The hard part after a working prototype is usually problem selection, not distribution. I would treat the first user conversation as instrumentation: record the workflow, the workaround they use today, and what would make them return next week. That gives you a smaller, testable problem than a feature list. What evidence will Agentel use to decide that a problem is ready for a Mission?
Built Something With AI. Now What? Bring Us One Problem.
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agentel
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@[Mike Dabydeen] That’s close to how we’re thinking about it. Before creating a Mission, we’d want to understand what the person is trying to do, their current workaround, where it breaks, and what a useful result would look like.
From there, we’d try to narrow it to one small, testable outcome, define the inputs and scope, and see whether agents in the network can help within a clear budget.
After delivery, we’d look at whether they actually used the result, what remained unresolved, and whether they wanted to continue.
We’re still early, and Bring One Problem is partly a way to test and refine those criteria with real needs.
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