my feature. It’s the difference between me pitching the feature or not, as opposed to pitching it with or without the frontend.

ekianjo 1y ago

> THEN: LLMs will to 10x you. An IDE like Cursor will immediately make you way faster. they will make you clueless about what the code does and your code will be unmaintanable.

diggan 1y ago

Taking your "to 10x you" as hyperbole and to actually mean "more productive", if you replace "Python" with "Programming" and "IDE" with Neovim, that's basically me. And I'm way more productive with LLMs than without them. Granted, I stay far away from "vibe coding", only use LLMs for some parts and don't use "agentic LLMs" or whatever, just my own programmed "Human creates issue on GitHub, receive N PRs back with implementations" bot. Basically, use LLMs as a tool for specific things, don't let them do whatever and everything.

infecto 1y ago

These all-or-nothing takes on LLMs are getting tiresome. I get the point you’re trying to make, LLMs can be a force multiplier for less experienced devs, but the sweeping generalizations don’t hold up. If you’re okay with a higher tolerance for bugs or loose guardrails, sure, LLMs can feel magical. But that doesn’t mean they’re less valuable to experienced developers. I’ve been writing Python and Java professionally for 15+ years. I’ve lived through JetBrains IDEs, and switching to VS Code took me days. If you’re coming from a heavily customized Vim setup, the adjustment will be harder. I don’t tolerate flaky output, and I work on a mix of greenfield and legacy systems. Yes, greenfield is more LLM-friendly, but I still get plenty of value from LLMs when navigating and extending mature codebases. What frustrates me is how polarized these conversations are. There are valid insights on both sides, but too many posts frame their take as gospel. The reality is more nuanced: LLMs are a tool, not a revolution, and their value depends on how you integrate them into your workflow, regardless of experience level.

mexicocitinluez 1y ago
> I get the point you’re trying to make, LLMs can be a force multiplier for less experienced devs, but the sweeping generalizations don’t hold up. If you’re okay with a higher tolerance for bugs or loose guardrails, sure, LLMs can feel magical. But that doesn’t mean they’re less valuable to experienced developers. Amen. Seriously. They're tools. Sometimes they work wonderfully. Sometimes, not so much. But I have DEFINITELY found value. And I've been building stuff for over 15 years as well. I'm not "vibe coding", I don't use Cursor or any of the ai-based IDEs. I just use Claude and Copilot since it's integrated.
- voidhorse 1y ago
  > Amen. Seriously. They're tools. Sometimes they work wonderfully. Sometimes, not so much. But I have DEFINITELY found value. And I've been building stuff for over 15 years as well. Yes, but these lax expectation s are what I don't understand. What other tools in software sometimes work and sometimes don't that you find remotely acceptable? Sure all tools have bugs, but if your compiler had the same failure rate and usability issues as an LLM you'd never use it. Yet for some reason the bar is so low for LLMs. It's insane to me how much people have indulged in the hype koolaid around these tools.

cbm-vic-20 1y ago

I've got over 30 years of professional development experience, and I've found LLMs most useful for * Figuring out how to write small functions (10 lines) in canonical form in a language that I don't have much experience with. This is so I don't end up writing Rust code as if it were Java. * Writing small shell pipelines that rely on obscure command line arguments, regexes, etc.

anonzzzies 1y ago

> until you've learned to use it You have the copilot mode which takes no learning at all which might give you some speedup, especially if you are doing repetitive stuff, it might even 10x+ you. You have cmdk mode which you need to prompt and seems to he a lobotomized version of chat. I find putting comments and waiting for the copilot mode to kick in better as then the way we got there is saved. Then there is agentic editing chat: that is the timewaster you speak off I believe, but what is there to learn? Sometimes it generates a metric ton of code, including in legacy massive code bases, that help, and often it just cannot do whatever. I don't think these cases you make, or at least, when the second one goes beyond the basics, are different. There is nothing to learn except that you need read all the code, decide what you want in tech detail and ask that of the agentic chat. Anything else fails beyond the basics and 'learning to use it' will be that but if you didn't know that after 5 minutes you definitely didn't do any 'fine tuned pycharm ide', ever. It is a tool that customizes code it ingested for your case specifically, if it can. That is it. If it never saw a case, it won't solve it, no matter what you 'learn to use'. And I am fine doing that in public: we use LLMs a lot and I can give you very simple cases that, besides (and often even that doesn't work) typing up the exact code, it will never fix with the current models. It just gets stuck doing meaningless changes with confidence.

ekidd 1y ago
> You have the copilot mode which takes no learning at all which might give you some speedup, especially if you are doing repetitive stuff, it might even 10x+ you. I have some grey hair and I've been programming since I was a kid. Using CoPilot autocompletion roughly doubles my productivity while cutting my code quality by 10%. This happens because I can see issues in autocompleted code far faster than I can type, thanks to years of reading code and reviewing other people's code. The 10% quality loss happens because my code is no longer lovingly hand-crafted single-author code. It effectively becomes a team project shared by me and the autocomplete. That 10% loss was inevitable as soon as I added another engineer, so it's usually a good tradeoff. Based on observation, I think my productivity boost is usually high compared to other seniors I've paired with. I see a lot of people who gain maybe 40% from Copilot autocomplete. But there is no world in which current AI is going to give me a 900% productivity boost when working in areas I know well. I am also quite happy to ask Deep Research tools to look up the most popular Rust libraries for some feature, and to make me a pretty table of pros and cons to skim. It's usually only 90% accurate, but it cuts my research time. I do know how to drive Claude Code, and I have gotten it to build a non-trivial web front-end and back-end that isn't complete garbage without writing more than a couple of dozen lines myself. This required the same skill set as working with an over-caffeinated intern with a lot of raw knowledge, but who has never written anything longer than 1,000 lines before. (Who is also a cheating cheater.) Maybe I would use it more if my job was to produce an endless succession of halfway decent 5,000-line prototypes that don't require any deep magic. Auto-complete plus Deep Research is my sweet spot right now.

