I’m a company of one, and I use it every day, multiple times a day as a coding assistant. I’m using the excellent Code Genie (sp?) plug-in to VSC which puts a chat window directly in VSC and does cool things like allow you to highlight blocks of code and ask contextual questions / refactors / bug checks, etc.
I would say my efficiency is up ~20% since starting to use it, and my Google searches & StackOverflow visits are probably down 80-90%. At least with respect to this corner of the internet, they are both in mortal danger.
Quick question: How does Code Genie get responses from the GPT API so quickly? I'm developing an app right now and it takes 40 seconds to query gpt-3.5-turbo.
Just curious how the data flow works. Are you sending information to both places, CGenie and OpenAI? Full disclosure, I have never used CGenie. I know you can turn off data collection at OpenAI, can you do the same with them?
The VSC extension is just a conduit to the OpenAI API. You use your own API key. I haven’t dug into the exact data flow, however, so I can’t speak to whether the extension is collecting any or what data itself.
I'm wearing a lot of hats at the moment since we're still in startup mode so the list is pretty varied:
- I ask it to create list of questions that different personas might want to answer with our reports section. I then ask it to categorize those questions & to then provide suggestions for graphs & dynamic filters that would help answer those questions.
- I ask it for help translating emails and documents for international customers.
- I ask it to create markdown, formatted spec documents with really verbose context. Helps me as sort of a foundation for feature sprint kickoffs.
- I ask it to take internal documentation and to simplify it so that we're able to use it for public facing help center documentation.
- I use it as my first resource for asking questions about SQL queries, React patterns, explaining different things eg SVG properties and how to manipulate them. I gut check things with Google when I feel like it might be hallucinating but generally it does really well ~ 90% of the time. Saves lots of time compared to going to Google first.
- I ask it for help writing tests or help refactoring code
- I asked it for help in creating some policy & procedures docs that we needed for compliance. Essentially gives you a decent template to then build from & customize.
- Lots of other things. It replaced Google for so many things in my daily workflow. It also helps a lot when you're not feeling creative and you need some ideas.
> I gut check things with Google when I feel like it might be hallucinating but generally it does really well ~ 90% of the time. Saves lots of time compared to going to Google first.
I was asking chatGPT give me boilerplate for Fabricjs Object today and it added a random object property which was nowhere to be found on official docs. At first I thought it was amazing to get a real looking code but upon testing I was confused how to take this.
I don't use it, it returns mostly incorrect code that makes me realize it's not worth it. I'm more productive and write better code ignoring ChatGPT 95% of the time.
my comment will probably get flagged or downvoted or whatever, but yeah agreed.
I literally cannot understand how people code that need gpt as an assistant for writing code. If I can reason about it, I can write it faster then the feedback loop takes for prompting.
It's for new things: new languages, frameworks, libraries. When you're not fluent, it can be a helpful hand for a beginner, or someone who has to do a lot things that they are not expert in, like a one man band in a sole enterprise or corner of a startup.
It can increase efficiency for generalists. For deep work, it's less useful.
No offense, but I wouldn't hire you based on your resistance to learning new technology.
You haven't spent enough time with GPT-4 and CoPilot to understand how LLMs can save you time. There is a reason why the world's top engineers like Andrej Kaparthy[1] and Guido van Rossum[2] are using these tools, they save a ton of time and work when used correctly.
Personally I'm using these tools for coding, research, and writing. Anyone who doesn't understand how much they can accelerate these tasks when used effectively are going to get left in the dust. I've spoken to colleagues who don't seem to get it as well, it's strange to me
I find it is really useful for giving me a base to start from, especially when it’s writing code for tools that I am not very comfortable with. It usually won’t spit out the ultimate solution on the first try, but it can give me an idea of how to modify what it gave to do exactly what I want, in way less time than actually writing it.
The use case where it's really good is boilerplate code that you may not remember. For example, I haven't written React code for years now. I know what good React code looks like when I see it because I've worked with it before, but I wouldn't be able to implement something from scratch without googling or copying stuff from Github. I just don't remember the libraries and best practices off the top of my head.
When I ask ChatGPT to do it for me it gives me an excellent starting point. Sure, there will be bugs, but because I know what I want I can spot and fix them immediately. It's much faster to adjust ChatGPT's code than it is to Google around for starting points.
