Ramblin' & Amblin' (2026-10-16): Recording this video and the way you're going

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Ramblin' & Amblin' (2026-10-16): Recording this video and the way you're going

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Ramblin' & Amblin' Field Notes with Mike Hall (Staff Software Engineer) Recorded on the move: engineering observations, systems architecture, and software craftsmanship reflections.
The Interviewer

Mike Hall

Host, ramblin-amblin

The Presentation


Mike Hall Host, ramblin-amblin ▶ Speaking
I'm recording this video and the way you're going to see it is because I've recorded the video and then I upload it to a Google Drive and then all the pipeline stuff happens. What it eventually does is it ends up back on my computer and where I run a enrichment and publishing pipeline which is going to take the video, it's going to transcribe it, it 's going to enrich the content, build a description and title based off of my content and my corpus of data, then it is going to publish a video to the appropriate channel playlist, well channel and playlist and then yeah then you'll see it if you if you watch my channel at least I'll see it and what's really interesting about this for me is not just that this is all going to happen but it's also in the context of an article I'm putting together on AI SLOP which is not really the SLOP, maybe it's right, I don't know but that's the trick is that while we can do stuff and build automation pipelines and all this amazing stuff with the tools and it just like happens almost instantaneously we're able to be able to do stuff where yeah there's an outcome but is it the right thing I don't know I don't know and like in this case you know it gives you a false sense of confidence somebody might look at some information that was spit out by the AI and because the AI generated something that was usable passively usable then the providence of the providence of whatever text that comes out in numbers and stats is and recommendations on what the the best specialized skill tool what I'm trying to say is that it was a lot of audio audio work was done and for cleaning up a video that had gotten corrupted and you could say yeah it looks like or it sounds like it's better but all of the stats and the numbers you know what I looked at is yeah I could do research and I could figure out what all of this stuff means but to leapfrog from problem to here is the complete solution it makes me think about what people are talking about what people are talking about AI saying oh we solved all these hypotheses and all of these impossible formulas but if we can't prove it then how do we know and if we can't reproduce it then how do we know how to prove it so yeah I 'm doing this and it's surreal because it is something that works and in this case you know I know all of the steps of what happens and why it works and how it works but there are decisions to get made by the AI tools based off of information that most of us are not really equipped to assess the accuracy or provenance or validity of any of those numbers and then we go and we repeat those numbers and repeat those statements and I've seen it I've seen it in action and this is just a particularly interesting opportunity to exercise this so hopefully this will be interesting all right we're at four minutes almost here all right thanks bye