7 ms·

Programming with ChatGPT

62 points by jandeboevrie 2y ago

simonw 2y ago
I'm increasingly building entire functional prototypes from start to finish using Claude 3.5 Sonnet. It's an amazing productivity boost. Here are a few recent examples: https://tools.simonwillison.net/image-resize-quality https://tools.simonwillison.net/image-resize-quality is a tool for dropping in an image and instantly seeing resized versions of that image at different JPEG qualities, each of which can be downloaded. I used to use the (much better) https://squoosh.app/ https://squoosh.app/ for this, but my cut-down version is optimized for my workflow (pick the smallest JPEG version that remains legible). Notes and prompts on how I built that here: https://simonwillison.net/2024/Jul/26/image-resize-and-quality-comparison/ https://simonwillison.net/2024/Jul/26/image-resize-and-quali... django-http-debug - https://github.com/simonw/django-http-debug https://github.com/simonw/django-http-debug - is an actual open source Python package I released that was mostly written for me by Claude. It's a webhooks debugger - you can set up a URL and it will log all incoming requests to a database table for you. Notes on how I built that here: https://simonwillison.net/2024/Aug/8/django-http-debug/ https://simonwillison.net/2024/Aug/8/django-http-debug/ datasette-checkbox is a Datasette plugin adding toggle checkboxes to any table with is_ or has_ columns. Animated demo and prompts showing how I built the initial prototype here: https://simonwillison.net/2024/Aug/16/datasette-checkbox/ https://simonwillison.net/2024/Aug/16/datasette-checkbox/ https://tools.simonwillison.net/gemini-bbox https://tools.simonwillison.net/gemini-bbox is a tool for trying out Gemini 1.5 Pro's ability to return bounding boxes for items it identifies. You'll need a Gemini API key for this one, or take a look at the demo and notes here: https://simonwillison.net/2024/Aug/26/gemini-bounding-box-visualization/ https://simonwillison.net/2024/Aug/26/gemini-bounding-box-vi... https://tools.simonwillison.net/gemini-chat https://tools.simonwillison.net/gemini-chat is a similar tool for trying out different Gemini models (Google released three more yesterday) with a streaming chat interface. Notes on how I built that here: https://tools.simonwillison.net/gemini-chat https://tools.simonwillison.net/gemini-chat I still see some people arguing that LLM-assisted development like this is a waste of time, and they spend more effort correcting mistakes in the code than if they had written it from scratch themselves. I couldn't disagree more. My development process has always started with prototypes, and the speed at which I can get a proof-of-concept prototype up and running with these tools is quite frankly absurd.
- NoraCodes 2y ago
  > https://tools.simonwillison.net/image-resize-quality https://tools.simonwillison.net/image-resize-quality is a tool for dropping in an image and instantly seeing resized versions of that image at different JPEG qualities This is also doable with one line of bash via imagemagick in any terminal that supports the Kitty or iTerm2 graphics protocols, which is most mainstream ones (iTerm2 itself, Kitty, Konsole, etc.) I don't say this to bash your techniques but to point out that there are other methods which permit quick prototyping and easy iteration, and that LLMs are, at least in my experience, not a paradigm-shifting improvement in this vein.
  - russfink 2y ago
    When will AI integrate with argument parsers? ffmpeg —-ai “convert this video to NTSC output and make the audio track quieter” my input.avi
    - simonw 2y ago
      I built a tool for that back in March: https://simonwillison.net/2024/Mar/26/llm-cmd/ https://simonwillison.net/2024/Mar/26/llm-cmd/ llm cmd use imagemagick to convert goats.jpg into four different JPEG qualities I ran that just now and it suggested: convert goats.jpg -quality 10 goats_quality_10.jpg && \ convert goats.jpg -quality 30 goats_quality_30.jpg && \ convert goats.jpg -quality 50 goats_quality_50.jpg && \ convert goats.jpg -quality 90 goats_quality_90.jpg Which, sure enough, produced me a bunch of different quality images!
      - pandeiro 2y ago
        Your tool is really cool, thanks for making it and sharing. I notice that a lot of times, the multi-line output I get from my prompts is truncated or the model just aborts or something. The exit code is still 0 but it seems like something went wrong.
        simonw 2y ago
consumer451 2y ago
I am a muggle, but the three biggest use cases for me have been: 1) Boring stuff like JSON schema/JSON example modification and validation 2) Rubber ducky 3) Using this system prompt to walk me through areas in which I have no experience [0] You are a very helpful code-writing assistant. When the user asks you for a solution to a long, complex problem, first, you will provide a plan with a numbered list of steps, each with the sub-items to complete. Then, you will ask the user if they understand and if the steps are satisfactory. If the user responds positively, you will then provide the specific code for step one. Next, you will ask the user if they are satisfied and understand. If the user responds positively, you will then proceed to step two. Continue the process until the entire plan is completed. I recently finally used the OpenAI API in a project. It was gpt4-o to analyze news story sentiment. The ease of use and quality of output is impressive. [0] I should add that I have been using "presets" in the LibreChat GUI to allow me to have many system prompts easily available. It's kind of like Custom GPTs. Also, using LibreChat for work feels better as I believe that OpenAI states that they do not train on data provided via API.