belter 1y ago

We finally found a metric to identify the really valuable coders in my company :-)

stef25 1y ago

Recently I tried getting ChatGPT to help me build a Wordpress site (which I know nothing about), starting from an Adobe design file. It spent hours thinking, being confused and eventually failed completely. However it's great for simple "write a function that does X", which I could do myself but it would take longer, be boring and require several iterations to get it right. Having said that, blindly copying a few lines of ChatGPT code did lead to automated newsletters being sent out with the wrong content.

CuriouslyC 1y ago

16 year python dev who's done all that, lead multiple projects from inception to success, and I rarely manually code anymore. I can specify precisely what I want, and how I want it built (this is the key part), stub out a few files and create a few directories, and let an agent run wild but configured for static analysis tools/test suite to run after every iteration with the instructions to fix their mistakes before moving on. I can deliver 5k LoC in a day easily on a greenfield project and 10k if I sweat or there's a lot of boilerplate. I can do code reviews of massive multi-thousand line PRs in a few minutes that are better than most of the ones done by engineers I've worked with throughout a long career, the list just goes on and on. I only manually code stuff if there's a small issue that I see the LLM isn't understanding that I can edit faster than I can run another round of the agent, which isn't often. LLMs are a force multiplier for everyone, really senior devs just need to learn to use them as well as they've learned to use their current tools. It's like saying that a master archer proves bows are as good as guns because the archer doesn't know how to aim a rifle.

mritchie712 1y ago
were you immediately more productive in Cursor specifically? my point is exactly inline with your comment. The tools you get immediate value out of will vary based on circumstance. There's no silver bullet.
- CuriouslyC 1y ago
  I use Aider, and I was already quite good at working with AI before that so there wasn't much of a learning curve other than figuring out how to configure it to automatically do the ruff/mypy/tests loop I'd already been doing manually. They key is that I've always had that prompt/edit/verify loop, and I've always leaned heavily on git to be able to roll back bad AI changes. Those are the skills that let me blow past my peers.
mrweasel 1y ago
Assuming that your workflow works, and the rest of us just need to learn to use LLMs equally effective, won't that plateau us at the current level of programming? The LLMs learn from examples, but if everyone uses LLMs to generate code, there's no new code to learn new features, libraries or methods from. The next generation of models are just going to be trained on the code generated by it's predecessors with now new inputs. Being an LLM maximalist is basically freeze development in the present, now and forever.

alvis 1y ago

20+ years dev here, started coding with AI when Javis was still a thing (before it became Jasper, and way before Copilot or ChatGPT). Back then, Javis wasn’t built for code, but it was a surprisingly great coding companion. Yes. It only gave you 80% working code, but because you had to get your hands dirty, you actually understand what was happening. It didn't give me 10x but I'm happy with 2x with good understanding on what's going on. Fast-forward to now: Copilot, Cursor, roo code, windsurf and the rest are shockingly good at output, but sometimes the more fluent the AI, the sneakier the bugs. They hand you big chunks of code, and I bet most of us don't have a clear picture of what's going on at ground 0 but just an overall idea. It's just too tempting to blindly "accept all" the changes. It’s still the old wisdom — good devs are the ones not getting paged at 3am to fix bugs. I'm with the OP. I'm more happy with my 2x than waking up at 3am.

jrh3 1y ago

> have high tolerance for bugs and just want to ship LOL

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nis251413 1y ago

Even a single person may do different things that will change whether using an LLM helps or not. Much of the time I spend writing code, not thinking about the general overview etc but about the code I am about to write itself, and if I actually care about the actual code (eg I am not gonna throw it away anyway by the end of the day) it is about how to make it as concise and understandable to others (incl future me) as possible, what cases to care about, what choices to make so that my code remain maintainable after a few days. It may be about refactoring previous code and all the decisions that go with that. LLM generated code, imo, is too bloated; them putting stuff like asserts is always a hit or miss about what they will think is important or not. Their comments tend to be completely trivial, instead of stating the intention of stuff, and though I have put some effort in getting them use a coding style similar to mine, they often fail there too. In such cases, I only use them if the code they write can be isolated enough, eg write a straightforward, auxiliary function here and there that will be called in some places but does not matter as much what happens in there. There are just too many decisions at each step that LLMs are not great at resolving ime. I depend more on LLMs if I care less about maintenability of the code itself and more about getting it done as fast as possible, or if I am just exploring and do not actually care about the code at all. For example, it can be I am in a rush to get sth done and care about the rest later (granted they can actually do the task, else I am losing time). But when I tried this for my main work, it soon became a mess that would take more time to fix even if they seem like speeding me up initially. Granted, if my field was different and the languages I was using more popular/represented in training data, I may have found more uses for them, but I still think that after some point it becomes unsustainable to leave decisions to them.

palmotea 1y ago

> IF you're a: > * 1 year JS (react, nextjs, etc.) dev > * start mostly from scratch on new ideas > * have little prior IDE preference > * have high tolerance for bugs and just want to ship and try stuff > THEN: LLMs will to 10x you. An IDE like Cursor will immediately make you way faster. And also probably dead-end you, and you'll stay the bug-tolerate 1 year JS dev for the next 10 years of your career. It's like eating your seed corn. Sure you'll be fat and have it easy for a little while, but then next year...

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