Different angle on this, and it may or may not fit your setup, but it changed things for me.

I’ve been accumulating audio since the early 2000s. Twenty-some years of ripped CDs, vinyl rips from release groups, random downloads. Several thousand albums. At some point I accepted that tags were never going to be consistent across that pile, because the sources never agreed on anything in the first place: a 1979 vinyl rip tagged by whoever released it, a CD rip from 2004, and a modern FLAC have nothing in common metadata-wise, and no tagger reconciles that without me babysitting it.

So I stopped trying to fix the tags and leaned on the folder structure instead. My tree already carried everything I cared about: genre at the top, then artist, then Artist - Year - Album, with subfolders for live, compilations and singles. That structure took years to build and it’s reliable in a way my tags never were.

I run Velvet (mStream fork) as the server for it. It serves the library by folder structure rather than by tag database, so there’s nothing to scan, nothing to match, nothing to get wrong. And I vibe-coded Sharesonic, an Android client for it, because I wanted to browse my library the way it’s actually organized and share a track, a playlist or an entire folder as a public link without exporting anything. Personal project, it’s on GitHub if anyone wants it.

To be clear about what this does and doesn’t solve: it doesn’t repair your files. If Picard truncated audio on you, that’s a real problem and it needs fixing at the file level, not at the player level. Worth checking whether the audio itself is actually shorter or whether it’s just the duration metadata disagreeing with the stream, because both look identical from the player side and only one of them is destructive.

The trade-off is real. You lose cross-cutting queries: no “everything from 1977 across all artists”, no proper album artist handling for compilations. If that matters, stay on Jellyfin and keep grinding through Picard. If you mostly navigate by “I want to hear that specific album”, folders are faster than any tag database.

Honestly, I don’t know what people expect either, and I do think there’s a fair bit of snobbery and gatekeeping around what this community rightly calls AI slop (and don’t get me started on reddit’s /r/selfhosted lol).

I’ve been interested in code from afar, but my life priorities and passions mean learning to code properly has to take a back seat. That said, I have ideas, I’m rigorous, and I can read and learn. So I use Claude to vibe-code a whole bunch of tools that fill a real gap in what already exists for my hobbies and my two jobs. Whether I use AI or not is my responsibility, and every public repo I have carries a disclaimer about AI usage.

For me, the bar should be: does it work, is it documented, and is the AI involvement disclosed clearly ? If yes to all three, I’m curious enough and big enough to review the repo and try it myself.

Mods here have proposed tags and standards to tell apart projects with varying degrees of AI involvement. Yet the systematic backlash makes me hesitant to share tools that could genuinely help some people, spark ideas for others, or maybe even lead to a collaboration with someone skilled enough to build something exceptional for the community. In my case, AI is a very useful tool, but it only ever produces stuff for me alone.

Which is a shame.

I stand by my technical observations, which were about the image, not the photographer. If you perceive critique as an attack, that’s your prerogative, but it’s not my problem. Have a nice day.

First, I don’t see what entitles you to use such a tone. Did I disrespect you? Given the time you took to delete your first response and stew over the next two, it seems I struck a nerve. Are you okay ?

Of course, I looked at the photographer’s Instagram feed. I saw his high-level commitment to wildlife photography. I analyzed the image he posted because I found it intriguing, because I enjoy the exercise, and because (by sharing it publicly) he invited critique. That’s my right.

My ability to spot inconsistencies comes from years of practice and a trained eye. What can I do about that?

That said, I never mentioned AI (and yes, my little profile rodent is rather cute, isn’t it?). I simply pointed out that the image appeared manipulated. Photoshop has been around since the ’90s, after all.

So, put your anger aside and let me appreciate and critique the work shared with the public in peace.

While the image is undeniably striking, a closer look reveals some inconsistencies: the lighting sources clash, and the patch of grass in the foreground feels out of place, almost as if it’s there to conceal something. It’s a well-crafted composition, but the seams show for those who know where to look. Still, kudos to the photographer for pulling off such a bold visual analogy.