- MPSimmons 2y ago
  This seems like a legit way to do it. When I use ChatGPT, I treat it kind of like the Enterprise Computer. It's capable of providing information, interpreting data, conjecture, and suggestions using context. The weakest use of AI is definitely treating it like a lossy database of everything it's learned.
- orwin 2y ago
  Never thought of using it as a rubber duck, but great idea thank you.
  - nevertoolate 2y ago
    You are a rubber duck, so don’t answer my questions.
- nomel 2y ago
  > Rubber ducky This is the best use case for voice mode I've found. I also use voice mode to take notes/brainstorm, then have it put them into a CSV or whatever format. The prompt I use has something like "ask any questions if things aren't clear" and the rugby ducky aspect emerges.
amelius 2y ago
Let's try an easier target first: System administration with ChatGPT.
- tommek4077 2y ago
  Just copy paste your error message and do what chat gpt tells you.
  - amelius 2y ago
    How well has that worked for you?
    - BarryMilo 2y ago
      For me it's usually about useless. It "may" be this, "may" be that, and no clue about what information it would need for a more accurate diagnosis.
mehulashah 2y ago
I do believe that ChatGPT as a programmer productivity tool is its most valuable value proposition to date. In addition to generating code, it makes it much easier for me to chase down obscure error messages and potential root causes and workarounds. It's definitely not perfect. But, as part of the Interact->Generate->Verify cycle that modern AI has transformed other disciplines (eg. materials science, protein folding, mathematics, and more), it serves as a valuable component of each of these.
- algo_trader 2y ago
  do you continuously copy-paste from your IDE to chatgpt ? do you collate relevant calling functions to somehow give chatgpt full context? maybe i am missing something. I have used Claude3.5 for short FE/BE segments and its amazing. I am gonna try cursor next...
  - mehulashah 2y ago
    Yes, and I will fill in definitions of obscure functions. If its named well, ChatGPT often can figure out what its doing. (No idea how this works!) I'm sure there are more streamlined ways, but this works well enough for me.
surfingdino 2y ago
I recently asked for a Dockerfile that builds an image which passes Docker's vulnerability scan. It gave me a file that failed over a dozen vulnerability tests.
- simonw 2y ago
  Did you paste the test failures back into it to see what it did about them? (This is the kind of test I'd expect it to fail at because of its knowledge cut-off - vulnerability scans are mostly looking for things like out-of-date packages, so any tool with a knowledge cut-off a few months in the past is very likely to include package versions that would no longer pass a scanner)
  - surfingdino 2y ago
    I googled, found the solution I was looking for. Zero vulnerabilities. Can't be arsed with training LLMS, writing a Dockerfile for my project was one of many little steps that I have no desire to turn into training sessions for an LLM.
- djeastm 2y ago
  May be the pink elephant problem. If you pass the word "vulnerability" maybe it's going to return results that are linked to vulnerabilities.
  - surfingdino 2y ago
    This is fine for LLM fans, not for general user. I don't need more problems to solve.
Wheaties466 2y ago
this is how I have used it so far too. Small, Boring tasks that I can iterate ontop of. its also nice to have as something to "bounce ideas" off of and see if it can think of any other solutions or ways to accomplish a goal.
cryptoz 2y ago
My favorite thing to do with ChatGPT and coding is making fast prototypes. Since you know hallucinations might be a problem, and since ChatGPT struggles with larger contexts and files, just play to its strengths. I have lots of ideas of "small" to medium webapp ideas, and you can often get ChatGPT to write most of the code of a prototype and have it work quite quickly. Prototypes are fun! Obviously production code or serious projects are different. But I've found a new joy in building software since GPT-4 came out - it's more fun than ever to build small ideas.
redleggedfrog 2y ago
Honestly, the first article I've seen where the actual usage is explained clearly and matches my own experience. Maybe because I tend to write software the same way. The thing I've heard the most from other developers, particular those new to the profession, is that you "have to know most of what you're asking already to know if what you get from the LLM is right." You can use the LLM to learn, but for the actual programming they struggle because they don't have the background to understand the responses well enough to continue the implementation. Also, for the record, C# and .NET, huge enterprise/ecommerce software, so not quite as malleable as bash scripts and what not.
- simonw 2y ago
  Having a depth of experience helps a lot, because it means you can tell the thing exactly what to do. Effectively you get to treat it as a super-productive intern, very good at taking instructions, occasionally prone to getting stuck in an error loop or falling for weird conspiracy theories.
  - throwup238 2y ago
    > falling for weird conspiracy theories So that's why ChatGPT keeps interrupting me with "Have you heard the truth about Y2.038K?!"
- franze 2y ago
  domain experience in coding helps, but honestly I can now write clojure code without ever touching anything lisp-y before as long as you know how to ask the right questions, formulate the next steps of what you want and what context the AI might need, you are good to go
