Hey fellow programmers, I wanted to share a little experiment I’ve been
conducting lately that has significantly improved my workflow. I’ve started
using AI to generate my Git commit messages, and it’s been a game-changer! By
feeding all the changes I’ve made into a language model with a large context
window (LLM), the AI not only generates a concise commit title but also provides
bullet points describing each of the changes in precise detail. The level of
detail and informativeness it brings to my commit messages is incredible. I used
to spend a considerable amount of time crafting commit messages that accurately
captured the essence of the changes I made. Now, with the help of AI, I find
myself copy-pasting its generated messages most of the time. It’s not just a
time-saver; it also ensures that my commits are well-documented and easy to
understand for my team members. If you haven’t explored using AI for your Git
commits, I highly recommend giving it a try. It can significantly boost your
productivity and help you maintain clean and informative version control
history. Plus, it’s a fascinating intersection of AI and software development!
Have you experimented with similar AI-powered tools for your programming tasks?
I’d love to hear your experiences and any recommendations you might have. Let’s
discuss the future of AI in programming in the comments!
It writes more informative commits than I could ever make so I’m just reading what it says and mostly copy/pasting completely most of the time, I write all of the changes I’ve made into an LLM with a large context window and it write a very detailed commit not just with a title but with bullet points describing each of the changes precisely
If you were on my team and I knew you were doing this, aside from all the other issues everybody else has mentioned in this thread, I’d be going out of my way not just to check every single one of your git commits (both code changes and commit messages) for inaccuracies but also also to find every possible reason to nit pick everything you committed.
You shouldn’t be using LLMs to write your git commits (messages or code changes.) They hallucinate. But if you are going to use them, you need to spend much more time proofreading what they output than you’d spend writing it yourself. Check every single word for errors. (And, honestly, make the text fit with the way other commits by your team read (assuming you are on a team).)
In short, if you’re going to use LLMs, DO NOT TRUST ANYTHING THEY GIVE YOU. And don’t be surprised if you get negative blowback from others for using them at all. Keep in mind what can happen if you trust LLMs.
IMHO, the provided link is largely irrelevant to this topic. It is about lawyers who used ChatGPT as a search enginehttps://youtu.be/oqSYljRYDEM?t=1436, which is not what it is for, and it will tell you that over and over again. The lawyers in question were not even “trusting ChatGPT”. They blatantly and actively disregarded ChatGPT telling them that it was not a search engine and could not provide up to date legal information https://youtu.be/oqSYljRYDEM?t=1466
This topic is about using LLMs to generate natural language describing code changes that it is provided with which is not only completely different than using an LLM as a defacto search engine, but it is also something LLMs are actually meant to do: autocomplete. This topic is more akin to using LLMs to write title headings for legal documents which are already basically complete as is than it is akin to the link provided.
If you were on my team and I knew you were doing this, aside from all the other issues everybody else has mentioned in this thread, I’d be going out of my way not just to check every single one of your git commits (both code changes and commit messages) for inaccuracies but also also to find every possible reason to nit pick everything you committed.
You shouldn’t be using LLMs to write your git commits (messages or code changes.) They hallucinate. But if you are going to use them, you need to spend much more time proofreading what they output than you’d spend writing it yourself. Check every single word for errors. (And, honestly, make the text fit with the way other commits by your team read (assuming you are on a team).)
In short, if you’re going to use LLMs, DO NOT TRUST ANYTHING THEY GIVE YOU. And don’t be surprised if you get negative blowback from others for using them at all. Keep in mind what can happen if you trust LLMs.
IMHO, the provided link is largely irrelevant to this topic. It is about lawyers who used ChatGPT as a search engine https://youtu.be/oqSYljRYDEM?t=1436, which is not what it is for, and it will tell you that over and over again. The lawyers in question were not even “trusting ChatGPT”. They blatantly and actively disregarded ChatGPT telling them that it was not a search engine and could not provide up to date legal information https://youtu.be/oqSYljRYDEM?t=1466
This topic is about using LLMs to generate natural language describing code changes that it is provided with which is not only completely different than using an LLM as a defacto search engine, but it is also something LLMs are actually meant to do: autocomplete. This topic is more akin to using LLMs to write title headings for legal documents which are already basically complete as is than it is akin to the link provided.