11 ms·

I trusted an LLM, now I'm on day 4 of an afternoon project

278 points by nemofoo 2y ago

rekabis 2y ago
> As they say, I was trying to get a few birds stoned at once. Imma gonna have to work this into a convo some day. Just to see the “wait, what??” expressions on people’s faces.
righthand 2y ago
I spend a good portion of my time asking people to fix their LLM code now at work. It has made code reviews tiring. And it has increased pairing time significantly, making it a less fun activity.
- Joel_Mckay 2y ago
  When workmanship doesn't matter, than the ship is already sinking. It has been my experience 1 code clown can poison a project with dozens of reasonably talented engineers active. i.e. clowns often go through the project smearing bad kludges over acceptable standards to appear like their commit frequency means something. This is why most developers secretly dream of being plumbers. Good luck, =3
BigParm 2y ago
LLM == WGCM = Wild Goose Chase Model
tanseydavid 2y ago
I ask this question without a hint of tone or sarcasm. You said: "*it’s a junior dev faking competence. Trust it at your own risk.*" My question is simply: "wouldn't you expect to personally be able to tell that a human junior dev was faking competence?" Why should it be different with the LLM?
- latexr 2y ago
  Obviously, it depends on context. When talking to someone live you can pick up on subtle hints such as tone of voice, or where they look, or how they gesticulate, or a myriad other signals which give you a hint to their knowledge gaps. If you're communicating via text, the signals change. Furthermore, as you interact with people more often you understand them better and refine your understanding of them. LLMs always forget and “reset” and are in flux. They aren’t as consistent. Plus, they don’t grow with you and pick up on your signals and wants. It’s incredibly worrying that it needs to be explained again and again that LLMs are different from people, do not behave like people, and should not be compared to people or interacted like people, because they are not people.
  - appleorchard46 2y ago
    Interestingly your description of social cues you expect to pick up on are the exact sort of social cues I struggle with. If someone says something, generally speaking I expect it to be true unless there is an issue with it that suggests otherwise. I suppose the wide range of negative and positive experiences people seem to have working with LLMs is related to the wide range of expectations people have for their interactions in general.
- layer8 2y ago
  Not instantly. You’d give the human junior dev the benefit of the doubt at first. But when it becomes clear that the junior dev is faking competence all the time (that might take longer than the four days in TFA — yes I know it’s not exactly comparable, just saying) and won’t stop with that and start being honest instead, you’d eventually let them go, because that’s no way to work with someone.
zitterbewegung 2y ago
I have used LLMs as a tool and I start to "give up" working with it after a few tries. It excels at simple tasks, boilerplate, or scripts but larger programs you really have to know what exactly you want to do. I do see the LLMs ingesting more and more documentation and content and they are improving at giving me right answers. Almost two years ago I don't believe they had every python package indexed and now they appear to have at least the documentation or source code of it.
- XorNot 2y ago
  The trouble is the only reliable use-case LLMs actually seem good at is "augmented search engine". Any attempts at coding with them just end up feeling like trying to code via a worse interface. So it's handy to get a quick list of "all packages which do X", but it's worse then useless to have it speculate as to which one to use or why, because of the hallucination problem.
  - zitterbewegung 2y ago
    Yes it does work as an augmented search engine but, it does output working code you just have to prompt it better if the code is not that complex like a simple endpoint you just have to understand exactly what you want.
anigbrowl 2y ago
I've found them tobe quite a time saver, within limits. The blog post seemed scattered and disorganized to me, and the author admits having no experience with using LLMs to this end, so perhaps the problem lies behind their eyes.
addaon 2y ago
There's not much actual LLM-generated text in this post to go by, but it seems like each of the tokens generated by the LLM would be reasonable to have high probability. It sounds like the developer here thought that the sequence of tokens then carried meaning, where instead any possible meaning came from the reading. I wonder if this developer would be as irritated by the inaccuracies if they had cast sticks onto the ground to manage their stock portfolio and found the prophecy's "meaning" to be plausible but inaccurate.
pieix 2y ago
> AI isn’t a co-pilot; it’s a junior dev faking competence. Trust it at your own risk. This is a good take that tracks with my (heavy) usage of LLMs for coding. Leveraging productive-but-often-misguided junior devs is a skill every dev should actively cultivate!
- codr7 2y ago
  What you're doing is sacrificing learning for speed. Which is fine, if it's a conscious choice for yourself.
  - piva00 2y ago
    I don't think GP was talking about themselves being a junior using LLMs, at least my interpretation was that devs should learn how to leverage misguided junior, and LLMs are more-or-less on the level of a misguided junior. Which I completely agree, I use LLMs for the cases where I do know what I'm trying to do, I just can't remember some exact detail that would require reading documentation. It's much quicker to leverage a LLM rather than going on a wild goose chase of the piece of information I know exists. Also it's a pretty good tool to scaffold the boring stuff, asking a LLM "generate test code for X asserting A, B, and C" and editing it to be a proper test frees up mental space for more important stuff. I wouldn't trust a LLM to generate any kind of business logic-heavy code, instead I use it as a quite smart template/scaffold generator.
    - pieix 2y ago
      Thanks for explaining my intent, you nailed it.
    - codr7 2y ago
      And the end result is you won't learn the details, so you will become more and more dependent on your magic piano.
      - piva00 2y ago
        I know the details, I've been through the wading, thrashing around the docs, the books, I just can't recall the right incantation at that moment and a LLM is more efficient than searching the web. I still have the skills to search the web if the magic piano disappears. Don't know why you are trying to come up with a situation that doesn't exist, what's your point exactly against this quite narrow use-case?
stuaxo 2y ago
The junior dev faking competence is useful but needs a lot of supervision (unlike a real junior dev we don't know if this one will get better).
tacoooooooo 2y ago
the "AI lies" takeaway is way off for those actually using these tools. Calling it a "junior dev faking competence" is catchy, but misses the point. We're not expecting a co-pilot, it's a tool, a super-powered intern that needs direction. The spaghetti code mess wasn't AI "lying", it was a lack of control and proper prompting. Experienced folks aren't surprised by this. LLMs are fast for boilerplate, research, and exploring ideas, but they're not autonomous coders. The key is you staying in charge: detailed prompts, critical code review, iterative refinement. Going back to web interfaces and manual pasting because editor integration felt "too easy" is a massive overcorrection. It's like ditching cars for walking after one fender bender. Ultimately, this wasn't an AI failure, it was an inexperienced user expecting too much, too fast. The "lessons learned" are valid, but not AI-specific. For those who use LLMs effectively, they're force multipliers, not replacements. Don't blame the tool for user error. Learn to drive it properly.
- latexr 2y ago
  > We're not expecting a co-pilot Microsoft’s offering is literally called “copilot”. That is exactly what they’re marketing it as.
- cruffle_duffle 2y ago
  “Experienced folks” in this case means folks who’ve used LLM’s enough to somewhat understand how to “feed them” in ways that make the tools generate productive output. Learning to properly prompt an LLM to get a net gain in value is a skill in it of itself.
potsandpans 2y ago