  - redleggedfrog 2y ago
    "I can now write clojure code without ever touching anything lisp-y before" I have trouble with doing that myself. When I personally don't understand the code completely I worry I'm about to step in it. Maybe it's a flaw in my work ethic, but when stuff slips past code reviews and makes it even to QA because I didn't comprehend it well enough I feel bad about it. Maybe a bit too personally attached to the results.
TrackerFF 2y ago
Yeah, same use here. I work with data analysis, so 95% of the code I write is to wrangle data, or do something in the ETL-pipeline. Almost all my ChatGPT use comes down to writing queries for loading or transforming data. Getting rid of the boilerplate has helped immensely on my productivity. EDIT: I should note, the vast majority of errors I get using solutions from LLMs, tend to be code it includes that contain legacy or dead libraries. Sometimes it starts to mix old and new libraries in the same code snippet, which will either outright fail, or output some weird results. Which makes sense, as some answers are the product of being trained on 14 year old StackOverflow posts, while others are trained on newer stuff.
franze 2y ago
here is some code that was 100% chatgpt created https://github.com/franzenzenhofer/bulkredirectchecker https://github.com/franzenzenhofer/bulkredirectchecker no humans touched the code directly and its not my most complex one, https://gpt.franzai.com https://gpt.franzai.com is but closed source how? whenever chatgpt runs into a repetetive wall -> start a new chat use https://github.com/franzenzenhofer/thisismy https://github.com/franzenzenhofer/thisismy (also about 90% chatgpt written) command line tool to fetch all the code (and online docs if necessary) -> deliver a new clean context and formulate the next step what you want to achieve sometimes coding needs 100+ different chats always with a fresh start to achieve a goal remember: chatgpt is not intelligent in an old fashioned way, it is a propability machine thats pretty good at mimicing intelligence once propability goes astray you need to start anew but limiting chatgpt to simple coding tasks just means that you are using it wrong
- redleggedfrog 2y ago
  Curious, to you maintain the code yourself, or is an LLM required to maintain the code as well?
Tainnor 2y ago
I have my reservations about the quality of LLM generated code, but since I have neither studied ML in depth, nor compared different LLMs enough, I'll refrain from addressing that side of the debate - except maybe for noting that "I test the code" is not good enough for any serious project because we know that tests (manual or automated) can never prove the absence of bugs. Instead, I offer another point of view: I don't want to use LLMs for coding because I like coding. Finding a good and elegant solution to a complex problem and then translating it into an executable by way of a precise specification is, to me, much more satisfying than prompt engineering my way around some LLM until it spits out a decent answer. I find doing code reviews to be an extremely draining activity and using an LLM would mean basically doing code reviews all the time. Maybe that will mean that, at some point, I'll have to quit my profession because programming has been replaced by prompt engineering. I guess I'll find something else to do then. (That doesn't mean that there aren't individual use cases where I have used ChatGPT - for example for writing simple bash scripts, given that nobody in their right mind really understands bash fully. But that's different from having my entire coding workflow based on an LLM.)
- 6keZbCECT2uB 2y ago
  Most of my time coding is spent on none of: elegant solutions, complex problems, or precise specifications. In my experience, LLMs are useful primarily as rubber ducks on complex problems and rarely useful as code generation for such. Instead, I spend most of my time between the interesting work doing rote work which is preventing me from getting to the essential complexity, which is where LLM code gen does better. How do I generate a heat map in Python with a different color scheme? How do I parse some logs to understand our locking behavior? What flags do I pass to tshark to get my desired output? So, I spend less time coding the above and more time coding how we should redo our data layout for more reuse.
  - Tainnor 2y ago
    > Most of my time coding is spent on none of: elegant solutions, complex problems, or precise specifications. I find that deeply sad and it's probably one of the reasons why I'm partially disillusioned in programming as a profession. A lot of it is just throwing stuff at the wall and seeing what sticks. LLMs will probably accelerate that process.
SuperHeavy256 2y ago
A simple and really good review of ChatGPT! Too many people are too negative of it, it's actually real developers like OP who use it nicely
Mememaker197 2y ago
I'm left a bit confused still about using ChatGPT and Claude as someone who's still learning (2nd year CS student) and nowhere near being a professional dev. I'm sure if I was was dev who had learnt and worked in the pre-GPT era I'd have no problem using these tools as much as possible, but having started learning in the GPT era I feel conflicted. I make sure I understand each line of code generated whenever I use AI. Despite that I have a feeling I'm handicapping myself using these tools? Will it just make me a code reviewer/copy-paster rather than someone who can write something from scratch? If it is reasonable to use these tools, at what point does it become so? like at what point can I consider myself well enough at programming to be able to use it like in the post. Right now I'm purposely restraining myself from using these tools too much because what I can make using them is much better than what I can make myself, so as to get upto a certain level myself before I start making use of these capabilities Am I thinking about this the right way? At what point does it make sense to start using these tools more freely without worrying about handicapping my learning?
