10 ms·

With AI you need to think bigger

305 points by boznz 2y ago

finneganscat 2y ago
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pmarreck 2y ago
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- WesolyKubeczek 2y ago
  Accidentally thought too big
  - jm4rc05 2y ago
    https://imgs.xkcd.com/comics/is_it_worth_the_time.png https://imgs.xkcd.com/comics/is_it_worth_the_time.png
- boznz 2y ago
  bugger! More than two visitors to my web site and it falls apart, I might fork out the $10 for the better CPU and more memory option before I post something in future.
antonkar 2y ago
Agree, let’s build direct democratic simulated multiverse. Or at least make a digital back up of Earth. Or at least represent an LLM as a green field with objects, where humans are the only agents: you stand near a monkey, see chewing mouth nearby, go there (your prompt now is “monkey chews”), close by you see an arrow pointing at a banana, father away an arrow points at an apple, very far away at the horizon an arrow points at a tire (monkeys rarely chew tires). So things close by are more likely tokens, things far away are less likely, you see all of them at once (maybe you’re on top of a hill to see farther). This way we can make a form of static place AI, where humans are the only agents
- boznz 2y ago
  A simulation in a simulation... Neat!
  - antonkar 2y ago
    Thanks, I wrote extensively about it) If interested, you can find a link in my profile or ask anything here
    - boznz 2y ago
      Thanks I will take my time reading it, you certainly could never be criticized for thinking too small.
deleted 2y ago
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TZubiri 2y ago
Probably right at the end of your career is where this tool would be the most useful An undergrad using the hottest tech right of the bat? Cooked. It's like giving the world 128gb of ram and 64bits in 1970, we would have just maxed it out by 1972.
- bloomingkales 2y ago
  An undergrad using the hottest tech right of the bat? Cooked. What if I tell you there is an undergrad that just flunked a class and is depressed and cries about it? Considers changing their major? This is pre-AI. We have a chance that undergrads will never feel that way again. Not intimidated by anything.
  - TZubiri 2y ago
    There's a misconception that passing is worth 1 and flunking is worth 0. There's shitty ways to pass and good ways to pass
    - deleted 2y ago
      [deleted]
- laidoffamazon 2y ago
  > Cooked People using this phrase should probably stop, it's become extremely tiresome as a cliche
  - jgord 2y ago
    Im guessing "cooked" means the opposite of "based" ? but I could be a Feynman radian out on those vectors in leet space.
    - laidoffamazon 2y ago
      Cooked means "you're finished, it's over, no return", it's a really definitive term which I'm opposed to by philosophy
wbakst 2y ago
it's interesting, it feels like less needing to think much bigger and more so that we're now able to accept that much bigger ideas we've been thinking about are far more feasible. that's so cool. all those grand ideas that felt so far away are right here ready to grasp and realize.
mindwok 2y ago
This article is strangely timed for me. About a year ago a company reached out to me about doing an ERP migration. I turned it away because I thought it’d just be way, way too much work. This weekend, I called my colleague and asked him to call them back and see if they’re still trying to migrate. AI definitely has changed my calculus around what I can take on.
klabb3 2y ago
As a mostly LLM-skeptic I reluctantly agree this is something AI actually does well. When approaching unfamiliar territory, LLMs (1) use simple language (improvement over academia but also much professional intentionally obfuscated literature), (2) use the right abstraction (they seem good at ”zooming out” to big picture of things, and (3) you can move both laterally between topics and ”zoom in” quickly. Another way of putting it is ”picking the brain” of an expert in order to build a rough mental model. It’s downsides, such as hallucinations and lack of reasoning (yeah) aren’t very problematic here. Once you’re familiar enough you can switch to better tools and know what to look for.
- wewewedxfgdf 2y ago
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  - the13 2y ago
    Probably all the hype and bs.
  - layer8 2y ago
    They didn’t say that they were invested in it.
  - fasbiner 2y ago
    Your framing is extrapolative, mendacious and is adding what could charitably be called your interpersonal problems to a statement which is perfectly neutral, intended as an admission against general inclination to lend credibility to the observation that follows. Someone uncharitable would say things about your cognitive abilities and character that are likely true but not useful.
  - shitloadofbooks 2y ago
    I know you’re being disparaging by using language like “bake into their identity” but everyone is “something” about “something”. I’m “indifferent” about “roller coasters” and “passionate” about “board games”. To answer the question (but I’m not OP), I’m skeptical about LLMs. “These words are often near each other” vastly exceeds my expectation at being fairly convincing that the machine “knows” something, but it’s dangerously confident when it’s hilariously incorrect. Whatever we call the next technological leap where there’s actual knowledge (not just “word statistics” I’ll be less skeptical about.
simonw 2y ago
I wrote something similar about this effect almost two years ago: https://simonwillison.net/2023/Mar/27/ai-enhanced-development/ https://simonwillison.net/2023/Mar/27/ai-enhanced-developmen... "AI-enhanced development makes me more ambitious with my projects" With an extra 23 months of experience under my belt since then I'm comfortable to say that the effect has stayed steady for me over time, and even increased a bit.
- deleted 2y ago
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- shmoogy 2y ago
  100% agree with this, sometimes I feel I'm becoming too reliant on it - but I step back and see how much more ambitious of projects I take on, and finish quickly still, due to it.
  - hombre_fatal 2y ago
    Claude 3.7 basically one-shot a multiplayer game's server-authority rollback netcode with client-side prediction and interpolation. I spent months of my life in my 20s trying to build a non-janky implementation of that and failed which was really demoralizing. Over the last couple weekends I got farther than I was able to get in weeks or months. And when I get stumped, I have the confidence of being able to rubber-duck my way through it with an LLM if it can't outright fix it itself. Though I also often wonder how much time I have left professionally in software. I try not to think about that. :D
    - xandrius 2y ago
      You know the 80/20 "rule"? Well, that last 20% is what I believe will keep us around. AI is going to be a great multiplier but if the base is 0, you can multiply it by whatever you want. I feel ChatGPT-like products are like outsourcing to cheaper countries, it might work for some but for anyone else, now they have to hire more expensive people to fix/redo the work done by the cheaper labor. This seems to be exactly the same but using AI.
bloomingkales 2y ago
I definitely felt this. I thought "If I have to redo this in Flutter or in Swift, I can". I don't know either, so have to move with some caution (but it's all very exciting).
- jgord 2y ago
  At first glance, it seems like _porting_ code to another language / api .. is probably a good sweet spot for these code LLMs .. .. and even automating the testing to check results match, coming up with edge cases etc. ... and if thats true, then they could be useful for _optimizing_ by porting to other apis / algos, checking same-ness of behavior, then comparing performance. The whole "vibe coding" doesn't grab me - as I feel the bottleneck is with my creativity and understanding rather than generating viable code - using a productive expressive language like javascript or lisp and working on a small code base helps that. eg. I would like to be able to take an algo and port it to run on GPU for example... without having to ingest much arcane api quirks. JAX looks like a nice target, but Ive held off for now.
  - nop_slide 2y ago