Counterexample: Ive been able to complete more side projects in the last month leveraging llms than i have ever in my life. One of which I believe to have potential as a viable product, and another which involved complicated rust `no_std` and linker setup for compiling rust code onto bare metal RISCV from scratch. I think the key to being successful here is to realize that you're still at the wheel as an engineer. The llm is there to rapidly synthesize the universe of information. You still need to 1) have solid fundamentals in order to have an intuition against that synthesis, and 2) be experienced enough to translate that synthesis into actionable outcomes. If youre lacking in either, youre at the same whims of copypasta that have always existed.
- chamomeal 2y ago
  I agree with his point about asking AI to “fix” problems though. It’s really nice that you don’t have to fully understand something to use it, but that becomes a problem if you lean on it too much
- mythrwy 2y ago
  I've had both experiences strangely enough.
- talldayo 2y ago
  > which involved complicated rust `no_std` and linker setup for compiling rust code onto bare metal RISCV from scratch. That's complicated, but I wouldn't say the resulting software is complex. You gave an LLM a repetitive, translation-based job, and you got good results back. I can also believe that an LLM could write up a dopey SAAS in half the time it would take a human to do the same. But having the right parameters only takes you so far. Once you click generate, you are trusting that the model has some familiarity with your problem and can guide you without needing assistance. Most people I've seen rely entirely on linting and runtime errors to debug AI code, not "solid fundamentals" that can fact-check a problem they needed ChatGPT to solve first place. And the "experience" required to iterate and deploy AI-generated code basically boils down to your copy-and-paste skills. I like my UNIX knowledge, but it's not a big enough gate to keep out ChatGPT Andy and his cohort of enthusiastic morons. We're going to see thousands of AI-assisted success stories come out of this. But we already had those "pennies on the dollar" success stories from hiring underpaid workers out of India and Pakistan. AI will not solve the unsolved problems of our industry and in many ways it will exacerbate the preexisting issues.
nsavage 2y ago
Funny enough, I posted an article I wrote here yesterday with the same sort of thesis. Different technologies (mine was Docker) but same idea of LLM leading me astray and causing a lot of frustration
powerset 2y ago
I've had a similar experience, shipping new features at incredible speed, then waste a ton of time going down the wrong track trying to debug something because the LLM gave me a confidently wrong solution.
- williamcotton 2y ago
  Well that's kind of on you for not noticing that it was the wrong solution, isn't it?
  - cruffle_duffle 2y ago
    I think the parents post happened to everybody, and if it hasn’t it will. The edge between being actually more productive or just “pretend productive” using large language models is something that we all haven’t completely figured out yet.
  - trinix912 2y ago
    Sometimes the solution is 99% correct but the other 1% is so subtly wrong that it both doesn't work and is a debugging hell.
    - forgetfreeman 2y ago
      Welcome to programming.
  - mythrwy 2y ago
    Ya but you kind of get painted in corner sometimes. And sunken cost fallacy kicks in.
  - nyarlathotep_ 2y ago
    often it's something you casually overlook, some minor implementation detail that you didn't give much thought to that ends up being a huge mess later on, IME
  - th0ma5 2y ago
KronisLV 2y ago
In my experience LLMs will help you with things that have been solved thousands of times before and are just a matter of finding some easily researched solution. The very moment when you try to go off the beaten path and do something unconventional or stuff that most people won't have written a lot about, it gets more tricky. Just consider how many people will know how to configure some middleware in a Node.js project... vs most things related to hardware or low level work. Or even working with complex legacy codebases that have bits of code with obscure ways of interacting and more levels of abstraction that can be reasonably put in context. Then again, if an LLM gets confused, then a person might as well. So, personally I try to write code that'd be understandable by juniors and LLMs alike.
- winocm 2y ago
  In my experience, a LLM decided to not know type alignment rules in C and confidently trotted out the wrong answer. It left a horrible taste in my mouth for the one time I decided to look at using a LLM for anything and it keeps leaving me wondering if I'd end up more time bashing the LLM into working than just working out the answer myself and learning the underlying reasoning why. It was so wrong that I wonder what version of the C standard it was even hallucinating.
- NitpickLawyer 2y ago
  > vs most things related to hardware or low level work. counter point: https://github.com/ggerganov/llama.cpp/pull/11453 https://github.com/ggerganov/llama.cpp/pull/11453 > This PR provides a big jump in speed for WASM by leveraging SIMD instructions for qX_K_q8_K and qX_0_q8_0 dot product functions. > Surprisingly, 99% of the code in this PR is written by DeekSeek-R1. The only thing I do is to develop tests and write prompts (with some trials and errors)
  - alfalfasprout 2y ago
    A single PR doesn't really "prove" anything. Optimization passes on well-tested narrowly scoped code are something that LLMs are already pretty good at.
anaisbetts 2y ago
Context matters a lot, copy-pasting snippets to a webpage is _way_ less effective than Cursor/Windsurf.
cmdtab 2y ago
Today, I needed to write a proxy[0] that wraps an object and log all method calls recursively. I asked claude to write the initial version. It came up with a complicated class based solution. I spent more than 30 minutes getting a good abstract to come out. I was copy pasting typescript errors and applying fixes it suggested without thinking much. In the end, I gave up and wrote what I wanted myself in 5 minutes. 0] https://github.com/cloudycotton/browser-operator/blob/main/src/proxies.ts https://github.com/cloudycotton/browser-operator/blob/main/s...
- dambi0 2y ago
  Would you have written it in five minutes has you not just spent 30 minutes ruling out wrong solutions?
  - cmdtab 2y ago
    Yes. I wrote how to do it technically. Claude was able to come up with a solution that worked on second attempt. The problem was it didn’t work with typescript nicely. The approach overcomplicated anything that depended on this class.
- deleted 2y ago
  [deleted]
transcriptase 2y ago
I’ve been able to do more far complex things with ESP32s and RPis in an evening without knowing the first thing about python or c++. I can also tell when it’s stuck in some kind of context swamp and won’t be any more help, because it will just keep making the same stupid mistakes over and over and generally forgetting past instructions. At that point I take the last working code and paste it into a new chat.
thot_experiment 2y ago
As opposed to not trusting an LLM, and ending up on day 4 of an afternoon project? :P I've been doing that since way before LLMs were a thing.
ravroid 2y ago
One strategy I've been experimenting with is maintaining a 'spec' document, outlining all features and relevant technical notes about a project. I include the spec with all relevant source files in my prompt before asking the LLM to implement a new change or feature. This way it doesn't have to do as much guessing as to what my code is doing, and I can avoid relying on long-running conversations to maintain context. Instead, for each big change I include an up-to-date spec and all of the relevant source files. I update the spec to reflect the current state of the project as changes are made to give the LLM context about my project (this also doubles as documentation). I use an NPM script to automate concatenating the spec + source files + prompt, which I then copy/paste to o1. So far this has been working somewhat reliably for the early stages of a project but has diminishing returns.
- SparkyMcUnicorn 2y ago
  You're describing functionality that's built into Aider. You might want to try it out. Aider also has a copy/paste mode to use web ui interfaces/subscriptions instead apis. I definitely use and update my CONVENTIONS.md files and started adding a second specification file for new projects. This + architect + "can your suggestion be improved, or is there a better way?" has gotten me pretty far.
  - ravroid 2y ago