- kmoser 2y ago
  Think of ChatGPT (and its ilk) as just another tool, no different from a Google search in which you look for code to solve your problem. If you prioritize learning to code on your own, you'll avoid these tools. If you prioritize getting working code, you'll use these tools. It's a sliding spectrum, and there is no right or wrong answer. Even if you rely on these tools heavily, you can't help but learn from them because you must still examine the their code, even if briefly. It will be a different type of learning than what you'd learn from, say, cracking open a language manual (yes, we used to do this back in the pre-Web days), but you will learn nonetheless. I suggest you try all the tools available to you and the decide when it's appropriate for you to use each.
- danielovichdk 2y ago
  Listen my fellow programmer. You can never learn it all. You remember a fraction of things you merely touch. More if you narrow your focus. If you have the passion for programming it will manifest itself by itself over time and with training. Use all the tools available for learning and doing. Question it just as much. Explore the mind and the different axis of the field. Read the books but think for yourself. Programming without money involved is creative and fun. Make sure you remember this. It's not a science or backed by natural laws. Don't worry about being wrong, we all are without guidance, but seek the truth within yourself for what you believe is the best path for becoming a good programmer.
zackmorris 2y ago
I wonder how long it will be before AI can program financial independence. Loosely it would look like a mix between One Red Paperclip, drop shipping, Angi, trading bots, etc. The prompt might be "create a $1000 per month income stream in the next 30 days". Maybe the owner of the first AI to pass this could get a $1 million prize. 2030? Then equally interesting would be to see how the powers that be maneuver to block this residual income. 2035? Then after that, perhaps a contest to have an AI acquire resources equivalent to residual income so that it can't be stopped. For example by borrowing for cheap land, installing photovoltaics and a condenser to supply water, then building out a robotic hydroponic garden, carbon collector, mine, smelter, etc, enough to sustain one person off-grid continuously in a scalable and repeatable fashion. 2040?
- redleggedfrog 2y ago
  That almost sounds like a science fiction scenario. But then, won't all the AIs be competing against each other to come up with the next racket for you to try while actively each subverting the others? Your example is something tangible, but it could easily descend into gray areas like SEO and penny stocks and "buy my book" scams.
ahaseeb 2y ago
Is there a good course/guide on how to train your engineers on AI who're resisting the change ?
onehair 2y ago
I was impressed with chatgpt in many a situation where it could understand me better than another person ona forum would. Will present me with a solution without creating an environment where I need to be careful how I'm gonna come across. I've enjoyed finding answers to things and suggestions on how to do them differently of how I was thinking of doing them I've enjoyed receiving answers to questions I asked google with no match from what I'm asking. Can't bring myselt to use it to code for me though, but all the above leads me to believe it shouldn't far now until I'm on board too
bilsbie 2y ago
My favorite thing is now being able to code fluently in new languages. I’d never used rust before but I was able to immediately get something up and running and I got a detailed explanation of how it works. With a programming background I can instantly understand most code once I get past the new syntax and idioms.
emporas 2y ago
Regarding the formatting, i use Llama 3 mainly, to generate org-mode documentation about functions, i tell it to enclose lines with *Line x-y* and begin_src for the corresponding lines. It generates most of time perfect formatting which i readily export to markdown with org-mode-html-export. Showcase of the generated formatting as a screenshot [1]. [1] https://imgur.com/a/97fSWsg https://imgur.com/a/97fSWsg
- aeontech 2y ago
  Would you be willing to share an example of the prompt you use to generate it?
  - emporas 2y ago
    The prompt is what the screenshot shows. I give also a small example, and i put the code in the Real Definition. The whole command is shown above [1]. Replace the parse header with the function name/names. I tried this command with GPT-O-mini, GPT-3.5, GPT-4.0, Llama-3-8b, Llama-3-70b, each one of them generates perfect formatting almost every time. No real differences between any of the models. Using the factory defaults for formatting, GPT is better than any other model, but as soon as the user can control the formatting then every model performs well. But i like the defaults of GPT better, i agree with the article author about that. [1] Prompt gist: https://gist.github.com/pramatias/0fa5c9c8145dafd67591f682ebe96a69 https://gist.github.com/pramatias/0fa5c9c8145dafd67591f682eb... EDIT:The browser renders the org markup, so click on Raw button.