    > At first glance, it seems like _porting_ code to another language / api .. is probably a good sweet spot for these code LLMs .. I recently ported skatevideosite.com from svelte/python to ruby on rails. I leaned on AI heavily to translate the svelte files to ERB templates and it did a wonderful job. My experiene generally with these systems is that they are good with handling things you _give_ it, but less so when coming up with stuff from scratch. For example I've tried to use it to build out additional features and the results are subpar. Agree, yeah "vibe coding" is super cringe haha
forum-soon-yuck 2y ago
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haswell 2y ago
I recently discovered that some of the Raspberry Pi models support the Linux Kernel's "Gadget Mode". This allows you to configure the Pi to appear as some type of device when plugged into a USB port, i.e. a Mass Storage/USB stick, Network Card, etc. Very nifty for turning a Pi Zero into various kinds of utilities. When I realized this was possible, I wanted to set up a project that would allow me to use the Pi as a bridge from my document scanner (has the ability to scan to a USB port) to a SMB share on my network that acts as the ingest point to a Paperless-NGX instance. Scanner -> USB "drive" > Some of my code running on the Pi > The SMB Share > Paperless. I described my scenario in a reasonable degree of detail to Claude and asked it to write the code to glue all of this together. What it produced didn't work, but was close enough that I only needed to tweak a few things. While none of this was particularly complex, it's a bit obscure, and would have easily taken a few days of tinkering the way I have for most of my life. Instead it took a few hours, and I finished a project. I, too, have started to think differently about the projects I take on. Projects that were previously relegated to "I should do that some day when I actually have time to dive deeper" now feel a lot more realistic. What will truly change the game for me is when it's reasonable to run GPT-4o level models locally.
- liotier 2y ago
  Please, I would be delighted if you published that code... Just yesterday I was thinking that a two-faced Samba share/USB Mass Storage dongle Pi would save me a lot of shuttling audio samples between my desktop and my Akai MPC.
  - haswell 2y ago
    I've been thinking about writing up a blog post about it. Might have to do a Show HN when time allows. This guide was a huge help: https://github.com/thagrol/Guides/blob/main/mass-storage-gadget.pdf https://github.com/thagrol/Guides/blob/main/mass-storage-gad...
    - thierrydamiba 2y ago
      Please do-I think this is a great example of how AI can be helpful. We see so many stories about how terrible AI coding is. We need more practical stories of how it can help.
CosmicShadow 2y ago
The exciting thing about AI is it let's you go back to any project or idea you've ever had and they are now possibly doable, even if they seemed impossible or too much work back then. Some of the key pieces missing have become trivial, and even if you don't know how to do something AI will help you figure it out or just let you come up with a solution that may seem dirty, but actually works, whereas before it was impossible without expert systems and grinding out so much code. It's opened so many doors. It's hard to remember ideas that you have written off before, there are so many blind spots that are now opportunities.
- wruza 2y ago
  It doesn’t do that for things rarely done before though. And it’s poisoned with opinions from the internet. E.g. you can convince it that we have to remove bullshit layers from programming and make it straightforward. It will even print a few pages of vague bullet points about it, if not yet. But when you ask it to code, it will dump a react form. I’m not trying to invalidate experiences itt, cause I have a similar one. But it feels futile as we are stuck with our pre-AI bloated and convoluted ways of doing things^W^W making lots of money and securing jobs by writing crap nobody understands why, and there’s no way to undo this or to teach AI to generalize. I think this novelty is just blindness to how bad things are in the areas you know little about. For example, you may think it solves the job when you ask it to create a button and a route. And it does. But the job wasn’t to create a route, load and validate data and render it on screen in a few pages and files. The job was to take a query and to have it on screen in a couple of lines. Yes it helps writing pages of our nonsense, but it’s still nonsense. It works, but feels like we have fooled ourselves twice now. It also feels like people will soon create AI playbooks for structuring and layering their output, cause ability to code review it will deteriorate in just a few years with less seniors and much more barely-coders who get into it now.
  - jboggan 2y ago
    > And it’s poisoned with opinions from the internet. This is the scary part. What current AI's are very effectively doing is surfacing the best solution (from a pre-existing blog/SO answer) that I might have been able to Google 10 years ago when search was "better" and there was less SEO slop on the internet - and pre-extract the relevant code for me (which is no minor thing). But I repeatedly have been in situations where I ask for a feature and it brings in a new library and a bunch of extra code and only 2 weeks later as I get more familiar with that library do I realize that the "extra" code I didn't understand at first is part of a Hello World blog post on that framework and I suddenly understand that I have enabled interfaces and features on my business app that were meant for a toy example.
saltcod 2y ago
Found the same thing. I was toying with a Discord bot a few weeks ago that involved setting up and running a node server, deployed to Fly via docker. A bunch of stuff a bit out of my wheelhouse. All of it turned out to be totally straightforward with LLM assistance. Thinking bigger is a practice to hone.
- autocole 2y ago
  Can you describe how you used LLMs for deployment? I'm actually doing this exact thing but I'm feeling annoyed by DevOps and codebase setup work. I wonder if I'm just being too particular about which tools I'm using rather than just going with the flow
101008 2y ago
> I am now at a real impasse, towards the end of my career and knowing I could happily start it all again with a new insight and much bigger visions for what I could take on. It feels like wining the lottery two weeks before you die I envy this optimistic. I am not the opposite (im a sr engineer with more than 15 years of experience), but I am scared about my future. I invested too much time in learning concepts, theory, getting a Master degree, and in a few years all of my knowledge can be useless in the market.
- boznz 2y ago
  IT is never static. I have had to take several forks in my career with languages and technologies often leading to dead-ends and re-training. It is amazing how much you learn doing one thing directly translates to another, it can often lead to you not having a specific/narrow mindset too. Having an LLM next to you means there is never a stupid question, I ask the AI the same stupid questions repeatedly until I get it, that is not really possible with a smart human, even if they have the patience, you are often afraid to look dumb in their eyes.
  - 101008 2y ago
    I'm worried about being replaced by LLM. If it keeps evolving to the point where a CTO can ask LLM to do something and deploy it, why he would pay for a team of engineers? Forking to different technologies and languages is one thing (I've been there, I started with PHP and I haven't touch it for almost a decade now), but being replaced by a new tech is something different. I don't see how I could pivot to still be useful.
    - wruza 2y ago
      I see it more as “if an LLM can do that, why would I need an employer?” This coin has two sides. If a CTO can live without you, you can live without an expensive buffer between you and your clients. He’s now just a guy like you, and adds little value compared to everyone else.
      - 2y ago
lordnacho 2y ago
This is much like other advances in computing. Being able to write code that compiled into assembly, instead of directly writing assembly, meant you could do more. Which soon meant you had to do more, because now everyone was expecting it. The internet meant you could take advantage of open source to build more complex software. Now, you have to. Cloud meant you could orchestrate complicated apps. Now you can't not know how it works. LLMs will be the same. At the moment people are still mostly playing with it, but pretty soon it will be "hey why are you writing our REST API consumer by hand? LLM can do that for you!" And they won't be wrong, if you can get the lower level components of a system done easily by LLM, you need to be looking at a higher level.