    Didn't know about Aider - going to give that a try, thanks!
mordymoop 2y ago
I am frankly tired of seeing this kind of post on HN. I feel like the population of programmers is bifurcating into those who are committed to mastering these tools, learning to work around their limitations and working to leverage their strengths… and those who are committed to complaining about how they aren’t already perfect Culture Ship Minds. We get it. They’re not superintelligent at everything yet. They couldn’t infer what you must’ve really meant in your heart from your initial unskillful prompt. They couldn’t foresee every possible bug and edge case from the first moment of conceptualizing the design, a flaw which I’m sure you don’t have. The thing that pushes me over the line into ranting territory is that computer programmers, of all people, should know that computers do what you tell them to.
- antigeox 2y ago
  > I am frankly tired of seeing this kind of post on HN. You've been here since 2016 and this is the kind of posting that finally gets to you? How in the world have you avoided all the shitposts in the last decade? What is your secret?
  - mordymoop 2y ago
    It’s the fact that it’s the same thing over and over. The 100th case of “Well I had a bad experience using LLM for coding!” is not interesting.
    - antigeox 2y ago
      [dead]
- bigstrat2003 2y ago
  Nobody is complaining that LLMs aren't perfect Culture minds. People disagree with the premise that they are useful tools given their current capabilities. Your portrayal of those with whom you disagree is such a strawman that it might as well be set to a soy-vs-wojak meme.
  - 2y ago
rglover 2y ago
> AI is great for generating ideas or drafting code, but it doesn’t understand. It’s like giving a junior developer a chainsaw instead of a scalpel—it might finish the job, but you’ll spend twice as long cleaning up the mess. For anything remotely complex, this is dead on. I use various models daily to help with coding, and more often than not, I have to just DIY it or start brand new chats (because the original context got overwhelmed and started hallucinating). This is why it's incredibly frustrating to see VCs and AI founders straight-up gaslighting people about what this stuff can (or will) do. They're trying to push this as a "work killer," but really, it's going to be some version of the opposite: a mess creator that necessitates human intervention. Where we're at is amazing, but we've got a loooong way to go before we can be on hover crafts sipping sodas Wall-E style.
lxe 2y ago
I'm developing an intuition to how and what to ask in order for the LLM's answer to be helpful. Once you start spinning your wheels, clear context, copy what you need, and start over.
insane_dreamer 2y ago
> junior dev faking competence A bit on a tangent, but has there been any discussion of how junior devs in the future are ever going to get past that stage and become senior dev calibre if companies can replace the junior devs with AIs? Or is the thinking we'll be fine until all the current senior devs die off and by then AI will be able to replace them too so we won't need anyone? 1. CS/Eng degree 2. ??? 3. Senior dev!
- dragonwriter 2y ago
  Training will adapt to the widespread use of AI coding assistance if they are that universally useful, and people will come into the market as junior AI wranglers, with skillsets stronger than curent junior devs is some areas but weaker in others; current seniors will grumble about holes in their knowledge, but that's been the case with the generational changes in software development as the common problems people face at different levels have shifted over time. The details are new, but the process isn't.
  - insane_dreamer 2y ago
    Not if the goal is to replace the junior devs with AIs -- people won't be "coming into the market" because they won't be needed. Companies are not saving money by paying for AI tools if they continue to hire the same number of people. The only way it makes financial sense, and for the enormous amounts of money being invested into AI to reap profits, is if companies are able to reduce the cost of labor. First, they only need 75% of the junior devs they have now, then 50%, then 25%.
    - dragonwriter 2y ago
      > Not if the goal is to replace the junior devs with AIs -- people won't be "coming into the market" because they won't be needed. It won't happen all at once, and as tasks done by current juniors are incrementally taken over by AI, the expected entry skillset will evolve in line with those changes. There will always be junior people in the field, but their expected knowledgebase and tasks will evolve, and even if 100% of the work currently done by juniors is eventually AI-ified, there will still be juniors, they just will be doing completely different things, and going through a completely different learning process to get there. > Companies are not saving money by paying for AI tools if they continue to hire the same number of people. Companies which have a fixed lump of tech work (in practice, none, actually) will save money because they will hire fewer total workers because output per worker will increase, but they will still have people who are newer and more experienced within that set, because the More realistic companies that either make money with tech work or that apply internal effort to tech as long as it has net positive utility may actually end up spending more on tech, because each dollar spent gives more results. This still saves money (or makes more money), but the savings (where it is about savings, and not revenue) will be in the areas tech is applied to, not tech itself.
dstainer 2y ago
One of the areas where I've struggled to get effective use out of the LLM's is with UI/UX. That isn't my primary area of expertise (backend) so it definitively could be operator error here, but I use tools like v0.dev and just can't quite get it to do what I need it to do. Anybody have any tools, workflows, suggestions for this?
DigitalSea 2y ago
This is like watching a carpenter blame their hammer because they didn’t measure twice. AI is a tool, it's like a power tool for a tradesperson: it'll amplify your skills, but if you let it steer the whole project? You’ll end up with a pile of bent nails. LLMs are jittery apprentices. They'll hallucinate measurements, over-sand perfectly good code, or spin you in circles for hours. I’ve been there back in the GPT-4 days especially, nothing stings like realising you wasted a day debugging AI’s creative solution to a problem you could've solved in 20 minutes. When you treat AI like a toolbelt, not a replacement for your own brain? Magic. It’s killer at grunt work like; explaining regex, scaffolding boilerplate, or untangling JWT auth spaghetti. You still gotta hold the blueprint. AI ain't some magic wand: it’s a nail gun. Point it wrong, and you’ll spend four days prying out mistakes. Sucks it cost you time, but hey, now you know to never let the tool work you. It's hopefully a lesson OP learns once and doesn't let it sour their experience with AI, because when utilised properly, you can really get things done, even if it's just the tedious/boring stuff or things you'd spend time Google bashing, reading docs or finding on StackOverflow.
groby_b 2y ago
I mean.... No design. Hardware & software. 2 different platforms. A new language. Zig. Unrealistic time expectations. A senior SWE would've still tanked this, just in different ways. Personally, I'd still consider it a valuable experiment, because the lessons learned are really valuable ones. Enjoy round 2 :)
protocolture 2y ago
I used very similar hardware to accomplish a very similar project (Notifications on a round screen) and the LLM was great for everything except UX.
tippytippytango 2y ago
What I learned is you can’t outsource expertise to an LLM, after many similar experiences to OP. Don’t ask it for advice, ask it to teach you so you can make decisions like this on your own. Preferably ground questions with excerpts from human made documents. It seems to make less mistakes when explaining things, and those mistakes are more noticeable when they do happen.
Fourier864 2y ago
FWIW, I fed in the same problematic prompt to all the current ChatGPT models and even the legacy/mini models enumerated a bunch of pitfalls and considerations. I wonder why/how it managed to tell the author everything was perfect? A weird one-off occurrence?
deleted 2y ago
[deleted]
theodric 2y ago