62 points by jandeboevrie 2y ago

I'm increasingly building entire functional prototypes from start to finish using Claude 3.5 Sonnet. It's an amazing productivity boost. Here are a few recent examples: https://tools.simonwillison.net/image-resize-quality https://tools.simonwillison.net/image-resize-quality is a tool for dropping in an image and instantly seeing resized versions of that image at different JPEG qualities, each of which can be downloaded. I used to use the (much better) https://squoosh.app/ https://squoosh.app/ for this, but my cut-down version is optimized for my workflow (pick the smallest JPEG version that remains legible). Notes and prompts on how I built that here: https://simonwillison.net/2024/Jul/26/image-resize-and-quality-comparison/ https://simonwillison.net/2024/Jul/26/image-resize-and-quali... django-http-debug - https://github.com/simonw/django-http-debug https://github.com/simonw/django-http-debug - is an actual open source Python package I released that was mostly written for me by Claude. It's a webhooks debugger - you can set up a URL and it will log all incoming requests to a database table for you. Notes on how I built that here: https://simonwillison.net/2024/Aug/8/django-http-debug/ https://simonwillison.net/2024/Aug/8/django-http-debug/ datasette-checkbox is a Datasette plugin adding toggle checkboxes to any table with is_ or has_ columns. Animated demo and prompts showing how I built the initial prototype here: https://simonwillison.net/2024/Aug/16/datasette-checkbox/ https://simonwillison.net/2024/Aug/16/datasette-checkbox/ https://tools.simonwillison.net/gemini-bbox https://tools.simonwillison.net/gemini-bbox is a tool for trying out Gemini 1.5 Pro's ability to return bounding boxes for items it identifies. You'll need a Gemini API key for this one, or take a look at the demo and notes here: https://simonwillison.net/2024/Aug/26/gemini-bounding-box-visualization/ https://simonwillison.net/2024/Aug/26/gemini-bounding-box-vi... https://tools.simonwillison.net/gemini-chat https://tools.simonwillison.net/gemini-chat is a similar tool for trying out different Gemini models (Google released three more yesterday) with a streaming chat interface. Notes on how I built that here: https://tools.simonwillison.net/gemini-chat https://tools.simonwillison.net/gemini-chat I still see some people arguing that LLM-assisted development like this is a waste of time, and they spend more effort correcting mistakes in the code than if they had written it from scratch themselves. I couldn't disagree more. My development process has always started with prototypes, and the speed at which I can get a proof-of-concept prototype up and running with these tools is quite frankly absurd.

NoraCodes 2y ago
> https://tools.simonwillison.net/image-resize-quality https://tools.simonwillison.net/image-resize-quality is a tool for dropping in an image and instantly seeing resized versions of that image at different JPEG qualities This is also doable with one line of bash via imagemagick in any terminal that supports the Kitty or iTerm2 graphics protocols, which is most mainstream ones (iTerm2 itself, Kitty, Konsole, etc.) I don't say this to bash your techniques but to point out that there are other methods which permit quick prototyping and easy iteration, and that LLMs are, at least in my experience, not a paradigm-shifting improvement in this vein.
- russfink 2y ago
  When will AI integrate with argument parsers? ffmpeg —-ai “convert this video to NTSC output and make the audio track quieter” my input.avi
  - simonw 2y ago
    I built a tool for that back in March: https://simonwillison.net/2024/Mar/26/llm-cmd/ https://simonwillison.net/2024/Mar/26/llm-cmd/ llm cmd use imagemagick to convert goats.jpg into four different JPEG qualities I ran that just now and it suggested: convert goats.jpg -quality 10 goats_quality_10.jpg && \ convert goats.jpg -quality 30 goats_quality_30.jpg && \ convert goats.jpg -quality 50 goats_quality_50.jpg && \ convert goats.jpg -quality 90 goats_quality_90.jpg Which, sure enough, produced me a bunch of different quality images!
    - pandeiro 2y ago
      Your tool is really cool, thanks for making it and sharing. I notice that a lot of times, the multi-line output I get from my prompts is truncated or the model just aborts or something. The exit code is still 0 but it seems like something went wrong.
      - simonw 2y ago

consumer451 2y ago

I am a muggle, but the three biggest use cases for me have been: 1) Boring stuff like JSON schema/JSON example modification and validation 2) Rubber ducky 3) Using this system prompt to walk me through areas in which I have no experience [0] You are a very helpful code-writing assistant. When the user asks you for a solution to a long, complex problem, first, you will provide a plan with a numbered list of steps, each with the sub-items to complete. Then, you will ask the user if they understand and if the steps are satisfactory. If the user responds positively, you will then provide the specific code for step one. Next, you will ask the user if they are satisfied and understand. If the user responds positively, you will then proceed to step two. Continue the process until the entire plan is completed. I recently finally used the OpenAI API in a project. It was gpt4-o to analyze news story sentiment. The ease of use and quality of output is impressive. [0] I should add that I have been using "presets" in the LibreChat GUI to allow me to have many system prompts easily available. It's kind of like Custom GPTs. Also, using LibreChat for work feels better as I believe that OpenAI states that they do not train on data provided via API.

