Artificial Intelligence and the Linux Community

I have wanted to write this blog post for quite some time, but been unsure about the exact angle of it. I think I found that angle now where I will root the post in a very tangible concrete example.

So the reason I wanted to write this was because I do feel there is a palpable skepticism and negativity towards AI in the Linux community, and I understand that there are societal implications that worry us all, like how deep fakes have the potential to upend a lot of things from news disbursement to court proceedings. Or how malign forces can use AI to drive narratives in social media etc., is if social media wasn’t toxic enough as it is. But for open source developers like us in the Linux community there is also I think deep concerns about tooling that deeply incurs into something that close to the heart of our community, writing code and being skilled at writing code. I hear and share all those concerns, but at the same time having spent time the last weeks using Claude.ai I do feel it is not something we can afford not to engage with. So I know people have probably used a lot of different AI tools in the last year, some being more cute than useful others being somewhat useful and others being interesting improvements to your Google search for instance. I think I shared a lot of those impressions, but using Claude this last week has opened my eyes to what AI enginers are going to be capable of going forward.

So my initial test was writing a python application for internal use at Red Hat, basically connecting to a variety of sources and pulling data and putting together reports, typical management fare. How simple it was impressed me though, I think most of us having to deal with pulling data from a new source know how painful it can be, with issues ranging from missing, outdated or hard to parse API documentation. I think a lot of us also then spend a lot of time experimenting to figure out the right API calls to make in order to pull the data we need. Well Claude was able to give me python scripts that pulled that data right away, I still had to spend some time with it to fine tune the data being pulled and ensuring we pulled the right data, but I did it in a fraction of the time I would have spent figuring that stuff out on my own. The one data source Claude struggled with Fedora’s Bohdi, well once I pointed it to the URL with the latest documentation for that it figured out that it would be better to use the bohdi client library to pull data and once it had that figured out it was clear sailing.

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