> "From her perspective, I order doordash and turn into a degen who is unfit to father. From my perspective, I get to enjoy my favorite place and just tinker or play games or do whatever. These are the days I get to play mad scientist and feel most like myself." Most demeaning and depressingly toxic thing I've read today...
neilv 2y ago
> TLDR - AI isn’t a co-pilot; it’s a junior dev faking competence. Trust it at your own risk. A junior dev faking competence while plagiarizing like crazy. The plagiarizing part is why the junior dev from hell might not get fired: laundering open source copyrights can have beancounter alignment.
65 2y ago
I have never found a use for LLMs for programming because I can find the (correct) answer much easier with a search. Perhaps the search engines just suck so hard these days people resort to LLMs. I use Kagi and GitHub to search and the results are much better.
turnsout 2y ago
Counterpoint: I'm on day 26 of an afternoon project I never would have attempted on my own, and I'm going to release it as a major feature. Cursor & Claude got the boilerplate set up, which was half the mental barrier. Then they acted as thought partners as I tried out various implementations. In the end, I came up with the algorithm to make the thing performant, and now I'm hand-coding all the shader code—but they helped me think through what needed to be done. My take is: LLMs are best at helping you code at the edge of your capabilities, where you still have enough knowledge to know when they're going wrong. But they'll help you push that edge forward.
lbotos 2y ago
Nemo, are you using a self-hosted install or .com? If .com, email me (it's in my profile) and I can see if there is a reason your account is getting so heavily captcha'd.
adsharma 2y ago
A few mitigation ideas * Get AI to write tests * Use copy/paste. No IDE * Use python (not because it's better than zig)
tashian 2y ago
I used Claude to help me build a side project in 4 hours that I would never have built otherwise. Essentially, it's a morphing wavetable oscillator in React (https://waves.tashian.com https://waves.tashian.com). Six months ago, I tried building this app with ChatGPT and got nowhere fast. Building it with Claude required a gluing together a few things that I didn't know much about: JavaScript audio processing, drawing on a JavaScript canvas, an algorithm for bilinear interpolation. I don't write JavaScript often. But I know how to program and I understand what I'm looking at. The project came together easily and the creative momentum of it felt great to me. The most amazing moment was when I reported a bug—I told Claude that the audio was stuttering whenever I moved the controls—and it figured out that we needed to use an AudioWorklet thread instead of trying to play the audio directly from the React component. I had never even heard of AudioWorklet. Claude refactored my code to use the AudioWorklet, and the stutter disappeared. I wouldn't have built this without Claude, because I didn't need it to exist that badly. Claude reduced the creative inertia just enough for me to get it done.
- masklinn 2y ago
  What was your workflow for doing that? Just going back and forth in a chat, or a more integrated experience in a dedicated editor?
  - tashian 2y ago
    Just copy/paste from the chat window. I kept running into token limits. I came away from it wanting a much better workflow. That's the next step for me in learning AI... playing with different integrated editor tools.
Havoc 2y ago
That’s a fun writeup. I’ve come to a similar conclusion - for now at least it’s best applied at a fairly granular level. Make me a red brick wall there rather than „hey architect make me a house“. I do think OP tried a bit too much new stuff in one go though. USB plus zig is quite a bit more ambitious than the traditional hello world in a new lang
qiqitori 2y ago
Your plan was to use USB, but to me it looks like you're pretty much just using serial via USB. That's completely fine of course! One cheap way to tackle your problem is to use a version of printf with locking, which is likely available in many microcontroller SDKs (it's also slow). (Or you could add your own mutex.) USB-CDC is cooler than that, you can make the Pico identify as more than just one device. E.g. https://github.com/Noltari/pico-uart-bridge https://github.com/Noltari/pico-uart-bridge identifies as two devices (so you get /dev/ttyACM0 and /dev/ttyACM1). So you could have logs on one and image transfers on another. I don't think you're limited to just two, but I haven't looked into it too far. You can of course also use other USB protocols. For example you could have the Pico present itself as a mass-storage device or a USB camera, etc. You're just limited by the relatively slow speed of USB1.1. (Though the Pico doesn't exactly have a lot of memory so even USB1.1 will saturate all your RAM in less than 1 second)
medhir 2y ago
Perhaps being a PM for several years has helped, I’ve had great success speeding up my programming workflows by prompting Claude with very specific, well defined tasks. Like many others are saying, you need to be in the drivers seat and in control. The LLM is not going to fully complete your objectives for you, but it will speed you up when provided with enough context, especially on mundane boilerplate tasks. I think the key to LLMs being useful is knowing how to prompt with enough context to get a useful output, and knowing what context is not important so the output doesn’t lead you in the wrong direction.
Graziano_M 2y ago
OP could have written the firmware in zig, too! https://github.com/ZigEmbeddedGroup/microzig https://github.com/ZigEmbeddedGroup/microzig
ffitch 2y ago
for what it’s worth, my afternoon projects tend to take over four days even if no llm is involved
- raleighm 2y ago
  Laughed aloud at this one. Yup, same here.
superq 2y ago
Most LLMs default to being sycophantic yes-men, but if you create a custom prompt, it can help mitigate any issues. I have a custom prompt that instructs gpt4o to get aggressive about attacking anything I say (and, importantly, anything it says). Here's my result for the same question: https://chatgpt.com/share/67984aa9-1608-8012-be93-a77728ab8e50 https://chatgpt.com/share/67984aa9-1608-8012-be93-a77728ab8e...
cudgy 2y ago
Really enjoyed reading your article. Haven’t laughed as much reading a tech article in quite some time. You should consider doing some YouTube videos as your communications style is very humble and entertaining. Made me wanna join in your garage and help out with the project :)
j45 2y ago
I doubt one experience, positive, or negative counts for them all. Learning how to build or create with a new kind of word processor is a skill unto itself.
petarb 2y ago
> My wife and I have a deal where 1 day a month, She takes the kiddo and I am absolved of all responsibilities. I get a full day to lock in and build projects. I love it!
djray 2y ago
The OP misunderstands (perhaps deliberately or for humorous effect) what a co-pilot is. This is telling: "I learned that I need to stay firmly in the driver’s seat when tackling new tech." Er, that's pretty much what a pilot is supposed to do! You can't (as yet) just give an AI free reign over your codebase and expect to come back later that day to discover a fully finished implementation. Maybe unless your prompt was "Make a snake game in Python". A pilot would be supervising their co-pilot at all times. Comparing AIs to junior devs is getting tiresome. AIs like Claude and newer versions of ChatGPT have incredible knowledge bases. Yes, they do slip up, especially with esoteric matters where there are few authoritative (or several conflicting) sources, but the breadth of knowledge in and of itself is very valuable. As an anecdote, neither Claude nor ChatGPT were able to accurately answer a question I had about file operation flags yesterday, but when I said to ChatGPT that its answer wasn't correct, it apologised and said the Raymond Chen article it had sourced wasn't super clear about the particular combination I'd asked about. That's like having your own research assistant, not a headstrong overconfident junior dev. Yes, they make mistakes, but at least now they'll admit to them. This is a long way from a year or two ago. In conclusion: don't use an AI as one of your primary sources of information for technology you're new to, especially if you're not double-checking its answers like a good pilot.
sarob 2y ago
You are running the show and the LLM can act like many other roles to help you. Obscure or confusing topics, likely the LLM will be as bad at solving as any employee. Give it a plan. Follow up and make sure it’s on track.
jmt710 2y ago
[dead]