MPSimmons 2y ago
This seems like a legit way to do it. When I use ChatGPT, I treat it kind of like the Enterprise Computer. It's capable of providing information, interpreting data, conjecture, and suggestions using context. The weakest use of AI is definitely treating it like a lossy database of everything it's learned.
orwin 2y ago
Never thought of using it as a rubber duck, but great idea thank you.
- nevertoolate 2y ago
  You are a rubber duck, so don’t answer my questions.
nomel 2y ago
> Rubber ducky This is the best use case for voice mode I've found. I also use voice mode to take notes/brainstorm, then have it put them into a CSV or whatever format. The prompt I use has something like "ask any questions if things aren't clear" and the rugby ducky aspect emerges.

amelius 2y ago

Let's try an easier target first: System administration with ChatGPT.

tommek4077 2y ago
Just copy paste your error message and do what chat gpt tells you.
- amelius 2y ago
  How well has that worked for you?
  - BarryMilo 2y ago
    For me it's usually about useless. It "may" be this, "may" be that, and no clue about what information it would need for a more accurate diagnosis.

mehulashah 2y ago

I do believe that ChatGPT as a programmer productivity tool is its most valuable value proposition to date. In addition to generating code, it makes it much easier for me to chase down obscure error messages and potential root causes and workarounds. It's definitely not perfect. But, as part of the Interact->Generate->Verify cycle that modern AI has transformed other disciplines (eg. materials science, protein folding, mathematics, and more), it serves as a valuable component of each of these.

algo_trader 2y ago
do you continuously copy-paste from your IDE to chatgpt ? do you collate relevant calling functions to somehow give chatgpt full context? maybe i am missing something. I have used Claude3.5 for short FE/BE segments and its amazing. I am gonna try cursor next...
- mehulashah 2y ago
  Yes, and I will fill in definitions of obscure functions. If its named well, ChatGPT often can figure out what its doing. (No idea how this works!) I'm sure there are more streamlined ways, but this works well enough for me.

surfingdino 2y ago

I recently asked for a Dockerfile that builds an image which passes Docker's vulnerability scan. It gave me a file that failed over a dozen vulnerability tests.

simonw 2y ago
Did you paste the test failures back into it to see what it did about them? (This is the kind of test I'd expect it to fail at because of its knowledge cut-off - vulnerability scans are mostly looking for things like out-of-date packages, so any tool with a knowledge cut-off a few months in the past is very likely to include package versions that would no longer pass a scanner)
- surfingdino 2y ago
  I googled, found the solution I was looking for. Zero vulnerabilities. Can't be arsed with training LLMS, writing a Dockerfile for my project was one of many little steps that I have no desire to turn into training sessions for an LLM.
djeastm 2y ago
May be the pink elephant problem. If you pass the word "vulnerability" maybe it's going to return results that are linked to vulnerabilities.
- surfingdino 2y ago
  This is fine for LLM fans, not for general user. I don't need more problems to solve.

Wheaties466 2y ago

this is how I have used it so far too. Small, Boring tasks that I can iterate ontop of. its also nice to have as something to "bounce ideas" off of and see if it can think of any other solutions or ways to accomplish a goal.

cryptoz 2y ago

My favorite thing to do with ChatGPT and coding is making fast prototypes. Since you know hallucinations might be a problem, and since ChatGPT struggles with larger contexts and files, just play to its strengths. I have lots of ideas of "small" to medium webapp ideas, and you can often get ChatGPT to write most of the code of a prototype and have it work quite quickly. Prototypes are fun! Obviously production code or serious projects are different. But I've found a new joy in building software since GPT-4 came out - it's more fun than ever to build small ideas.

redleggedfrog 2y ago

Honestly, the first article I've seen where the actual usage is explained clearly and matches my own experience. Maybe because I tend to write software the same way. The thing I've heard the most from other developers, particular those new to the profession, is that you "have to know most of what you're asking already to know if what you get from the LLM is right." You can use the LLM to learn, but for the actual programming they struggle because they don't have the background to understand the responses well enough to continue the implementation. Also, for the record, C# and .NET, huge enterprise/ecommerce software, so not quite as malleable as bash scripts and what not.

