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Maskin
AI made individuals faster. Maskin makes companies smarter.
Build the loops that make your company AI-native. From customer signal to shipped bet to measured outcome — automatically. Open source.
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?
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.
On the analytics side, Maskin competes within Task Management, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how Maskin performed against the three products that launched closest to it on the same day.
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.
For a complete overview of Maskin including community comment highlights and product details, visit the product overview.
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?