- aithrowawaycomm 2y ago
  Even the example in the post seemed closely related to other advances in consumer-level computing: I re-created this system using an RPi5 compute module and a $20 camera sensor plugged into it. Within two hours I wrote my first machine learning [application], using the AI to assist me and got the camera on a RPi board to read levels of wine in wine bottles on my test rig. The original project took me six weeks solid! Undoubtedly this would have taken longer without AI. But I imagine the Raspberry Pi + camera was easier to set up out-of-the-box than whatever they used 14 years ago, and it's definitely easier to set up a paint-by-numbers ML system in Python.
- 8373746439 2y ago
  > LLMs will be the same. At the moment people are still mostly playing with it, but pretty soon it will be "hey why are you writing our REST API consumer by hand? LLM can do that for you!" Not everyone wants to be a "prompt engineer", or let their skills rust and be replaced with a dependency on a proprietary service. Not to mention the potentially detrimental cognitive effects of relegating all your thinking to LLMs in the long term.
  - crent 2y ago
    I agree that not everyone wants to be. I think OPs point though is the market will make “not being a prompt engineer” a niche like being a COBOL programmer in 2025. I’m not sure I entirely agree but I do think the paradigm is shifting enough that I feel bad for my coworkers who intentionally don’t use AI. I can see a new skill developing in myself that augments my ability to perform and they are still taking ages doing the same old thing. Frankly, now is the sweet spot because the expectation hasn’t raised enough to meet the output so you can either squeeze time to tackle that tech debt or find time to kick up your feet until the industry catches up.
tqwhite 2y ago
Using AI has changed everything for me and made my ambition swell. I despise looking up the details of frameworks and api’s, transmitting a change of strategy through a system, typing the usual stupid loops and processes that are the foundation of all programs. Hell, the amount of time I save on typing errors is worth it. I have plans for many things I didn’t have the energy for in the past.
- CokeFaultSoyuz 2y ago
  [flagged]
Xen9 2y ago
What psychedelic/mind-altering/weird coaching prompts do you use? I have separate system prompts for taboo-teaching, excessive-pedanticism, excessive-toxicity, excessive-praise, et cetera. My general rules is anything & everything humans would never ever do, but that would somehow allow me to explore altered states of consciousness, ways of thinking, my mind, the world, better. Something to make me smarter from the experience of the chat.
- CokeFaultSoyuz 2y ago
  [flagged]
TooTony 2y ago
I use Cursor to write Python programs to solve tasks in my daily work that need to be completed with programming. It's very convenient, and I no longer need to ask the company's programmers for help. Large language models are truly revolutionary productivity tools.
curious_cat_163 2y ago
Yes -- LLMs can write a lot of code and after some reviewing it can also go to prod -- but I have not nearly enough applications of LLMs on the post-prod phase; like dealing with evolution in requirements, ensuring security as zero days get discovered, etc. Would love to hear folks' experience around "managing" all this new code.
SamPatt 2y ago
For me, it isn't just about complexity, but about customization. I can have the LLMs build me custom bash scripts or make me my own Obsidian plugins. They're all little cogs in my own workflow. None of these individual components are complex, but putting all of them together would have taken me ages previously. Now I can just drop all of them into the conversation and ask it for a new script that works with them to do X. Here's an example where I built a custom screenshot hosting tool for my blog: https://sampatt.com/blog/2025-02-11-jsDelivr https://sampatt.com/blog/2025-02-11-jsDelivr
hn_throwaway_99 2y ago
I feel like I'm straddling the fence a bit on this topic. When it comes to some personal projects, I've written a slew of them since AI coding tools got quite good. I'm primarily a backend developer, and while I've done quite a bit of frontend dev, I'm relatively slow at it, and I'm especially slow as CSS. AI has completely removed this bottleneck for me. Often times if I'm coding up a frontend, I'll literally just say "Ok, now make it pretty with a modern-looking UI", and it does a decent job, and anything I need to fix is an understandable change that I can do quickly. So now I'll whip up nice little "personal tool" apps in literally like 30 mins, where in the past I would have spent 30 mins just trying to figure out some CSS voodoo about why it's so hard to get a button centered. But in my job, where I also use AI relatively frequently, it is great for helping to learn new things, but when I've tried to use it for things like large scale, repo-wide refactorings it's usually been a bit of a PITA - reviewing all of the code and fixing it's somewhat subtle mistakes often feels like it's slower than doing it myself. It that sense, I think it's reasonable to consider AI like a competent junior developer (albeit at "junior developer" level across every technology ever invented). I can give a junior developer a "targeted" task, and they usually do a good job, even if I have to fix something here or there. But when I give them larger tasks that cross many components or areas of concern, that's often where they struggle mightily as well.
tomjuggler 2y ago
I have been using AI coding tools since the first GitHub co-pilot. One thing has not changed: garbage in = garbage out. If you know what you are doing the tools can improve output a lot - but while you might get on for a little bit without that experience guiding you, eventually AI will code you into a corner if it's not guided right. I saw mention of kids learning to code with AI and I have to say, that's great, but only if they are just doing it for fun. Anyone who is thinking of a career in generating code for a living should first and foremost focus on understanding the principles. The best way to do that is still writing your own programs by hand.
- _diyar 2y ago
  The AUC of learning to program remains the same before and after AI, both for hobbyist and professionals. What changes is the slope of the on-ramp – AI makes it easier to get started, achieve first wins and learn the table-stakes for your field.
nottorp 2y ago
> I have noticed that I am no longer scared that a project will be too big or too complex for me, That's still a valid worry. At best, you can do larger projects on your own than before. > or that a project will use a technology or programming language I don’t know. Was that ever a worry? I've always considered it an opportunity for self improvement.
deleted 2y ago
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xrd 2y ago
Where are the LLM leaderboards for software estimation accuracy? I have been using Claude Code and Aider and I do think they provide incredibly exciting potential. I can spin up new projects with mind boggling results. And, I can start projects in domains where I previously had almost no experience. It is truly exciting. AND... The thing I worry most about is that now non-technical managers can go into Claude and say "build me XYZ!" and the AI will build a passable first version. But, any experienced software person knows that the true cost of software is in the maintenance. That's 90% of the cost. Reducing that starting point to zero cost only reduces the total cost of software by 10%, but people are making it seem like you no longer need a software engineer that understands complex systems. Or, maybe that is just my fears vocalized. I have seen LLMs dig into old and complex codebases and fix things that I was not expecting them to handle. I tend to write a lot of tests in my code, so I can see that the tests pass and the code compiles. The barbarians have come over the walls, truly. But, IMHO, there is still a space where we cannot ask any of the AI coding tools to review a spec and say "Will you get this done in 2 months?" I don't think we are there, yet. I don't see that the context window is big enough to jam entire codebases inside it, and I don't yet see that these tools can anticipate a project growing into hundreds of files and managing the interdepedencies between them. They are good at writing tests, and I am impressed by that, so there is a pathway. I'm excited to understand more about how aider creates a map of the repository and effectively compresses the information in ways similar to how I keep track of high level ideas. But, it still feels very early and there are gaps. And, I think we are in for a rude awakening when people start thinking this pushes the cost and complexity of software projects to zero. I love the potential for AI coding, but it feels like it is dangerously marketing and sales driven right now and full of hype.