278 points by nemofoo 2y ago

> As they say, I was trying to get a few birds stoned at once. Imma gonna have to work this into a convo some day. Just to see the “wait, what??” expressions on people’s faces.

righthand 2y ago

I spend a good portion of my time asking people to fix their LLM code now at work. It has made code reviews tiring. And it has increased pairing time significantly, making it a less fun activity.

Joel_Mckay 2y ago
When workmanship doesn't matter, than the ship is already sinking. It has been my experience 1 code clown can poison a project with dozens of reasonably talented engineers active. i.e. clowns often go through the project smearing bad kludges over acceptable standards to appear like their commit frequency means something. This is why most developers secretly dream of being plumbers. Good luck, =3

BigParm 2y ago

LLM == WGCM = Wild Goose Chase Model

tanseydavid 2y ago

I ask this question without a hint of tone or sarcasm. You said: "*it’s a junior dev faking competence. Trust it at your own risk.*" My question is simply: "wouldn't you expect to personally be able to tell that a human junior dev was faking competence?" Why should it be different with the LLM?

latexr 2y ago
Obviously, it depends on context. When talking to someone live you can pick up on subtle hints such as tone of voice, or where they look, or how they gesticulate, or a myriad other signals which give you a hint to their knowledge gaps. If you're communicating via text, the signals change. Furthermore, as you interact with people more often you understand them better and refine your understanding of them. LLMs always forget and “reset” and are in flux. They aren’t as consistent. Plus, they don’t grow with you and pick up on your signals and wants. It’s incredibly worrying that it needs to be explained again and again that LLMs are different from people, do not behave like people, and should not be compared to people or interacted like people, because they are not people.
- appleorchard46 2y ago
  Interestingly your description of social cues you expect to pick up on are the exact sort of social cues I struggle with. If someone says something, generally speaking I expect it to be true unless there is an issue with it that suggests otherwise. I suppose the wide range of negative and positive experiences people seem to have working with LLMs is related to the wide range of expectations people have for their interactions in general.
layer8 2y ago
Not instantly. You’d give the human junior dev the benefit of the doubt at first. But when it becomes clear that the junior dev is faking competence all the time (that might take longer than the four days in TFA — yes I know it’s not exactly comparable, just saying) and won’t stop with that and start being honest instead, you’d eventually let them go, because that’s no way to work with someone.

zitterbewegung 2y ago

I have used LLMs as a tool and I start to "give up" working with it after a few tries. It excels at simple tasks, boilerplate, or scripts but larger programs you really have to know what exactly you want to do. I do see the LLMs ingesting more and more documentation and content and they are improving at giving me right answers. Almost two years ago I don't believe they had every python package indexed and now they appear to have at least the documentation or source code of it.

XorNot 2y ago
The trouble is the only reliable use-case LLMs actually seem good at is "augmented search engine". Any attempts at coding with them just end up feeling like trying to code via a worse interface. So it's handy to get a quick list of "all packages which do X", but it's worse then useless to have it speculate as to which one to use or why, because of the hallucination problem.
- zitterbewegung 2y ago
  Yes it does work as an augmented search engine but, it does output working code you just have to prompt it better if the code is not that complex like a simple endpoint you just have to understand exactly what you want.

anigbrowl 2y ago

I've found them tobe quite a time saver, within limits. The blog post seemed scattered and disorganized to me, and the author admits having no experience with using LLMs to this end, so perhaps the problem lies behind their eyes.

addaon 2y ago

There's not much actual LLM-generated text in this post to go by, but it seems like each of the tokens generated by the LLM would be reasonable to have high probability. It sounds like the developer here thought that the sequence of tokens then carried meaning, where instead any possible meaning came from the reading. I wonder if this developer would be as irritated by the inaccuracies if they had cast sticks onto the ground to manage their stock portfolio and found the prophecy's "meaning" to be plausible but inaccurate.

pieix 2y ago

> AI isn’t a co-pilot; it’s a junior dev faking competence. Trust it at your own risk. This is a good take that tracks with my (heavy) usage of LLMs for coding. Leveraging productive-but-often-misguided junior devs is a skill every dev should actively cultivate!

codr7 2y ago
What you're doing is sacrificing learning for speed. Which is fine, if it's a conscious choice for yourself.
- piva00 2y ago
  I don't think GP was talking about themselves being a junior using LLMs, at least my interpretation was that devs should learn how to leverage misguided junior, and LLMs are more-or-less on the level of a misguided junior. Which I completely agree, I use LLMs for the cases where I do know what I'm trying to do, I just can't remember some exact detail that would require reading documentation. It's much quicker to leverage a LLM rather than going on a wild goose chase of the piece of information I know exists. Also it's a pretty good tool to scaffold the boring stuff, asking a LLM "generate test code for X asserting A, B, and C" and editing it to be a proper test frees up mental space for more important stuff. I wouldn't trust a LLM to generate any kind of business logic-heavy code, instead I use it as a quite smart template/scaffold generator.
  - pieix 2y ago
    Thanks for explaining my intent, you nailed it.
  - codr7 2y ago
    And the end result is you won't learn the details, so you will become more and more dependent on your magic piano.
    - piva00 2y ago
      I know the details, I've been through the wading, thrashing around the docs, the books, I just can't recall the right incantation at that moment and a LLM is more efficient than searching the web. I still have the skills to search the web if the magic piano disappears. Don't know why you are trying to come up with a situation that doesn't exist, what's your point exactly against this quite narrow use-case?

stuaxo 2y ago

The junior dev faking competence is useful but needs a lot of supervision (unlike a real junior dev we don't know if this one will get better).

tacoooooooo 2y ago

the "AI lies" takeaway is way off for those actually using these tools. Calling it a "junior dev faking competence" is catchy, but misses the point. We're not expecting a co-pilot, it's a tool, a super-powered intern that needs direction. The spaghetti code mess wasn't AI "lying", it was a lack of control and proper prompting. Experienced folks aren't surprised by this. LLMs are fast for boilerplate, research, and exploring ideas, but they're not autonomous coders. The key is you staying in charge: detailed prompts, critical code review, iterative refinement. Going back to web interfaces and manual pasting because editor integration felt "too easy" is a massive overcorrection. It's like ditching cars for walking after one fender bender. Ultimately, this wasn't an AI failure, it was an inexperienced user expecting too much, too fast. The "lessons learned" are valid, but not AI-specific. For those who use LLMs effectively, they're force multipliers, not replacements. Don't blame the tool for user error. Learn to drive it properly.

latexr 2y ago
> We're not expecting a co-pilot Microsoft’s offering is literally called “copilot”. That is exactly what they’re marketing it as.
cruffle_duffle 2y ago
“Experienced folks” in this case means folks who’ve used LLM’s enough to somewhat understand how to “feed them” in ways that make the tools generate productive output. Learning to properly prompt an LLM to get a net gain in value is a skill in it of itself.

