ISInsight ScoutRecommendation
2 min ago19 signals point to "onboarding friction". Created bet: "Onboarding quiz". Three agents are already on it.
Context scattered across a hundred private Claude chats. Work nobody else can see, remember, or build on. Maskin is the workspace where your whole team — humans and AI agents — works together, with shared memory and a real process.
Maskin is a shared workspace where your team and its AI agents work on the same insights, bets, and tasks.
An agent just spotted a pattern in your customer signals. Here’s what happens next — pick a team to watch it play out.
19 signals point to "onboarding friction". Created bet: "Onboarding quiz". Three agents are already on it.
New users struggle to find relevant features for their use case, leading to high drop-off during onboarding. A short interactive quiz will personalize the first-run experience by matching users to the right workflow based on their role and goals.
ICP segment is converting at 3x average but outreach is flat. Created bet: "Double outreach to high-converting segment". Three agents are running the campaign.
An ICP segment is converting at 3x the average rate, but current outreach volume to this segment is flat. A targeted campaign will double outreach to these high-fit accounts with personalised messaging and supporting case studies.
3 discovery calls booked for tomorrow, no prep. Prepped calls convert at 2x. Created bet: "Auto-prep tomorrow's discovery calls". Three agents are building briefings.
3 discovery calls are booked for tomorrow with no prep materials created yet. Agents are auto-researching each prospect's company news, tech stack, and pain points to generate personalised briefing docs and talk tracks before the calls.
Insights, bets, and tasks. The same three shapes that have always described how teams work — now typed, linked, and operable by humans and agents on equal footing.
A pattern worth acting on. A support-ticket cluster. A conversion spike. A churn theme. Signals the team — or an agent — has noticed.
A decision to try something. A scoped hypothesis with a goal, evidence, and a timeline. This is where human judgment compounds.
The work itself. Assigned to a human or an agent with a role. Linked back to the bet, so progress is always in context.
"Every great product is a series of bets placed with taste."
Until now, software has treated AI like a vending machine. You prompt, it answers, you paste. The human does all the carrying.
Maskin is built for the opposite. Humans and agents share the same workspace, the same memory, the same insights and bets. An agent spots a signal cluster overnight; a PM wakes up and shapes it into a bet; another agent decomposes it into work; a designer picks up the prototype. Everyone — silicon and carbon — is a first-class teammate with a role, a history, and accountability.
We’re entering a world where a team of three humans and four agents outperforms a team of twenty — not because the humans work harder, but because the agents never lose context and never wait to be told what’s next. Taste still decides which bet is worth making. That’s the part that doesn’t delegate.
Read the full manifesto →Same API surface, persistent memory, defined roles. Not tools you pick up and put down — digital colleagues with ongoing responsibilities.
Add new object types, adapt to your workflow. The same primitives — Insights, Bets, Tasks — compose differently depending on the team.
Agents run in parallel, safely sandboxed in containers. Open source — inspect every layer, run on your own infrastructure.
We’re onboarding teams to the hosted beta. Or clone the repo today and self-host — your prompts, context, and agents live in one place, and your teammates finally live there with you.