- someothherguyy 2y ago
  > I can spin up new projects with mind boggling results Boggle a skeptical mind
  - xrd 2y ago
    Meaning, give you an example? This morning I created a new project. I provided a postgres database URL to a remote service (with a non-standard connection string, includes a parameter "?sslmode=require"). Then, I said: * "Write me a fastapi project to connect to a postgres database using a database url." * "Retrieve the schema from the remote database." It used psql to connect, retrieves the schema. That was unexpected, it figured out not only a coding task, but an external tool to connect to a database and did it without anything more than me providing the DATABASE_URL. Actually, I should say, I told it to look inside the .env file, and it did that. I had that URL wrong initially, so I told it to reload once I corrected it. It never got confused by my disorganization. * It automatically added sqlalchemy models and uses pydantic once it figured out the schema. * "Create a webpage that lets me review one table." * "Rewrite to use tailwindcss." It adds the correct tailwindcss CDN imports. * It automatically adds a modal dialog when I click on one of the records. * It categorized fields in the database into groupings inside the modal, groupings that do indeed make sense. I know the devil is in the details, or in the future. I'm sure there are gaping security holes. But, this saved me a lot of time and it works.
CaffeineLD50 2y ago
I had a minor desire to make a feature that had a slightly higher effort than reward, so although I knew I could struggle it out I didn't bother. After years of this I decided to give an AI a shot at the code. It produced something plausible looking and I was excited. Was it that easy? The code didn't work. But the approach made me more motivated to look into it and I found a solution. So although the AI gave me crap code it still inspired the answer, so I'm calling that a win. Simply making things feel approachable can be enough.
- radlad 2y ago
  I had a similar experience but found that with a little prodding, I was even able to get it to finish the job. Then it was a little messy, so I asked it to refactor it. Of course, not everything lends itself to this: often I already know exactly the code I want and it's easier to just type it than corral the AI.
- headcanon 2y ago
  Agreed, its always nicer for me to have something to work with, even if by the end of it its entirely rewritten. It helps to have it generate code sometimes to just explore ideas and refine the prompt. If its obviously wrong, thats ok, sometimes I needed to see the wrong answer to get to the right one faster. If its not obviously wrong, then its a good enough starting point we can iterate to the answer.
  - __xor_eax_eax 2y ago
    I love throwing questions at it where previously it would have been daunting because you don't even know the right questions to ask, and the amount of research you'd need to do to even ask the proper question is super high. Its great for ideating in that way. It does produce some legendary BS though.
- nineplay 2y ago
  One of my more effective uses of AI is for rubber duck debugging. I tell it what I want the code to do, iterate over what it comes back with, adjust the code ( 'now rewrite foo() so 'bar' is is passed in'). What comes back isn't necessarily perfect and I don't blindly copy and paste but that isn't the point. At the end I've worked out what I want to do and some of the tedious boiler-plate code is taken care of.
nbzso 2y ago
Lost me there: that a project will use a technology or programming language I don’t know.:) Good luck.
smhinsey 2y ago
It seems like the emphasis on getting results in one shot reduces the maximum potential quality of the output as compared to a more incremental approach. For example, create an initial prompt to generate a structured description of the features in the program you've described. You can then iterate on this and follow up with a prompt that generates a structured description of a system architecture based on the feature description, and iterate on that. You could build up other informational layers as well, before aggregating all that structural data into the generation of the actual code. This can feed into the generation of tests as well. If you look at things like LLM party for comfyui, it's the same basic concept.
noelwelsh 2y ago
We really need to get nuanced about the discussion around LLMs in programming. My experience is that LLMs work great for producing glue code. Join together a bunch of well documented APIs? LLMs will make enough progress that I can finish it myself. Produce a pile of HTML and CSS for a nondescript design? I'll get at least a mostly working result that I can easily fix up. But try to, say, design a cross platform GUI library and the results are underwhelming. LLMs know a heck of a lot of stuff, but they are not very good at working with concepts.
- elliotbnvl 2y ago
  The missing piece in your view here is that eventually nearly all code is or eventually becomes gibberish glue code, or it stops being used. LLMs just speed up the cycle.
aantix 2y ago
Humans are inherently greedy. Once we get a feel for what the AI can and cannot do, bigger bets will occur. Currently, companies seem tight - team counts are held low, and hiring is frozen. Very much a position of "let's see how much AI efficiency gains us". But eventually, the money sitting on the sidelines will look attractive again - attractive for taking bigger, more ambitious bets. More hiring has to take place.
amunozo 2y ago
This is the most important change AI assisted code for me: it's making me confident I can tackle any problem.
w10-1 2y ago
Think bigger in 3 distinct ways: 1. Lower learning curve, for new or revived skills (weaving - gather and summarize) 2. Lower incremental cost: almost always faster at choosing the next step (scouting) 3. Faster time-to-maturity: when building test suites, faster both at first-pass coverage and at gap-filling (zoo-keeping) But the huge, gaping pitfall -- now coming down the tracks even faster -- is the same as without AI: once you build a complex system, committing to its invariants, you quickly find it difficult to change in the direction you want, because each choice triggers a tangle of incommensurable choices. Sometimes heroic re-factorings (beyond AI now) can extend life a bit, but usually the only people who can avoid abrupt stasis are those with deep experience and the insight into how to change things (incrementally). I'd guess with AI such pitfalls become more common and more difficult to escape. So: yes, think bigger for projects with relatively definitive and complete requirements, but take care with foundational code you expect to grow.
g8oz 2y ago
Claude gave me the confidence to setup a router using the relatively obscure VyOS network stack. It was a lot of back and forth. The syntax has changed quite a bit between versions and Claude kept giving me out of date code. I would reply with the error message and snippets of the current documentation and it would try again. Things eventually worked. Perhaps it was a bit of a "stone soup" situation, but I would not have attempted the project without the assistance of an LLM.
winterbloom 2y ago
Bad blog post You don't want to use AI for complex things that you might not fully understand. These are the cases where you'll miss the hallucinations and get fucked
- tonyoconnell 2y ago
  You just don't understand that AI becoming smarter than humans
hackburg 2y ago
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305 points by boznz 2y ago