Another example are shell scripts. I only touch bash once every few months and I keep forgetting the syntax for certain operations. Asking ChatGPT to give me a starting point is much faster than googling and visiting 20 StackOverflow posts for what I want.
But I agree with you that for day-to-day work on the same codebase where you have all the context, ChatGPT usually isn't worth it.
We use it a lot at my job. A lot of tasks that used to hour long minor tasks are great for generating with ChatGPT and getting them done in a few minutes
Prompts like these
1. Generate me a build pipeline using GitHub actions that builds a java project with docker and posts JUnit test results to a PR
2. Write me a python program that copies all the Cloudwatch dashboards my production AWS account, replace all the instances of the word ‘prod’ and replace with ‘qa’ and and post the results to this AWS account.
These are two things I’ve done recently that aren’t particularly enjoyable but necessary parts of any software work.
I'm not in tech like most of y'all. I help out my dad with his consulting company for mostly public agencies. The other day a group we're working with wanted my dad to write some media notes for the unveiling of a project that's been in the works for a while. I gave chatgpt a quick prompt of what the project is, who the audience is, how it's important for a certain demographic and for the community, etc. My dad edited it and sent it over to the leader of this group for his speech the next day. Even though it was edited, I laughed because a chatgpt quote that wasn't edited made it on to the government's website for a pretty big announcement.
Other than that I used it this morning while editing a report we hired a team to create. It was helpful to reword some sentences that weren't very clear before sending it off to the client.
Other than that, I mostly use it to brainstorm ideas/give me related concepts to something I'm working on.
Also, not work related, but last week I used chatgpt to create an opening message for a dating app. I knew the gist of a joke I wanted to say related to this woman's interests, but had chatgpt word it for me. There was a lot more to our conversations, but she did at least respond to the opener and we got the conversation rolling. We actually went on a date this weekend, where I had to rely on my own brain's inefficient language model! It went pretty well though.
Haha good question. I...did not. I feel a bit weird about that but I like to overshare, so it will definitely come out. She was talking about how she uses chatgpt to help write abstracts for her engineering PhD papers. Hopefully she won't take issue with it and think I'm not genuine, etc. I think it will be fine though based on our other conversations.
I did actually do something somewhat similar with another girl. She was a nursing student who used chatgpt for statistics homework (as well as to cheat on exams!). After we hung out I sent her a simple chatgpt generated message along the lines of thanks for hanging out, had a great time, should do it again, etc. Then immediately after I sent a message saying that I had asked chatgpt what to say to someone after a date. She seemed to think that was funny...although we never did hang out again (for other reasons).
Extremely good at turning JSON into a Go struct. Just in general, as someone who has spent years writing Python, it’s helped me fill in gaps with Go. This is a killer feature for GPT.. if you’re proficient in one language it can help you rapidly get up to speed in another.
Working for a large international company I use ChatGPT mostly as a code generator for one time tools (for a variety of languages and shells) and also to generate boilerplate text for email answers and document templates. I'm looking at this form a technical perspective and anything that can help my creative side be a bit better is good. A 2023 way of the rubber duck method of debugging, or a 2023 method of generating "manager speak".
We have had strict instructions not to put any code/email/text into ChatGPT, just use it as a virtual person to talk to and get ideas from.
But: the moment ChatGPT v4 can run on-prem in my private cloud things will be going to be wild. One advantage of working in a large multinational is that for everything there is a procedure or a standard. I have 25 years of design documents, source code, test documents, user documents, and a ticket system with 25 years of problems & answers how each ticket was resolved. The moment I can feed that into my local ChatGPT instance the whole helpdesk/support system will dramatically change.
I'm optimistic on the timeline: I think that within the next 2 to 3 years all commercial ticket tracking systems will have their own ChatGPT-like back-end.
Yes. It is a good clue engine. If I can’t solve a problem it will give me something to try. Sometimes misses the mark. Sometimes finds something I hadn’t thought of.
Also great for asking how to in Python questions and explaining ML concepts. Danger is I wont learn Python properly but just remember the prompts!
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I would say my efficiency is up ~20% since starting to use it, and my Google searches & StackOverflow visits are probably down 80-90%. At least with respect to this corner of the internet, they are both in mortal danger.
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- I ask it to create list of questions that different personas might want to answer with our reports section. I then ask it to categorize those questions & to then provide suggestions for graphs & dynamic filters that would help answer those questions.
- I ask it for help translating emails and documents for international customers.