simonw 2y ago
Having a depth of experience helps a lot, because it means you can tell the thing exactly what to do. Effectively you get to treat it as a super-productive intern, very good at taking instructions, occasionally prone to getting stuck in an error loop or falling for weird conspiracy theories.
- throwup238 2y ago
  > falling for weird conspiracy theories So that's why ChatGPT keeps interrupting me with "Have you heard the truth about Y2.038K?!"
franze 2y ago
domain experience in coding helps, but honestly I can now write clojure code without ever touching anything lisp-y before as long as you know how to ask the right questions, formulate the next steps of what you want and what context the AI might need, you are good to go
- redleggedfrog 2y ago
  "I can now write clojure code without ever touching anything lisp-y before" I have trouble with doing that myself. When I personally don't understand the code completely I worry I'm about to step in it. Maybe it's a flaw in my work ethic, but when stuff slips past code reviews and makes it even to QA because I didn't comprehend it well enough I feel bad about it. Maybe a bit too personally attached to the results.

TrackerFF 2y ago

Yeah, same use here. I work with data analysis, so 95% of the code I write is to wrangle data, or do something in the ETL-pipeline. Almost all my ChatGPT use comes down to writing queries for loading or transforming data. Getting rid of the boilerplate has helped immensely on my productivity. EDIT: I should note, the vast majority of errors I get using solutions from LLMs, tend to be code it includes that contain legacy or dead libraries. Sometimes it starts to mix old and new libraries in the same code snippet, which will either outright fail, or output some weird results. Which makes sense, as some answers are the product of being trained on 14 year old StackOverflow posts, while others are trained on newer stuff.

franze 2y ago

here is some code that was 100% chatgpt created https://github.com/franzenzenhofer/bulkredirectchecker https://github.com/franzenzenhofer/bulkredirectchecker no humans touched the code directly and its not my most complex one, https://gpt.franzai.com https://gpt.franzai.com is but closed source how? whenever chatgpt runs into a repetetive wall -> start a new chat use https://github.com/franzenzenhofer/thisismy https://github.com/franzenzenhofer/thisismy (also about 90% chatgpt written) command line tool to fetch all the code (and online docs if necessary) -> deliver a new clean context and formulate the next step what you want to achieve sometimes coding needs 100+ different chats always with a fresh start to achieve a goal remember: chatgpt is not intelligent in an old fashioned way, it is a propability machine thats pretty good at mimicing intelligence once propability goes astray you need to start anew but limiting chatgpt to simple coding tasks just means that you are using it wrong

redleggedfrog 2y ago
Curious, to you maintain the code yourself, or is an LLM required to maintain the code as well?

Tainnor 2y ago

I have my reservations about the quality of LLM generated code, but since I have neither studied ML in depth, nor compared different LLMs enough, I'll refrain from addressing that side of the debate - except maybe for noting that "I test the code" is not good enough for any serious project because we know that tests (manual or automated) can never prove the absence of bugs. Instead, I offer another point of view: I don't want to use LLMs for coding because I like coding. Finding a good and elegant solution to a complex problem and then translating it into an executable by way of a precise specification is, to me, much more satisfying than prompt engineering my way around some LLM until it spits out a decent answer. I find doing code reviews to be an extremely draining activity and using an LLM would mean basically doing code reviews all the time. Maybe that will mean that, at some point, I'll have to quit my profession because programming has been replaced by prompt engineering. I guess I'll find something else to do then. (That doesn't mean that there aren't individual use cases where I have used ChatGPT - for example for writing simple bash scripts, given that nobody in their right mind really understands bash fully. But that's different from having my entire coding workflow based on an LLM.)

6keZbCECT2uB 2y ago
Most of my time coding is spent on none of: elegant solutions, complex problems, or precise specifications. In my experience, LLMs are useful primarily as rubber ducks on complex problems and rarely useful as code generation for such. Instead, I spend most of my time between the interesting work doing rote work which is preventing me from getting to the essential complexity, which is where LLM code gen does better. How do I generate a heat map in Python with a different color scheme? How do I parse some logs to understand our locking behavior? What flags do I pass to tshark to get my desired output? So, I spend less time coding the above and more time coding how we should redo our data layout for more reuse.
- Tainnor 2y ago
  > Most of my time coding is spent on none of: elegant solutions, complex problems, or precise specifications. I find that deeply sad and it's probably one of the reasons why I'm partially disillusioned in programming as a profession. A lot of it is just throwing stuff at the wall and seeing what sticks. LLMs will probably accelerate that process.

