This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
Product upvotes vs the next 3
Waiting for data. Loading
Product comments vs the next 3
Waiting for data. Loading
Product upvote speed vs the next 3
Waiting for data. Loading
Product upvotes and comments
Waiting for data. Loading
Product vs the next 3
Loading
D.R.I.P.
Turn your saved content graveyard into PDFs you'll use
Update: D.R.I.P. now runs on Windows and Linux too, not just macOS πͺπ§ Same daily PDFs, same self-learning loop β now with a one-click installer for each OS and native scheduling (launchd / systemd / Task Scheduler). Already verified on real Windows and Linux machines. Anyone who's already bought it gets the update free.
I built DRIP because my "saved" tab became a graveyard.
Across YouTube, X, Instagram, TikTok, Facebook, LinkedIn, and browser bookmarks, I had thousands of items I'd genuinely wanted to act on β recipes, workouts, strategy articles, podcast interviews β and watched maybe 5% of them. The volume itself made the whole pile feel dead.
So I built something that runs every morning while I sleep:
- Reads what I saved across all 7 platforms (subtitles first, never downloads the video file) - Detects what each item actually IS β recipe, workout, podcast, strategy article - Generates the right format: ingredient tables, exercise tables, podcast summaries - Sorts everything into folders by topic
The bit I'm most proud of: a self-learning loop. I rate each PDF k (keep) or t (trash), and the AI derives one-line rules from my mistakes and injects them into the classifier as few-shot examples on the next run. Inspired by Karpathy's autoresearch loop.
Runs entirely on your machine with Ollama (free, fully local), or plug in Claude/GPT/Grok if you'd rather. As of v2 it runs on macOS, Windows, AND Linux β one installer per OS.
Looking for early users to rate what it generates β that's literally what makes it better. Would love your feedback.
About D.R.I.P. on Product Hunt
βTurn your saved content graveyard into PDFs you'll useβ
D.R.I.P. was submitted on Product Hunt and earned 4 upvotes and 2 comments, placing #108 on the daily leaderboard. Update: D.R.I.P. now runs on Windows and Linux too, not just macOS πͺπ§ Same daily PDFs, same self-learning loop β now with a one-click installer for each OS and native scheduling (launchd / systemd / Task Scheduler). Already verified on real Windows and Linux machines. Anyone who's already bought it gets the update free.
On the analytics side, D.R.I.P. competes within Mac, Productivity and Artificial Intelligence β topics that collectively have 1.2M followers on Product Hunt. The dashboard above tracks how D.R.I.P. performed against the three products that launched closest to it on the same day.
Who hunted D.R.I.P.?
D.R.I.P. was hunted by Bruce. A βhunterβ on Product Hunt is the community member who submits a product to the platform β 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.
For a complete overview of D.R.I.P. including community comment highlights and product details, visit the product overview.
Bruce
Hey Product Hunt π
I built DRIP because my "saved" tab became a graveyard.
Across YouTube, X, Instagram, TikTok, Facebook, LinkedIn, and browser bookmarks, I had thousands of items I'd genuinely wanted to act on β recipes, workouts, strategy articles, podcast interviews β and watched maybe 5% of them. The volume itself made the whole pile feel dead.
So I built something that runs every morning while I sleep:
- Reads what I saved across all 7 platforms (subtitles first, never downloads the video file)
- Detects what each item actually IS β recipe, workout, podcast, strategy article
- Generates the right format: ingredient tables, exercise tables, podcast summaries
- Sorts everything into folders by topic
The bit I'm most proud of: a self-learning loop. I rate each PDF k (keep) or t (trash), and the AI derives one-line rules from my mistakes and injects them into the classifier as few-shot examples on the next run. Inspired by Karpathy's autoresearch loop.
Runs entirely on your machine with Ollama (free, fully local), or plug in Claude/GPT/Grok if you'd rather. As of v2 it runs on macOS, Windows, AND Linux β one installer per OS.
Looking for early users to rate what it generates β that's literally what makes it better. Would love your feedback.