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Insufficient Storage The method could not be performed on the resource because the server is unable to store the representation needed to successfully complete the request. There is insufficient free space left in your storage allocation. Additionally, a 507 Insufficient Storage error was encountered while trying to use an ErrorDocument to handle the request.

WesolyKubeczek 2y ago
Accidentally thought too big
- jm4rc05 2y ago
  https://imgs.xkcd.com/comics/is_it_worth_the_time.png https://imgs.xkcd.com/comics/is_it_worth_the_time.png
boznz 2y ago
bugger! More than two visitors to my web site and it falls apart, I might fork out the $10 for the better CPU and more memory option before I post something in future.

antonkar 2y ago

Agree, let’s build direct democratic simulated multiverse. Or at least make a digital back up of Earth. Or at least represent an LLM as a green field with objects, where humans are the only agents: you stand near a monkey, see chewing mouth nearby, go there (your prompt now is “monkey chews”), close by you see an arrow pointing at a banana, father away an arrow points at an apple, very far away at the horizon an arrow points at a tire (monkeys rarely chew tires). So things close by are more likely tokens, things far away are less likely, you see all of them at once (maybe you’re on top of a hill to see farther). This way we can make a form of static place AI, where humans are the only agents

boznz 2y ago
A simulation in a simulation... Neat!
- antonkar 2y ago
  Thanks, I wrote extensively about it) If interested, you can find a link in my profile or ask anything here
  - boznz 2y ago
    Thanks I will take my time reading it, you certainly could never be criticized for thinking too small.

deleted 2y ago

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TZubiri 2y ago

Probably right at the end of your career is where this tool would be the most useful An undergrad using the hottest tech right of the bat? Cooked. It's like giving the world 128gb of ram and 64bits in 1970, we would have just maxed it out by 1972.

bloomingkales 2y ago
An undergrad using the hottest tech right of the bat? Cooked. What if I tell you there is an undergrad that just flunked a class and is depressed and cries about it? Considers changing their major? This is pre-AI. We have a chance that undergrads will never feel that way again. Not intimidated by anything.
- TZubiri 2y ago
  There's a misconception that passing is worth 1 and flunking is worth 0. There's shitty ways to pass and good ways to pass
  - deleted 2y ago
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laidoffamazon 2y ago
> Cooked People using this phrase should probably stop, it's become extremely tiresome as a cliche
- jgord 2y ago
  Im guessing "cooked" means the opposite of "based" ? but I could be a Feynman radian out on those vectors in leet space.
  - laidoffamazon 2y ago
    Cooked means "you're finished, it's over, no return", it's a really definitive term which I'm opposed to by philosophy

wbakst 2y ago

it's interesting, it feels like less needing to think much bigger and more so that we're now able to accept that much bigger ideas we've been thinking about are far more feasible. that's so cool. all those grand ideas that felt so far away are right here ready to grasp and realize.

mindwok 2y ago

This article is strangely timed for me. About a year ago a company reached out to me about doing an ERP migration. I turned it away because I thought it’d just be way, way too much work. This weekend, I called my colleague and asked him to call them back and see if they’re still trying to migrate. AI definitely has changed my calculus around what I can take on.

klabb3 2y ago

As a mostly LLM-skeptic I reluctantly agree this is something AI actually does well. When approaching unfamiliar territory, LLMs (1) use simple language (improvement over academia but also much professional intentionally obfuscated literature), (2) use the right abstraction (they seem good at ”zooming out” to big picture of things, and (3) you can move both laterally between topics and ”zoom in” quickly. Another way of putting it is ”picking the brain” of an expert in order to build a rough mental model. It’s downsides, such as hallucinations and lack of reasoning (yeah) aren’t very problematic here. Once you’re familiar enough you can switch to better tools and know what to look for.

wewewedxfgdf 2y ago
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- the13 2y ago
  Probably all the hype and bs.
- layer8 2y ago
  They didn’t say that they were invested in it.
- fasbiner 2y ago
  Your framing is extrapolative, mendacious and is adding what could charitably be called your interpersonal problems to a statement which is perfectly neutral, intended as an admission against general inclination to lend credibility to the observation that follows. Someone uncharitable would say things about your cognitive abilities and character that are likely true but not useful.
- shitloadofbooks 2y ago
  I know you’re being disparaging by using language like “bake into their identity” but everyone is “something” about “something”. I’m “indifferent” about “roller coasters” and “passionate” about “board games”. To answer the question (but I’m not OP), I’m skeptical about LLMs. “These words are often near each other” vastly exceeds my expectation at being fairly convincing that the machine “knows” something, but it’s dangerously confident when it’s hilariously incorrect. Whatever we call the next technological leap where there’s actual knowledge (not just “word statistics” I’ll be less skeptical about.

simonw 2y ago

I wrote something similar about this effect almost two years ago: https://simonwillison.net/2023/Mar/27/ai-enhanced-development/ https://simonwillison.net/2023/Mar/27/ai-enhanced-developmen... "AI-enhanced development makes me more ambitious with my projects" With an extra 23 months of experience under my belt since then I'm comfortable to say that the effect has stayed steady for me over time, and even increased a bit.

deleted 2y ago
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shmoogy 2y ago
100% agree with this, sometimes I feel I'm becoming too reliant on it - but I step back and see how much more ambitious of projects I take on, and finish quickly still, due to it.
- hombre_fatal 2y ago
  Claude 3.7 basically one-shot a multiplayer game's server-authority rollback netcode with client-side prediction and interpolation. I spent months of my life in my 20s trying to build a non-janky implementation of that and failed which was really demoralizing. Over the last couple weekends I got farther than I was able to get in weeks or months. And when I get stumped, I have the confidence of being able to rubber-duck my way through it with an LLM if it can't outright fix it itself. Though I also often wonder how much time I have left professionally in software. I try not to think about that. :D
  - xandrius 2y ago
    You know the 80/20 "rule"? Well, that last 20% is what I believe will keep us around. AI is going to be a great multiplier but if the base is 0, you can multiply it by whatever you want. I feel ChatGPT-like products are like outsourcing to cheaper countries, it might work for some but for anyone else, now they have to hire more expensive people to fix/redo the work done by the cheaper labor. This seems to be exactly the same but using AI.

bloomingkales 2y ago

I definitely felt this. I thought "If I have to redo this in Flutter or in Swift, I can". I don't know either, so have to move with some caution (but it's all very exciting).