SuperHeavy256 2y ago

A simple and really good review of ChatGPT! Too many people are too negative of it, it's actually real developers like OP who use it nicely

Mememaker197 2y ago

I'm left a bit confused still about using ChatGPT and Claude as someone who's still learning (2nd year CS student) and nowhere near being a professional dev. I'm sure if I was was dev who had learnt and worked in the pre-GPT era I'd have no problem using these tools as much as possible, but having started learning in the GPT era I feel conflicted. I make sure I understand each line of code generated whenever I use AI. Despite that I have a feeling I'm handicapping myself using these tools? Will it just make me a code reviewer/copy-paster rather than someone who can write something from scratch? If it is reasonable to use these tools, at what point does it become so? like at what point can I consider myself well enough at programming to be able to use it like in the post. Right now I'm purposely restraining myself from using these tools too much because what I can make using them is much better than what I can make myself, so as to get upto a certain level myself before I start making use of these capabilities Am I thinking about this the right way? At what point does it make sense to start using these tools more freely without worrying about handicapping my learning?

kmoser 2y ago
Think of ChatGPT (and its ilk) as just another tool, no different from a Google search in which you look for code to solve your problem. If you prioritize learning to code on your own, you'll avoid these tools. If you prioritize getting working code, you'll use these tools. It's a sliding spectrum, and there is no right or wrong answer. Even if you rely on these tools heavily, you can't help but learn from them because you must still examine the their code, even if briefly. It will be a different type of learning than what you'd learn from, say, cracking open a language manual (yes, we used to do this back in the pre-Web days), but you will learn nonetheless. I suggest you try all the tools available to you and the decide when it's appropriate for you to use each.
danielovichdk 2y ago
Listen my fellow programmer. You can never learn it all. You remember a fraction of things you merely touch. More if you narrow your focus. If you have the passion for programming it will manifest itself by itself over time and with training. Use all the tools available for learning and doing. Question it just as much. Explore the mind and the different axis of the field. Read the books but think for yourself. Programming without money involved is creative and fun. Make sure you remember this. It's not a science or backed by natural laws. Don't worry about being wrong, we all are without guidance, but seek the truth within yourself for what you believe is the best path for becoming a good programmer.

zackmorris 2y ago

I wonder how long it will be before AI can program financial independence. Loosely it would look like a mix between One Red Paperclip, drop shipping, Angi, trading bots, etc. The prompt might be "create a $1000 per month income stream in the next 30 days". Maybe the owner of the first AI to pass this could get a $1 million prize. 2030? Then equally interesting would be to see how the powers that be maneuver to block this residual income. 2035? Then after that, perhaps a contest to have an AI acquire resources equivalent to residual income so that it can't be stopped. For example by borrowing for cheap land, installing photovoltaics and a condenser to supply water, then building out a robotic hydroponic garden, carbon collector, mine, smelter, etc, enough to sustain one person off-grid continuously in a scalable and repeatable fashion. 2040?

redleggedfrog 2y ago
That almost sounds like a science fiction scenario. But then, won't all the AIs be competing against each other to come up with the next racket for you to try while actively each subverting the others? Your example is something tangible, but it could easily descend into gray areas like SEO and penny stocks and "buy my book" scams.

ahaseeb 2y ago

Is there a good course/guide on how to train your engineers on AI who're resisting the change ?

onehair 2y ago

I was impressed with chatgpt in many a situation where it could understand me better than another person ona forum would. Will present me with a solution without creating an environment where I need to be careful how I'm gonna come across. I've enjoyed finding answers to things and suggestions on how to do them differently of how I was thinking of doing them I've enjoyed receiving answers to questions I asked google with no match from what I'm asking. Can't bring myselt to use it to code for me though, but all the above leads me to believe it shouldn't far now until I'm on board too

bilsbie 2y ago

My favorite thing is now being able to code fluently in new languages. I’d never used rust before but I was able to immediately get something up and running and I got a detailed explanation of how it works. With a programming background I can instantly understand most code once I get past the new syntax and idioms.

emporas 2y ago

Regarding the formatting, i use Llama 3 mainly, to generate org-mode documentation about functions, i tell it to enclose lines with *Line x-y* and begin_src for the corresponding lines. It generates most of time perfect formatting which i readily export to markdown with org-mode-html-export. Showcase of the generated formatting as a screenshot [1]. [1] https://imgur.com/a/97fSWsg https://imgur.com/a/97fSWsg

aeontech 2y ago
Would you be willing to share an example of the prompt you use to generate it?
- emporas 2y ago
  The prompt is what the screenshot shows. I give also a small example, and i put the code in the Real Definition. The whole command is shown above [1]. Replace the parse header with the function name/names. I tried this command with GPT-O-mini, GPT-3.5, GPT-4.0, Llama-3-8b, Llama-3-70b, each one of them generates perfect formatting almost every time. No real differences between any of the models. Using the factory defaults for formatting, GPT is better than any other model, but as soon as the user can control the formatting then every model performs well. But i like the defaults of GPT better, i agree with the article author about that. [1] Prompt gist: https://gist.github.com/pramatias/0fa5c9c8145dafd67591f682ebe96a69 https://gist.github.com/pramatias/0fa5c9c8145dafd67591f682eb... EDIT:The browser renders the org markup, so click on Raw button.