potsandpans 2y ago

Counterexample: Ive been able to complete more side projects in the last month leveraging llms than i have ever in my life. One of which I believe to have potential as a viable product, and another which involved complicated rust `no_std` and linker setup for compiling rust code onto bare metal RISCV from scratch. I think the key to being successful here is to realize that you're still at the wheel as an engineer. The llm is there to rapidly synthesize the universe of information. You still need to 1) have solid fundamentals in order to have an intuition against that synthesis, and 2) be experienced enough to translate that synthesis into actionable outcomes. If youre lacking in either, youre at the same whims of copypasta that have always existed.

chamomeal 2y ago
I agree with his point about asking AI to “fix” problems though. It’s really nice that you don’t have to fully understand something to use it, but that becomes a problem if you lean on it too much
mythrwy 2y ago
I've had both experiences strangely enough.
talldayo 2y ago
> which involved complicated rust `no_std` and linker setup for compiling rust code onto bare metal RISCV from scratch. That's complicated, but I wouldn't say the resulting software is complex. You gave an LLM a repetitive, translation-based job, and you got good results back. I can also believe that an LLM could write up a dopey SAAS in half the time it would take a human to do the same. But having the right parameters only takes you so far. Once you click generate, you are trusting that the model has some familiarity with your problem and can guide you without needing assistance. Most people I've seen rely entirely on linting and runtime errors to debug AI code, not "solid fundamentals" that can fact-check a problem they needed ChatGPT to solve first place. And the "experience" required to iterate and deploy AI-generated code basically boils down to your copy-and-paste skills. I like my UNIX knowledge, but it's not a big enough gate to keep out ChatGPT Andy and his cohort of enthusiastic morons. We're going to see thousands of AI-assisted success stories come out of this. But we already had those "pennies on the dollar" success stories from hiring underpaid workers out of India and Pakistan. AI will not solve the unsolved problems of our industry and in many ways it will exacerbate the preexisting issues.

nsavage 2y ago

Funny enough, I posted an article I wrote here yesterday with the same sort of thesis. Different technologies (mine was Docker) but same idea of LLM leading me astray and causing a lot of frustration

powerset 2y ago

I've had a similar experience, shipping new features at incredible speed, then waste a ton of time going down the wrong track trying to debug something because the LLM gave me a confidently wrong solution.

williamcotton 2y ago
Well that's kind of on you for not noticing that it was the wrong solution, isn't it?
- cruffle_duffle 2y ago
  I think the parents post happened to everybody, and if it hasn’t it will. The edge between being actually more productive or just “pretend productive” using large language models is something that we all haven’t completely figured out yet.
- trinix912 2y ago
  Sometimes the solution is 99% correct but the other 1% is so subtly wrong that it both doesn't work and is a debugging hell.
  - forgetfreeman 2y ago
    Welcome to programming.
- mythrwy 2y ago
  Ya but you kind of get painted in corner sometimes. And sunken cost fallacy kicks in.
- nyarlathotep_ 2y ago
  often it's something you casually overlook, some minor implementation detail that you didn't give much thought to that ends up being a huge mess later on, IME
- th0ma5 2y ago

KronisLV 2y ago

In my experience LLMs will help you with things that have been solved thousands of times before and are just a matter of finding some easily researched solution. The very moment when you try to go off the beaten path and do something unconventional or stuff that most people won't have written a lot about, it gets more tricky. Just consider how many people will know how to configure some middleware in a Node.js project... vs most things related to hardware or low level work. Or even working with complex legacy codebases that have bits of code with obscure ways of interacting and more levels of abstraction that can be reasonably put in context. Then again, if an LLM gets confused, then a person might as well. So, personally I try to write code that'd be understandable by juniors and LLMs alike.

winocm 2y ago
In my experience, a LLM decided to not know type alignment rules in C and confidently trotted out the wrong answer. It left a horrible taste in my mouth for the one time I decided to look at using a LLM for anything and it keeps leaving me wondering if I'd end up more time bashing the LLM into working than just working out the answer myself and learning the underlying reasoning why. It was so wrong that I wonder what version of the C standard it was even hallucinating.
NitpickLawyer 2y ago
> vs most things related to hardware or low level work. counter point: https://github.com/ggerganov/llama.cpp/pull/11453 https://github.com/ggerganov/llama.cpp/pull/11453 > This PR provides a big jump in speed for WASM by leveraging SIMD instructions for qX_K_q8_K and qX_0_q8_0 dot product functions. > Surprisingly, 99% of the code in this PR is written by DeekSeek-R1. The only thing I do is to develop tests and write prompts (with some trials and errors)
- alfalfasprout 2y ago
  A single PR doesn't really "prove" anything. Optimization passes on well-tested narrowly scoped code are something that LLMs are already pretty good at.

anaisbetts 2y ago

Context matters a lot, copy-pasting snippets to a webpage is _way_ less effective than Cursor/Windsurf.

cmdtab 2y ago

Today, I needed to write a proxy[0] that wraps an object and log all method calls recursively. I asked claude to write the initial version. It came up with a complicated class based solution. I spent more than 30 minutes getting a good abstract to come out. I was copy pasting typescript errors and applying fixes it suggested without thinking much. In the end, I gave up and wrote what I wanted myself in 5 minutes. 0] https://github.com/cloudycotton/browser-operator/blob/main/src/proxies.ts https://github.com/cloudycotton/browser-operator/blob/main/s...

dambi0 2y ago
Would you have written it in five minutes has you not just spent 30 minutes ruling out wrong solutions?
- cmdtab 2y ago
  Yes. I wrote how to do it technically. Claude was able to come up with a solution that worked on second attempt. The problem was it didn’t work with typescript nicely. The approach overcomplicated anything that depended on this class.
deleted 2y ago
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transcriptase 2y ago

I’ve been able to do more far complex things with ESP32s and RPis in an evening without knowing the first thing about python or c++. I can also tell when it’s stuck in some kind of context swamp and won’t be any more help, because it will just keep making the same stupid mistakes over and over and generally forgetting past instructions. At that point I take the last working code and paste it into a new chat.

thot_experiment 2y ago

As opposed to not trusting an LLM, and ending up on day 4 of an afternoon project? :P I've been doing that since way before LLMs were a thing.

ravroid 2y ago

One strategy I've been experimenting with is maintaining a 'spec' document, outlining all features and relevant technical notes about a project. I include the spec with all relevant source files in my prompt before asking the LLM to implement a new change or feature. This way it doesn't have to do as much guessing as to what my code is doing, and I can avoid relying on long-running conversations to maintain context. Instead, for each big change I include an up-to-date spec and all of the relevant source files. I update the spec to reflect the current state of the project as changes are made to give the LLM context about my project (this also doubles as documentation). I use an NPM script to automate concatenating the spec + source files + prompt, which I then copy/paste to o1. So far this has been working somewhat reliably for the early stages of a project but has diminishing returns.

