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).
Maskin
AI made individuals faster. Maskin makes companies smarter.
Two months ago Magnus and I made a bet. Can we build the workspace for AI Agent & Human collaboration using 3 structured elements: Bets, insights and tasks. Today that Machine (Maskin is Scandinavian for Machine) is running ours entire company using closed loops.
Magnus and I trained PMs in AI PM before this. Every team hit the same wall. Individuals got AI but the organisations did not. ChatGPT made one person 2x faster. The company they work in operates the same as it did in 2023.
The missing layer is loops, not features. A team forms a bet — a shaped, measurable outcome. Agents do the legwork: pull the signal, draft the work, surface the result. The human reads the outcome, the next bet is sharper because of it. That's what closing the loop looks like when you describe behavior instead of selling magic.
Maskin is the workspace that shape needs. One surface humans and agents share — same objects, same comments, same history. MCP-native end to end, Apache 2.0 from day one.
Humans do the thinking. Agents do the work.
One open question: when you've worked with an agent inside a real workflow, what was the smallest thing that made it suddenly feel like a teammate instead of a tool?
I've known Sebastian since our SPACE10 days, when we worked on conversational interfaces for IKEA. I've been waiting for someone to crack the multiplayer side of AI.
Can't wait to give it another go with the team!
Love the focus on shared objects and closed loops!
What’s the first workflow where teams usually realize Maskin is changing the company, not just making one person faster?
About Maskin on Product Hunt
“AI made individuals faster. Maskin makes companies smarter.”
Maskin was submitted on Product Hunt and earned 18 upvotes and 7 comments, placing #28 on the daily leaderboard. Build the loops that make your company AI-native. From customer signal to shipped bet to measured outcome — automatically. Open source.
Maskin was featured in Task Management (84.1k followers), Developer Tools (515.4k followers), Artificial Intelligence (473.1k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 215k products, making this a competitive space to launch in.
Who hunted Maskin?
Maskin was hunted by Sebastian Krumhausen. 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.
Want to see how Maskin stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Sebastian Krumhausen
Hi Product Hunt Community,
Two months ago Magnus and I made a bet. Can we build the workspace for AI Agent & Human collaboration using 3 structured elements: Bets, insights and tasks. Today that Machine (Maskin is Scandinavian for Machine) is running ours entire company using closed loops.
Magnus and I trained PMs in AI PM before this. Every team hit the same wall. Individuals got AI but the organisations did not. ChatGPT made one person 2x faster. The company they work in operates the same as it did in 2023.
The missing layer is loops, not features. A team forms a bet — a shaped, measurable outcome. Agents do the legwork: pull the signal, draft the work, surface the result. The human reads the outcome, the next bet is sharper because of it. That's what closing the loop looks like when you describe behavior instead of selling magic.
Maskin is the workspace that shape needs. One surface humans and agents share — same objects, same comments, same history. MCP-native end to end, Apache 2.0 from day one.
Humans do the thinking. Agents do the work.
One open question: when you've worked with an agent inside a real workflow, what was the smallest thing that made it suddenly feel like a teammate instead of a tool?