jgord 2y ago
At first glance, it seems like _porting_ code to another language / api .. is probably a good sweet spot for these code LLMs .. .. and even automating the testing to check results match, coming up with edge cases etc. ... and if thats true, then they could be useful for _optimizing_ by porting to other apis / algos, checking same-ness of behavior, then comparing performance. The whole "vibe coding" doesn't grab me - as I feel the bottleneck is with my creativity and understanding rather than generating viable code - using a productive expressive language like javascript or lisp and working on a small code base helps that. eg. I would like to be able to take an algo and port it to run on GPU for example... without having to ingest much arcane api quirks. JAX looks like a nice target, but Ive held off for now.
- nop_slide 2y ago
  > At first glance, it seems like _porting_ code to another language / api .. is probably a good sweet spot for these code LLMs .. I recently ported skatevideosite.com from svelte/python to ruby on rails. I leaned on AI heavily to translate the svelte files to ERB templates and it did a wonderful job. My experiene generally with these systems is that they are good with handling things you _give_ it, but less so when coming up with stuff from scratch. For example I've tried to use it to build out additional features and the results are subpar. Agree, yeah "vibe coding" is super cringe haha

forum-soon-yuck 2y ago

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haswell 2y ago

I recently discovered that some of the Raspberry Pi models support the Linux Kernel's "Gadget Mode". This allows you to configure the Pi to appear as some type of device when plugged into a USB port, i.e. a Mass Storage/USB stick, Network Card, etc. Very nifty for turning a Pi Zero into various kinds of utilities. When I realized this was possible, I wanted to set up a project that would allow me to use the Pi as a bridge from my document scanner (has the ability to scan to a USB port) to a SMB share on my network that acts as the ingest point to a Paperless-NGX instance. Scanner -> USB "drive" > Some of my code running on the Pi > The SMB Share > Paperless. I described my scenario in a reasonable degree of detail to Claude and asked it to write the code to glue all of this together. What it produced didn't work, but was close enough that I only needed to tweak a few things. While none of this was particularly complex, it's a bit obscure, and would have easily taken a few days of tinkering the way I have for most of my life. Instead it took a few hours, and I finished a project. I, too, have started to think differently about the projects I take on. Projects that were previously relegated to "I should do that some day when I actually have time to dive deeper" now feel a lot more realistic. What will truly change the game for me is when it's reasonable to run GPT-4o level models locally.

liotier 2y ago
Please, I would be delighted if you published that code... Just yesterday I was thinking that a two-faced Samba share/USB Mass Storage dongle Pi would save me a lot of shuttling audio samples between my desktop and my Akai MPC.
- haswell 2y ago
  I've been thinking about writing up a blog post about it. Might have to do a Show HN when time allows. This guide was a huge help: https://github.com/thagrol/Guides/blob/main/mass-storage-gadget.pdf https://github.com/thagrol/Guides/blob/main/mass-storage-gad...
  - thierrydamiba 2y ago
    Please do-I think this is a great example of how AI can be helpful. We see so many stories about how terrible AI coding is. We need more practical stories of how it can help.

CosmicShadow 2y ago

The exciting thing about AI is it let's you go back to any project or idea you've ever had and they are now possibly doable, even if they seemed impossible or too much work back then. Some of the key pieces missing have become trivial, and even if you don't know how to do something AI will help you figure it out or just let you come up with a solution that may seem dirty, but actually works, whereas before it was impossible without expert systems and grinding out so much code. It's opened so many doors. It's hard to remember ideas that you have written off before, there are so many blind spots that are now opportunities.

wruza 2y ago
It doesn’t do that for things rarely done before though. And it’s poisoned with opinions from the internet. E.g. you can convince it that we have to remove bullshit layers from programming and make it straightforward. It will even print a few pages of vague bullet points about it, if not yet. But when you ask it to code, it will dump a react form. I’m not trying to invalidate experiences itt, cause I have a similar one. But it feels futile as we are stuck with our pre-AI bloated and convoluted ways of doing things^W^W making lots of money and securing jobs by writing crap nobody understands why, and there’s no way to undo this or to teach AI to generalize. I think this novelty is just blindness to how bad things are in the areas you know little about. For example, you may think it solves the job when you ask it to create a button and a route. And it does. But the job wasn’t to create a route, load and validate data and render it on screen in a few pages and files. The job was to take a query and to have it on screen in a couple of lines. Yes it helps writing pages of our nonsense, but it’s still nonsense. It works, but feels like we have fooled ourselves twice now. It also feels like people will soon create AI playbooks for structuring and layering their output, cause ability to code review it will deteriorate in just a few years with less seniors and much more barely-coders who get into it now.
- jboggan 2y ago
  > And it’s poisoned with opinions from the internet. This is the scary part. What current AI's are very effectively doing is surfacing the best solution (from a pre-existing blog/SO answer) that I might have been able to Google 10 years ago when search was "better" and there was less SEO slop on the internet - and pre-extract the relevant code for me (which is no minor thing). But I repeatedly have been in situations where I ask for a feature and it brings in a new library and a bunch of extra code and only 2 weeks later as I get more familiar with that library do I realize that the "extra" code I didn't understand at first is part of a Hello World blog post on that framework and I suddenly understand that I have enabled interfaces and features on my business app that were meant for a toy example.

saltcod 2y ago

Found the same thing. I was toying with a Discord bot a few weeks ago that involved setting up and running a node server, deployed to Fly via docker. A bunch of stuff a bit out of my wheelhouse. All of it turned out to be totally straightforward with LLM assistance. Thinking bigger is a practice to hone.

autocole 2y ago
Can you describe how you used LLMs for deployment? I'm actually doing this exact thing but I'm feeling annoyed by DevOps and codebase setup work. I wonder if I'm just being too particular about which tools I'm using rather than just going with the flow

101008 2y ago

> I am now at a real impasse, towards the end of my career and knowing I could happily start it all again with a new insight and much bigger visions for what I could take on. It feels like wining the lottery two weeks before you die I envy this optimistic. I am not the opposite (im a sr engineer with more than 15 years of experience), but I am scared about my future. I invested too much time in learning concepts, theory, getting a Master degree, and in a few years all of my knowledge can be useless in the market.

boznz 2y ago
IT is never static. I have had to take several forks in my career with languages and technologies often leading to dead-ends and re-training. It is amazing how much you learn doing one thing directly translates to another, it can often lead to you not having a specific/narrow mindset too. Having an LLM next to you means there is never a stupid question, I ask the AI the same stupid questions repeatedly until I get it, that is not really possible with a smart human, even if they have the patience, you are often afraid to look dumb in their eyes.
- 101008 2y ago
  I'm worried about being replaced by LLM. If it keeps evolving to the point where a CTO can ask LLM to do something and deploy it, why he would pay for a team of engineers? Forking to different technologies and languages is one thing (I've been there, I started with PHP and I haven't touch it for almost a decade now), but being replaced by a new tech is something different. I don't see how I could pivot to still be useful.
  - wruza 2y ago
    I see it more as “if an LLM can do that, why would I need an employer?” This coin has two sides. If a CTO can live without you, you can live without an expensive buffer between you and your clients. He’s now just a guy like you, and adds little value compared to everyone else.
    - 2y ago

lordnacho 2y ago

This is much like other advances in computing. Being able to write code that compiled into assembly, instead of directly writing assembly, meant you could do more. Which soon meant you had to do more, because now everyone was expecting it. The internet meant you could take advantage of open source to build more complex software. Now, you have to. Cloud meant you could orchestrate complicated apps. Now you can't not know how it works. LLMs will be the same. At the moment people are still mostly playing with it, but pretty soon it will be "hey why are you writing our REST API consumer by hand? LLM can do that for you!" And they won't be wrong, if you can get the lower level components of a system done easily by LLM, you need to be looking at a higher level.