SparkyMcUnicorn 2y ago
You're describing functionality that's built into Aider. You might want to try it out. Aider also has a copy/paste mode to use web ui interfaces/subscriptions instead apis. I definitely use and update my CONVENTIONS.md files and started adding a second specification file for new projects. This + architect + "can your suggestion be improved, or is there a better way?" has gotten me pretty far.
- ravroid 2y ago
  Didn't know about Aider - going to give that a try, thanks!

mordymoop 2y ago

I am frankly tired of seeing this kind of post on HN. I feel like the population of programmers is bifurcating into those who are committed to mastering these tools, learning to work around their limitations and working to leverage their strengths… and those who are committed to complaining about how they aren’t already perfect Culture Ship Minds. We get it. They’re not superintelligent at everything yet. They couldn’t infer what you must’ve really meant in your heart from your initial unskillful prompt. They couldn’t foresee every possible bug and edge case from the first moment of conceptualizing the design, a flaw which I’m sure you don’t have. The thing that pushes me over the line into ranting territory is that computer programmers, of all people, should know that computers do what you tell them to.

antigeox 2y ago
> I am frankly tired of seeing this kind of post on HN. You've been here since 2016 and this is the kind of posting that finally gets to you? How in the world have you avoided all the shitposts in the last decade? What is your secret?
- mordymoop 2y ago
  It’s the fact that it’s the same thing over and over. The 100th case of “Well I had a bad experience using LLM for coding!” is not interesting.
  - antigeox 2y ago
    [dead]
bigstrat2003 2y ago
Nobody is complaining that LLMs aren't perfect Culture minds. People disagree with the premise that they are useful tools given their current capabilities. Your portrayal of those with whom you disagree is such a strawman that it might as well be set to a soy-vs-wojak meme.
- 2y ago

rglover 2y ago

> AI is great for generating ideas or drafting code, but it doesn’t understand. It’s like giving a junior developer a chainsaw instead of a scalpel—it might finish the job, but you’ll spend twice as long cleaning up the mess. For anything remotely complex, this is dead on. I use various models daily to help with coding, and more often than not, I have to just DIY it or start brand new chats (because the original context got overwhelmed and started hallucinating). This is why it's incredibly frustrating to see VCs and AI founders straight-up gaslighting people about what this stuff can (or will) do. They're trying to push this as a "work killer," but really, it's going to be some version of the opposite: a mess creator that necessitates human intervention. Where we're at is amazing, but we've got a loooong way to go before we can be on hover crafts sipping sodas Wall-E style.

lxe 2y ago

I'm developing an intuition to how and what to ask in order for the LLM's answer to be helpful. Once you start spinning your wheels, clear context, copy what you need, and start over.

insane_dreamer 2y ago

> junior dev faking competence A bit on a tangent, but has there been any discussion of how junior devs in the future are ever going to get past that stage and become senior dev calibre if companies can replace the junior devs with AIs? Or is the thinking we'll be fine until all the current senior devs die off and by then AI will be able to replace them too so we won't need anyone? 1. CS/Eng degree 2. ??? 3. Senior dev!

dragonwriter 2y ago
Training will adapt to the widespread use of AI coding assistance if they are that universally useful, and people will come into the market as junior AI wranglers, with skillsets stronger than curent junior devs is some areas but weaker in others; current seniors will grumble about holes in their knowledge, but that's been the case with the generational changes in software development as the common problems people face at different levels have shifted over time. The details are new, but the process isn't.
- insane_dreamer 2y ago
  Not if the goal is to replace the junior devs with AIs -- people won't be "coming into the market" because they won't be needed. Companies are not saving money by paying for AI tools if they continue to hire the same number of people. The only way it makes financial sense, and for the enormous amounts of money being invested into AI to reap profits, is if companies are able to reduce the cost of labor. First, they only need 75% of the junior devs they have now, then 50%, then 25%.
  - dragonwriter 2y ago
    > Not if the goal is to replace the junior devs with AIs -- people won't be "coming into the market" because they won't be needed. It won't happen all at once, and as tasks done by current juniors are incrementally taken over by AI, the expected entry skillset will evolve in line with those changes. There will always be junior people in the field, but their expected knowledgebase and tasks will evolve, and even if 100% of the work currently done by juniors is eventually AI-ified, there will still be juniors, they just will be doing completely different things, and going through a completely different learning process to get there. > Companies are not saving money by paying for AI tools if they continue to hire the same number of people. Companies which have a fixed lump of tech work (in practice, none, actually) will save money because they will hire fewer total workers because output per worker will increase, but they will still have people who are newer and more experienced within that set, because the More realistic companies that either make money with tech work or that apply internal effort to tech as long as it has net positive utility may actually end up spending more on tech, because each dollar spent gives more results. This still saves money (or makes more money), but the savings (where it is about savings, and not revenue) will be in the areas tech is applied to, not tech itself.

dstainer 2y ago

One of the areas where I've struggled to get effective use out of the LLM's is with UI/UX. That isn't my primary area of expertise (backend) so it definitively could be operator error here, but I use tools like v0.dev and just can't quite get it to do what I need it to do. Anybody have any tools, workflows, suggestions for this?

DigitalSea 2y ago

This is like watching a carpenter blame their hammer because they didn’t measure twice. AI is a tool, it's like a power tool for a tradesperson: it'll amplify your skills, but if you let it steer the whole project? You’ll end up with a pile of bent nails. LLMs are jittery apprentices. They'll hallucinate measurements, over-sand perfectly good code, or spin you in circles for hours. I’ve been there back in the GPT-4 days especially, nothing stings like realising you wasted a day debugging AI’s creative solution to a problem you could've solved in 20 minutes. When you treat AI like a toolbelt, not a replacement for your own brain? Magic. It’s killer at grunt work like; explaining regex, scaffolding boilerplate, or untangling JWT auth spaghetti. You still gotta hold the blueprint. AI ain't some magic wand: it’s a nail gun. Point it wrong, and you’ll spend four days prying out mistakes. Sucks it cost you time, but hey, now you know to never let the tool work you. It's hopefully a lesson OP learns once and doesn't let it sour their experience with AI, because when utilised properly, you can really get things done, even if it's just the tedious/boring stuff or things you'd spend time Google bashing, reading docs or finding on StackOverflow.

groby_b 2y ago

I mean.... No design. Hardware & software. 2 different platforms. A new language. Zig. Unrealistic time expectations. A senior SWE would've still tanked this, just in different ways. Personally, I'd still consider it a valuable experiment, because the lessons learned are really valuable ones. Enjoy round 2 :)

protocolture 2y ago

I used very similar hardware to accomplish a very similar project (Notifications on a round screen) and the LLM was great for everything except UX.

tippytippytango 2y ago

What I learned is you can’t outsource expertise to an LLM, after many similar experiences to OP. Don’t ask it for advice, ask it to teach you so you can make decisions like this on your own. Preferably ground questions with excerpts from human made documents. It seems to make less mistakes when explaining things, and those mistakes are more noticeable when they do happen.

Fourier864 2y ago

FWIW, I fed in the same problematic prompt to all the current ChatGPT models and even the legacy/mini models enumerated a bunch of pitfalls and considerations. I wonder why/how it managed to tell the author everything was perfect? A weird one-off occurrence?

deleted 2y ago

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theodric 2y ago

> "From her perspective, I order doordash and turn into a degen who is unfit to father. From my perspective, I get to enjoy my favorite place and just tinker or play games or do whatever. These are the days I get to play mad scientist and feel most like myself." Most demeaning and depressingly toxic thing I've read today...

neilv 2y ago

> TLDR - AI isn’t a co-pilot; it’s a junior dev faking competence. Trust it at your own risk. A junior dev faking competence while plagiarizing like crazy. The plagiarizing part is why the junior dev from hell might not get fired: laundering open source copyrights can have beancounter alignment.

