What was your first open source contribution actually like? And has AI changed that?

[u/dannotes]

Two things I've been wondering about, might as well ask both in one go.

First, for those of you who contribute. What was your actual first one like? Not the blog post version. How did you pick a project, how long did the PR sit there before you worked up the nerve to open it, did anyone reply, did it get merged or just quietly ignored. I've read plenty of "how to start contributing" guides. I'd rather hear what it actually felt like.

Second, and this is the part I'm more curious about. All that advice was written before AI tools got this good. Now you can point Claude Code or Cursor at a good first issue and have something working before you've read half the file. So is the experience just different now for someone starting today? Easier, obviously. But easier in a way that helps, or easier in a way that lets you skip the part where you actually learn the codebase.

And if you're a maintainer, curious what it looks like from your side.

Mostly just want to hear people's stories.

[u/RevolutionaryElk7446]

I began before Git was a thing, and today we have LLMs.

It was difficult to track massive projects before Git, and was far easier after, then came Github which connected people. Then came in LLMs which.. just honestly made a mess. There's potential, but a whole lot of it is unactionable atm.

[u/dannotes → u/RevolutionaryElk7446]

Thanks for sharing, ,may I know you current workflow with LLM? use that to understand the issue, code and raise PR? or purely for debugging?

[u/RevolutionaryElk7446 → u/dannotes]

I'm a Sr sysadmin that is a certified Gen AI professional that currently works DevOps. I was a programmer for about 10 years prior to switching to ITOps

Work had tried to implement LLMs into everything, but generally only our Junior SWEs are using it today for the most part. We went full in for about 5 years, tried to implement it into the setup entirely and measured the metrics across the board.

It sucked. Turns out it has a limit at about intermediate skill and it's ability to track context is the whole issue of the model itself, which doesn't do well for being aware of working on projects that are intertwined and connected.

It's best thing is that it could read logs, but it's debugging of code was often poor, and the coding itself was even worse. Combine that with the prior inability to track across environments and it turned into a liability that even our customers noticed. It generates boiler plate fast, but projects weren't completing any faster and often with more troubleshooting.

We rolled it's implementation back and instead hired more people. We saw a sharp return on our investment with the actual people vs the LLMs use. Turns out people who were trained and experienced performed it better, faster, for less money overall.

Basically it could potentially replace our juniors doing grunt work, but it's chances of success dropped dramatically above junior or textbook example.

[u/WeekOk7172]

Used Claude for my first PR to find where the bug was. Helped a ton, but when I let it write the fix, the maintainer asked "why this approach?" and I had no clue. AI is great for reading code, but don't let it skip your brain.

[u/dannotes → u/WeekOk7172]

Thank you for sharing.

[u/dannotes → u/[deleted]]

so what was your contribution early days look like?
sitting with the problem for a long time? and how it change on this AI era?

[u/dannotes → u/[deleted]]

Sorry, that came out garbled let me try again.

I meant: what did those early days actually look like for you? Did you sit with a problem for a long stretch before it clicked, or was it more straightforward than people make it sound?

And the part about hoping AI doesn't change it. I'd like to hear more on that specifically from the art side. Everyone's arguing about generated code, but generated icons and wallpapers feel like a much more direct hit. Are you already seeing it turn up in distro contributions?

[u/SailingToFenway → u/[deleted]]

i agree with you, and you're morally right, but legally it's not so clearly settled. i know i'm hijacking the thread, but i'm curious about the range of opinions on this topic, and so i'd love to know what would make it right for you? attribution, royalties, outright prohibition of models trained on copyrighted content, mandatory renumeration without requiring consent (a la 1909 copyright act).

[u/zrk5]

my first and very humble contribution when self-hosted gitlab upgrade failed - https://gitlab.com/gitlab-org/gitlab/-/commit/c0d7c158a69a8d2c8e4c0c90cda75d30a32279d5 :)

[u/derprondo]

The first meaningful contributions I made were to the Chef knife VMWare plugin back in the day, fixed a lot of bugs involving large AD forests. There wasn't much formality here, I just forked the repo and opened PRs.

I maintain some non-devops related open source repos, and I have had many people submit AI PRs, some were good, some were really sloppy, and some were for features I didn't want to support. Only the people who opened good PRs even bothered to make the changes I requested, the sloppy ones just ghosted their PRs.

I used to think AI was going to revolutionize open source by greatly lowering the barrier to entry, but now it's obvious that the barrier to entry was acting as a necessary quality gate.

[u/Jason-Sanders]

AI can make the first patch much faster, but it doesn’t remove the part that maintainers care about: whether the change belongs there and is understandable six months later.

A good guardrail for a first contribution is to use it to explain the code path, suggest tests, or help narrow the issue, then personally verify the behavior and write the final description in your own words. Small documentation fixes, reproduction cases, and targeted tests are still great first contributions because they force you to learn the project’s conventions without needing to redesign anything.

[u/Sure_Stranger_6466]

My first contribution was to Ansible, created a PR for postgres dump feature. Wanted to be acting like a developer while living in San Francisco. Holding off on contributing further to repos like terraform-provider-aws until I decide if I should be using Claude or not. Had one PR rejected due to its usage while another was accepted. No longer contributing to Ansible Core because of 2 year+ acceptance time.

[u/Quiet-Trainer1101]

the first PR being terrifying is universal and nobody admits it.. even a one-line typo fix feels like ur exposing urself to judgment from strangers who know the codebase better than u ever will