aithrowawaycomm 2y ago
Even the example in the post seemed closely related to other advances in consumer-level computing: I re-created this system using an RPi5 compute module and a $20 camera sensor plugged into it. Within two hours I wrote my first machine learning [application], using the AI to assist me and got the camera on a RPi board to read levels of wine in wine bottles on my test rig. The original project took me six weeks solid! Undoubtedly this would have taken longer without AI. But I imagine the Raspberry Pi + camera was easier to set up out-of-the-box than whatever they used 14 years ago, and it's definitely easier to set up a paint-by-numbers ML system in Python.
8373746439 2y ago
> LLMs will be the same. At the moment people are still mostly playing with it, but pretty soon it will be "hey why are you writing our REST API consumer by hand? LLM can do that for you!" Not everyone wants to be a "prompt engineer", or let their skills rust and be replaced with a dependency on a proprietary service. Not to mention the potentially detrimental cognitive effects of relegating all your thinking to LLMs in the long term.
- crent 2y ago
  I agree that not everyone wants to be. I think OPs point though is the market will make “not being a prompt engineer” a niche like being a COBOL programmer in 2025. I’m not sure I entirely agree but I do think the paradigm is shifting enough that I feel bad for my coworkers who intentionally don’t use AI. I can see a new skill developing in myself that augments my ability to perform and they are still taking ages doing the same old thing. Frankly, now is the sweet spot because the expectation hasn’t raised enough to meet the output so you can either squeeze time to tackle that tech debt or find time to kick up your feet until the industry catches up.

tqwhite 2y ago

Using AI has changed everything for me and made my ambition swell. I despise looking up the details of frameworks and api’s, transmitting a change of strategy through a system, typing the usual stupid loops and processes that are the foundation of all programs. Hell, the amount of time I save on typing errors is worth it. I have plans for many things I didn’t have the energy for in the past.

CokeFaultSoyuz 2y ago
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Xen9 2y ago

What psychedelic/mind-altering/weird coaching prompts do you use? I have separate system prompts for taboo-teaching, excessive-pedanticism, excessive-toxicity, excessive-praise, et cetera. My general rules is anything & everything humans would never ever do, but that would somehow allow me to explore altered states of consciousness, ways of thinking, my mind, the world, better. Something to make me smarter from the experience of the chat.

CokeFaultSoyuz 2y ago
[flagged]

TooTony 2y ago

I use Cursor to write Python programs to solve tasks in my daily work that need to be completed with programming. It's very convenient, and I no longer need to ask the company's programmers for help. Large language models are truly revolutionary productivity tools.

curious_cat_163 2y ago

Yes -- LLMs can write a lot of code and after some reviewing it can also go to prod -- but I have not nearly enough applications of LLMs on the post-prod phase; like dealing with evolution in requirements, ensuring security as zero days get discovered, etc. Would love to hear folks' experience around "managing" all this new code.

SamPatt 2y ago

For me, it isn't just about complexity, but about customization. I can have the LLMs build me custom bash scripts or make me my own Obsidian plugins. They're all little cogs in my own workflow. None of these individual components are complex, but putting all of them together would have taken me ages previously. Now I can just drop all of them into the conversation and ask it for a new script that works with them to do X. Here's an example where I built a custom screenshot hosting tool for my blog: https://sampatt.com/blog/2025-02-11-jsDelivr https://sampatt.com/blog/2025-02-11-jsDelivr

hn_throwaway_99 2y ago

I feel like I'm straddling the fence a bit on this topic. When it comes to some personal projects, I've written a slew of them since AI coding tools got quite good. I'm primarily a backend developer, and while I've done quite a bit of frontend dev, I'm relatively slow at it, and I'm especially slow as CSS. AI has completely removed this bottleneck for me. Often times if I'm coding up a frontend, I'll literally just say "Ok, now make it pretty with a modern-looking UI", and it does a decent job, and anything I need to fix is an understandable change that I can do quickly. So now I'll whip up nice little "personal tool" apps in literally like 30 mins, where in the past I would have spent 30 mins just trying to figure out some CSS voodoo about why it's so hard to get a button centered. But in my job, where I also use AI relatively frequently, it is great for helping to learn new things, but when I've tried to use it for things like large scale, repo-wide refactorings it's usually been a bit of a PITA - reviewing all of the code and fixing it's somewhat subtle mistakes often feels like it's slower than doing it myself. It that sense, I think it's reasonable to consider AI like a competent junior developer (albeit at "junior developer" level across every technology ever invented). I can give a junior developer a "targeted" task, and they usually do a good job, even if I have to fix something here or there. But when I give them larger tasks that cross many components or areas of concern, that's often where they struggle mightily as well.

tomjuggler 2y ago

I have been using AI coding tools since the first GitHub co-pilot. One thing has not changed: garbage in = garbage out. If you know what you are doing the tools can improve output a lot - but while you might get on for a little bit without that experience guiding you, eventually AI will code you into a corner if it's not guided right. I saw mention of kids learning to code with AI and I have to say, that's great, but only if they are just doing it for fun. Anyone who is thinking of a career in generating code for a living should first and foremost focus on understanding the principles. The best way to do that is still writing your own programs by hand.

_diyar 2y ago
The AUC of learning to program remains the same before and after AI, both for hobbyist and professionals. What changes is the slope of the on-ramp – AI makes it easier to get started, achieve first wins and learn the table-stakes for your field.

nottorp 2y ago

> I have noticed that I am no longer scared that a project will be too big or too complex for me, That's still a valid worry. At best, you can do larger projects on your own than before. > or that a project will use a technology or programming language I don’t know. Was that ever a worry? I've always considered it an opportunity for self improvement.