- I ask it to create markdown, formatted spec documents with really verbose context. Helps me as sort of a foundation for feature sprint kickoffs.
- I ask it to take internal documentation and to simplify it so that we're able to use it for public facing help center documentation.
- I use it as my first resource for asking questions about SQL queries, React patterns, explaining different things eg SVG properties and how to manipulate them. I gut check things with Google when I feel like it might be hallucinating but generally it does really well ~ 90% of the time. Saves lots of time compared to going to Google first.
- I ask it for help writing tests or help refactoring code
- I asked it for help in creating some policy & procedures docs that we needed for compliance. Essentially gives you a decent template to then build from & customize.
- Lots of other things. It replaced Google for so many things in my daily workflow. It also helps a lot when you're not feeling creative and you need some ideas.
I was asking chatGPT give me boilerplate for Fabricjs Object today and it added a random object property which was nowhere to be found on official docs. At first I thought it was amazing to get a real looking code but upon testing I was confused how to take this.
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I literally cannot understand how people code that need gpt as an assistant for writing code. If I can reason about it, I can write it faster then the feedback loop takes for prompting.
It can increase efficiency for generalists. For deep work, it's less useful.
You haven't spent enough time with GPT-4 and CoPilot to understand how LLMs can save you time. There is a reason why the world's top engineers like Andrej Kaparthy[1] and Guido van Rossum[2] are using these tools, they save a ton of time and work when used correctly.
[1] https://twitter.com/karpathy/status/1608895189078380544
[2] https://www.youtube.com/watch?v=_KjSkGgaJ1k
When I ask ChatGPT to do it for me it gives me an excellent starting point. Sure, there will be bugs, but because I know what I want I can spot and fix them immediately. It's much faster to adjust ChatGPT's code than it is to Google around for starting points.
Another example are shell scripts. I only touch bash once every few months and I keep forgetting the syntax for certain operations. Asking ChatGPT to give me a starting point is much faster than googling and visiting 20 StackOverflow posts for what I want.
But I agree with you that for day-to-day work on the same codebase where you have all the context, ChatGPT usually isn't worth it.
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Prompts like these
1. Generate me a build pipeline using GitHub actions that builds a java project with docker and posts JUnit test results to a PR
2. Write me a python program that copies all the Cloudwatch dashboards my production AWS account, replace all the instances of the word ‘prod’ and replace with ‘qa’ and and post the results to this AWS account.
These are two things I’ve done recently that aren’t particularly enjoyable but necessary parts of any software work.
Other than that I used it this morning while editing a report we hired a team to create. It was helpful to reword some sentences that weren't very clear before sending it off to the client.
Other than that, I mostly use it to brainstorm ideas/give me related concepts to something I'm working on.
Also, not work related, but last week I used chatgpt to create an opening message for a dating app. I knew the gist of a joke I wanted to say related to this woman's interests, but had chatgpt word it for me. There was a lot more to our conversations, but she did at least respond to the opener and we got the conversation rolling. We actually went on a date this weekend, where I had to rely on my own brain's inefficient language model! It went pretty well though.
I did actually do something somewhat similar with another girl. She was a nursing student who used chatgpt for statistics homework (as well as to cheat on exams!). After we hung out I sent her a simple chatgpt generated message along the lines of thanks for hanging out, had a great time, should do it again, etc. Then immediately after I sent a message saying that I had asked chatgpt what to say to someone after a date. She seemed to think that was funny...although we never did hang out again (for other reasons).
You can also check out the awesome work Tom did: https://github.com/twpayne/go-jsonstruct
We have had strict instructions not to put any code/email/text into ChatGPT, just use it as a virtual person to talk to and get ideas from.
But: the moment ChatGPT v4 can run on-prem in my private cloud things will be going to be wild. One advantage of working in a large multinational is that for everything there is a procedure or a standard. I have 25 years of design documents, source code, test documents, user documents, and a ticket system with 25 years of problems & answers how each ticket was resolved. The moment I can feed that into my local ChatGPT instance the whole helpdesk/support system will dramatically change. I'm optimistic on the timeline: I think that within the next 2 to 3 years all commercial ticket tracking systems will have their own ChatGPT-like back-end.
However, in a year I'm sure it'll be spontaneously demanding equal rights :)
Also great for asking how to in Python questions and explaining ML concepts. Danger is I wont learn Python properly but just remember the prompts!