65 2y ago

I have never found a use for LLMs for programming because I can find the (correct) answer much easier with a search. Perhaps the search engines just suck so hard these days people resort to LLMs. I use Kagi and GitHub to search and the results are much better.

turnsout 2y ago

Counterpoint: I'm on day 26 of an afternoon project I never would have attempted on my own, and I'm going to release it as a major feature. Cursor & Claude got the boilerplate set up, which was half the mental barrier. Then they acted as thought partners as I tried out various implementations. In the end, I came up with the algorithm to make the thing performant, and now I'm hand-coding all the shader code—but they helped me think through what needed to be done. My take is: LLMs are best at helping you code at the edge of your capabilities, where you still have enough knowledge to know when they're going wrong. But they'll help you push that edge forward.

lbotos 2y ago

Nemo, are you using a self-hosted install or .com? If .com, email me (it's in my profile) and I can see if there is a reason your account is getting so heavily captcha'd.

adsharma 2y ago

A few mitigation ideas * Get AI to write tests * Use copy/paste. No IDE * Use python (not because it's better than zig)

tashian 2y ago

I used Claude to help me build a side project in 4 hours that I would never have built otherwise. Essentially, it's a morphing wavetable oscillator in React (https://waves.tashian.com https://waves.tashian.com). Six months ago, I tried building this app with ChatGPT and got nowhere fast. Building it with Claude required a gluing together a few things that I didn't know much about: JavaScript audio processing, drawing on a JavaScript canvas, an algorithm for bilinear interpolation. I don't write JavaScript often. But I know how to program and I understand what I'm looking at. The project came together easily and the creative momentum of it felt great to me. The most amazing moment was when I reported a bug—I told Claude that the audio was stuttering whenever I moved the controls—and it figured out that we needed to use an AudioWorklet thread instead of trying to play the audio directly from the React component. I had never even heard of AudioWorklet. Claude refactored my code to use the AudioWorklet, and the stutter disappeared. I wouldn't have built this without Claude, because I didn't need it to exist that badly. Claude reduced the creative inertia just enough for me to get it done.

masklinn 2y ago
What was your workflow for doing that? Just going back and forth in a chat, or a more integrated experience in a dedicated editor?
- tashian 2y ago
  Just copy/paste from the chat window. I kept running into token limits. I came away from it wanting a much better workflow. That's the next step for me in learning AI... playing with different integrated editor tools.

Havoc 2y ago

That’s a fun writeup. I’ve come to a similar conclusion - for now at least it’s best applied at a fairly granular level. Make me a red brick wall there rather than „hey architect make me a house“. I do think OP tried a bit too much new stuff in one go though. USB plus zig is quite a bit more ambitious than the traditional hello world in a new lang

qiqitori 2y ago

Your plan was to use USB, but to me it looks like you're pretty much just using serial via USB. That's completely fine of course! One cheap way to tackle your problem is to use a version of printf with locking, which is likely available in many microcontroller SDKs (it's also slow). (Or you could add your own mutex.) USB-CDC is cooler than that, you can make the Pico identify as more than just one device. E.g. https://github.com/Noltari/pico-uart-bridge https://github.com/Noltari/pico-uart-bridge identifies as two devices (so you get /dev/ttyACM0 and /dev/ttyACM1). So you could have logs on one and image transfers on another. I don't think you're limited to just two, but I haven't looked into it too far. You can of course also use other USB protocols. For example you could have the Pico present itself as a mass-storage device or a USB camera, etc. You're just limited by the relatively slow speed of USB1.1. (Though the Pico doesn't exactly have a lot of memory so even USB1.1 will saturate all your RAM in less than 1 second)

medhir 2y ago

Perhaps being a PM for several years has helped, I’ve had great success speeding up my programming workflows by prompting Claude with very specific, well defined tasks. Like many others are saying, you need to be in the drivers seat and in control. The LLM is not going to fully complete your objectives for you, but it will speed you up when provided with enough context, especially on mundane boilerplate tasks. I think the key to LLMs being useful is knowing how to prompt with enough context to get a useful output, and knowing what context is not important so the output doesn’t lead you in the wrong direction.

Graziano_M 2y ago

OP could have written the firmware in zig, too! https://github.com/ZigEmbeddedGroup/microzig https://github.com/ZigEmbeddedGroup/microzig

ffitch 2y ago

for what it’s worth, my afternoon projects tend to take over four days even if no llm is involved

raleighm 2y ago
Laughed aloud at this one. Yup, same here.

superq 2y ago

Most LLMs default to being sycophantic yes-men, but if you create a custom prompt, it can help mitigate any issues. I have a custom prompt that instructs gpt4o to get aggressive about attacking anything I say (and, importantly, anything it says). Here's my result for the same question: https://chatgpt.com/share/67984aa9-1608-8012-be93-a77728ab8e50 https://chatgpt.com/share/67984aa9-1608-8012-be93-a77728ab8e...

cudgy 2y ago

Really enjoyed reading your article. Haven’t laughed as much reading a tech article in quite some time. You should consider doing some YouTube videos as your communications style is very humble and entertaining. Made me wanna join in your garage and help out with the project :)

j45 2y ago

I doubt one experience, positive, or negative counts for them all. Learning how to build or create with a new kind of word processor is a skill unto itself.

petarb 2y ago

> My wife and I have a deal where 1 day a month, She takes the kiddo and I am absolved of all responsibilities. I get a full day to lock in and build projects. I love it!

djray 2y ago

The OP misunderstands (perhaps deliberately or for humorous effect) what a co-pilot is. This is telling: "I learned that I need to stay firmly in the driver’s seat when tackling new tech." Er, that's pretty much what a pilot is supposed to do! You can't (as yet) just give an AI free reign over your codebase and expect to come back later that day to discover a fully finished implementation. Maybe unless your prompt was "Make a snake game in Python". A pilot would be supervising their co-pilot at all times. Comparing AIs to junior devs is getting tiresome. AIs like Claude and newer versions of ChatGPT have incredible knowledge bases. Yes, they do slip up, especially with esoteric matters where there are few authoritative (or several conflicting) sources, but the breadth of knowledge in and of itself is very valuable. As an anecdote, neither Claude nor ChatGPT were able to accurately answer a question I had about file operation flags yesterday, but when I said to ChatGPT that its answer wasn't correct, it apologised and said the Raymond Chen article it had sourced wasn't super clear about the particular combination I'd asked about. That's like having your own research assistant, not a headstrong overconfident junior dev. Yes, they make mistakes, but at least now they'll admit to them. This is a long way from a year or two ago. In conclusion: don't use an AI as one of your primary sources of information for technology you're new to, especially if you're not double-checking its answers like a good pilot.

sarob 2y ago

You are running the show and the LLM can act like many other roles to help you. Obscure or confusing topics, likely the LLM will be as bad at solving as any employee. Give it a plan. Follow up and make sure it’s on track.

jmt710 2y ago

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