MediaSeg is a local macOS utility that splits large media files into upload-ready chunks while preserving quality. It was produced and directed with full AI assistance, and shipped in 2 days from idea to public release. Originally created to streamline long-recording upload prep, MediaSeg is useful for NotebookLM and other size-limited upload destinations.
MediaSeg is a local macOS utility that splits large media files into upload-ready chunks while preserving quality.
It was produced and directed with full AI assistance, and shipped in 2 days from idea to public release.
Feedback welcome on workflow clarity, screenshots, and positioning.
As a music producer I hit this constantly with long mixdowns and stem bounces that blow past upload caps — does it handle audio-only files (WAV/AIFF) too, or is it video-first for now? Local + ffmpeg stream copy is exactly the right call.
This solves a real workflow annoyance. Zoom recordings and long interview clips are exactly the kind of files that break upload limits constantly, and the existing options are either clunky web tools or rolling your own ffmpeg commands. The macOS-native angle is smart - nobody wants a browser tab for this. Shipped in 2 days from idea is impressive too. What's the largest file you've tested it on, and does it handle multi-track audio correctly after splitting?
This is one of those tools you don't think about until you hit 2gb uplload limit and waste time compressing everything.
stream-copy by size is the honest call — but when a cut lands mid-GOP, the next chunk opens with no i-frame, so anything that re-decodes per chunk (notebooklm) eats garbage till the next keyframe. snapping the boundary to the nearest keyframe is the usual escape hatch.
How big is the largest file you’ve run through? I’m curious where the limit is, with NotebookLM recordings I once struggled with 4GB files and the standard tools were crying.
Honestly the kind of thing where the whole pitch is just "yeah, I needed this and got tired of waiting." 😅 Hitting upload caps on long recordings is such a quiet, recurring papercut. And local + no re-encode is exactly the right call.
Slick. Congrats on shipping it 👏
Does it split on keyframes to avoid glitches, or is it strictly by file size?
Local-first is the right default for long recordings. One positioning detail I would make very explicit: whether the split path uses stream copy vs re-encode. "Preserving quality" lands harder when people know the media is not being touched unnecessarily.
Anyone who’s wrestled a giant video file that won’t just upload knows exactly why it needs to exist. Simple, specific, useful. Good work!
About MediaSeg on Product Hunt
“Split large media files into upload-ready chunks on macOS”
MediaSeg launched on Product Hunt on June 22nd, 2026 and earned 130 upvotes and 26 comments, placing #8 on the daily leaderboard. MediaSeg is a local macOS utility that splits large media files into upload-ready chunks while preserving quality. It was produced and directed with full AI assistance, and shipped in 2 days from idea to public release. Originally created to streamline long-recording upload prep, MediaSeg is useful for NotebookLM and other size-limited upload destinations.
MediaSeg was featured in Mac (103.5k followers), Productivity (654.4k followers), Meetings (6.5k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 176.5k products, making this a competitive space to launch in.
Who hunted MediaSeg?
MediaSeg was hunted by Sho Nishikawa, ExaEdge. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Sho Nishikawa, ExaEdge