deleted 2y ago

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xrd 2y ago

Where are the LLM leaderboards for software estimation accuracy? I have been using Claude Code and Aider and I do think they provide incredibly exciting potential. I can spin up new projects with mind boggling results. And, I can start projects in domains where I previously had almost no experience. It is truly exciting. AND... The thing I worry most about is that now non-technical managers can go into Claude and say "build me XYZ!" and the AI will build a passable first version. But, any experienced software person knows that the true cost of software is in the maintenance. That's 90% of the cost. Reducing that starting point to zero cost only reduces the total cost of software by 10%, but people are making it seem like you no longer need a software engineer that understands complex systems. Or, maybe that is just my fears vocalized. I have seen LLMs dig into old and complex codebases and fix things that I was not expecting them to handle. I tend to write a lot of tests in my code, so I can see that the tests pass and the code compiles. The barbarians have come over the walls, truly. But, IMHO, there is still a space where we cannot ask any of the AI coding tools to review a spec and say "Will you get this done in 2 months?" I don't think we are there, yet. I don't see that the context window is big enough to jam entire codebases inside it, and I don't yet see that these tools can anticipate a project growing into hundreds of files and managing the interdepedencies between them. They are good at writing tests, and I am impressed by that, so there is a pathway. I'm excited to understand more about how aider creates a map of the repository and effectively compresses the information in ways similar to how I keep track of high level ideas. But, it still feels very early and there are gaps. And, I think we are in for a rude awakening when people start thinking this pushes the cost and complexity of software projects to zero. I love the potential for AI coding, but it feels like it is dangerously marketing and sales driven right now and full of hype.

someothherguyy 2y ago
> I can spin up new projects with mind boggling results Boggle a skeptical mind
- xrd 2y ago
  Meaning, give you an example? This morning I created a new project. I provided a postgres database URL to a remote service (with a non-standard connection string, includes a parameter "?sslmode=require"). Then, I said: * "Write me a fastapi project to connect to a postgres database using a database url." * "Retrieve the schema from the remote database." It used psql to connect, retrieves the schema. That was unexpected, it figured out not only a coding task, but an external tool to connect to a database and did it without anything more than me providing the DATABASE_URL. Actually, I should say, I told it to look inside the .env file, and it did that. I had that URL wrong initially, so I told it to reload once I corrected it. It never got confused by my disorganization. * It automatically added sqlalchemy models and uses pydantic once it figured out the schema. * "Create a webpage that lets me review one table." * "Rewrite to use tailwindcss." It adds the correct tailwindcss CDN imports. * It automatically adds a modal dialog when I click on one of the records. * It categorized fields in the database into groupings inside the modal, groupings that do indeed make sense. I know the devil is in the details, or in the future. I'm sure there are gaping security holes. But, this saved me a lot of time and it works.

CaffeineLD50 2y ago

I had a minor desire to make a feature that had a slightly higher effort than reward, so although I knew I could struggle it out I didn't bother. After years of this I decided to give an AI a shot at the code. It produced something plausible looking and I was excited. Was it that easy? The code didn't work. But the approach made me more motivated to look into it and I found a solution. So although the AI gave me crap code it still inspired the answer, so I'm calling that a win. Simply making things feel approachable can be enough.

radlad 2y ago
I had a similar experience but found that with a little prodding, I was even able to get it to finish the job. Then it was a little messy, so I asked it to refactor it. Of course, not everything lends itself to this: often I already know exactly the code I want and it's easier to just type it than corral the AI.
headcanon 2y ago
Agreed, its always nicer for me to have something to work with, even if by the end of it its entirely rewritten. It helps to have it generate code sometimes to just explore ideas and refine the prompt. If its obviously wrong, thats ok, sometimes I needed to see the wrong answer to get to the right one faster. If its not obviously wrong, then its a good enough starting point we can iterate to the answer.
- __xor_eax_eax 2y ago
  I love throwing questions at it where previously it would have been daunting because you don't even know the right questions to ask, and the amount of research you'd need to do to even ask the proper question is super high. Its great for ideating in that way. It does produce some legendary BS though.
nineplay 2y ago
One of my more effective uses of AI is for rubber duck debugging. I tell it what I want the code to do, iterate over what it comes back with, adjust the code ( 'now rewrite foo() so 'bar' is is passed in'). What comes back isn't necessarily perfect and I don't blindly copy and paste but that isn't the point. At the end I've worked out what I want to do and some of the tedious boiler-plate code is taken care of.

nbzso 2y ago

Lost me there: that a project will use a technology or programming language I don’t know.:) Good luck.

smhinsey 2y ago

It seems like the emphasis on getting results in one shot reduces the maximum potential quality of the output as compared to a more incremental approach. For example, create an initial prompt to generate a structured description of the features in the program you've described. You can then iterate on this and follow up with a prompt that generates a structured description of a system architecture based on the feature description, and iterate on that. You could build up other informational layers as well, before aggregating all that structural data into the generation of the actual code. This can feed into the generation of tests as well. If you look at things like LLM party for comfyui, it's the same basic concept.

noelwelsh 2y ago

We really need to get nuanced about the discussion around LLMs in programming. My experience is that LLMs work great for producing glue code. Join together a bunch of well documented APIs? LLMs will make enough progress that I can finish it myself. Produce a pile of HTML and CSS for a nondescript design? I'll get at least a mostly working result that I can easily fix up. But try to, say, design a cross platform GUI library and the results are underwhelming. LLMs know a heck of a lot of stuff, but they are not very good at working with concepts.

elliotbnvl 2y ago
The missing piece in your view here is that eventually nearly all code is or eventually becomes gibberish glue code, or it stops being used. LLMs just speed up the cycle.

aantix 2y ago

Humans are inherently greedy. Once we get a feel for what the AI can and cannot do, bigger bets will occur. Currently, companies seem tight - team counts are held low, and hiring is frozen. Very much a position of "let's see how much AI efficiency gains us". But eventually, the money sitting on the sidelines will look attractive again - attractive for taking bigger, more ambitious bets. More hiring has to take place.

amunozo 2y ago

This is the most important change AI assisted code for me: it's making me confident I can tackle any problem.

w10-1 2y ago

Think bigger in 3 distinct ways: 1. Lower learning curve, for new or revived skills (weaving - gather and summarize) 2. Lower incremental cost: almost always faster at choosing the next step (scouting) 3. Faster time-to-maturity: when building test suites, faster both at first-pass coverage and at gap-filling (zoo-keeping) But the huge, gaping pitfall -- now coming down the tracks even faster -- is the same as without AI: once you build a complex system, committing to its invariants, you quickly find it difficult to change in the direction you want, because each choice triggers a tangle of incommensurable choices. Sometimes heroic re-factorings (beyond AI now) can extend life a bit, but usually the only people who can avoid abrupt stasis are those with deep experience and the insight into how to change things (incrementally). I'd guess with AI such pitfalls become more common and more difficult to escape. So: yes, think bigger for projects with relatively definitive and complete requirements, but take care with foundational code you expect to grow.

g8oz 2y ago

Claude gave me the confidence to setup a router using the relatively obscure VyOS network stack. It was a lot of back and forth. The syntax has changed quite a bit between versions and Claude kept giving me out of date code. I would reply with the error message and snippets of the current documentation and it would try again. Things eventually worked. Perhaps it was a bit of a "stone soup" situation, but I would not have attempted the project without the assistance of an LLM.

winterbloom 2y ago

Bad blog post You don't want to use AI for complex things that you might not fully understand. These are the cases where you'll miss the hallucinations and get fucked

tonyoconnell 2y ago
You just don't understand that AI becoming smarter than humans

hackburg 2y ago

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