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Kooking
Swipe recipes. AI scores each one for your taste.
Forget endless scrolling. Kooking is built around the swipe. Every recipe you discover gets an AI Score — calculated for YOUR taste, pantry, and cooking style — before you even open it. Swipe right on what looks good. The AI learns. Your scores get smarter. Every recipe comes from a real home cook's kitchen, not a brand or algorithm. No noise. Just swipe, score, and cook.
Hey Product Hunt! 👋 Deepak here, maker of Kooking.
One of the core design decisions we made early on was the swipe-to-discover feed — and I want to share why we went this way and how it actually works under the hood.
🤔 The problem with recipe discovery today
Every recipe app I tried had the same broken loop: you search, you scroll, you bookmark 200 things, and you never cook any of them. The problem isn't a lack of recipes — it's that none of them feel personally relevant in the moment.
Searching requires intent. But most nights, you don’t have a dish in mind — you just want something to catch your eye.
🃏 Why swipe?
Swiping maps perfectly to how people actually decide what to cook. It’s visual, low-friction, and mood-driven. Right means "save this," left means "not tonight." No search bar, no filters, no rabbit holes.
But the real power is what happens behind each swipe. Every interaction — save, skip, cook, import — feeds a live taste profile that makes the next card more relevant than the last.
✨ How the AI match score works
Each recipe card shows a personal match score (0–100). It’s not a global popularity rank — it’s built entirely around you. Here’s what drives it:
Taste profile — cuisines, ingredients, and cooking styles you consistently save or cook
Cooking behaviour — quick weeknight meals vs. weekend projects, minimal prep vs. complex techniques
Meal plan context — if you’ve already got chicken twice this week, the feed surfaces variety automatically
Time & season signals — a slow braise scores higher on a Sunday afternoon than a Tuesday at 6pm
Creator affinity — recipes from creators you consistently engage with get a natural boost
The score is intentionally visible on every card. We want it to feel transparent — not like a black-box algorithm deciding what you eat, but a smart suggestion you can trust or override.
The more you swipe, the sharper it gets. Early users have told us it starts feeling "weirdly accurate" after just a couple of sessions.
Would love to know — what would make a recipe discovery feed feel truly personal to you? Drop it below 👇
About Kooking on Product Hunt
“Swipe recipes. AI scores each one for your taste.”
Kooking was submitted on Product Hunt and earned 5 upvotes and 2 comments, placing #111 on the daily leaderboard. Forget endless scrolling. Kooking is built around the swipe. Every recipe you discover gets an AI Score — calculated for YOUR taste, pantry, and cooking style — before you even open it. Swipe right on what looks good. The AI learns. Your scores get smarter. Every recipe comes from a real home cook's kitchen, not a brand or algorithm. No noise. Just swipe, score, and cook.
On the analytics side, Kooking competes within Social Media, Cooking and Artificial Intelligence — topics that collectively have 567.2k followers on Product Hunt. The dashboard above tracks how Kooking performed against the three products that launched closest to it on the same day.
Who hunted Kooking?
Kooking was hunted by Deepak Sharma. 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.
For a complete overview of Kooking including community comment highlights and product details, visit the product overview.
Deepak Sharma
Hey Product Hunt! 👋 Deepak here, maker of Kooking.
One of the core design decisions we made early on was the swipe-to-discover feed — and I want to share why we went this way and how it actually works under the hood.
🤔 The problem with recipe discovery today
Every recipe app I tried had the same broken loop: you search, you scroll, you bookmark 200 things, and you never cook any of them. The problem isn't a lack of recipes — it's that none of them feel personally relevant in the moment.
Searching requires intent. But most nights, you don’t have a dish in mind — you just want something to catch your eye.
🃏 Why swipe?
Swiping maps perfectly to how people actually decide what to cook. It’s visual, low-friction, and mood-driven. Right means "save this," left means "not tonight." No search bar, no filters, no rabbit holes.
But the real power is what happens behind each swipe. Every interaction — save, skip, cook, import — feeds a live taste profile that makes the next card more relevant than the last.
✨ How the AI match score works
Each recipe card shows a personal match score (0–100). It’s not a global popularity rank — it’s built entirely around you. Here’s what drives it:
Taste profile — cuisines, ingredients, and cooking styles you consistently save or cook
Cooking behaviour — quick weeknight meals vs. weekend projects, minimal prep vs. complex techniques
Meal plan context — if you’ve already got chicken twice this week, the feed surfaces variety automatically
Time & season signals — a slow braise scores higher on a Sunday afternoon than a Tuesday at 6pm
Creator affinity — recipes from creators you consistently engage with get a natural boost
The score is intentionally visible on every card. We want it to feel transparent — not like a black-box algorithm deciding what you eat, but a smart suggestion you can trust or override.
The more you swipe, the sharper it gets. Early users have told us it starts feeling "weirdly accurate" after just a couple of sessions.
Would love to know — what would make a recipe discovery feed feel truly personal to you? Drop it below 👇