Portfolio strategy, weekly evidence, and decision-making notes for AI-native operators, from the Agimon team.
10 posts
The code keeps compiling. What breaks first is the shared map of what lives where and why. Why vibe coding erodes the system map long before it touches the syntax.
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Agents draft the focus, budget, and metric calls now. Here is an honest three-column inventory of what the operator job became: what agents own first, what got harder, and what nobody had a job description for before.
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Your portfolio decisions have more than one reader now: you approving this week, the agents drafting the next call from them, and whoever asks in six months why the bet was made. A note in your head serves none of them.
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Segment, channel, and value metric are focus, budget, and metric decisions you make deliberately from evidence and record in the ledger, not a document written after the build.
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One weekly cycle. Here is exactly what Agimon produces when you turn a week of product, sales, and marketing evidence into typed focus, budget, and metric decisions, and what you open Monday morning.
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On AI products, cost scales with engagement. Your heaviest users are your most expensive to serve. Here is the one number to compute before you pick a pricing model.
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MCP crossed 97 million monthly downloads and became infrastructure. Here is what actually changes when agents gain standing access to operate your portfolio and its decision ledger, not just answer questions about it.
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AI collapsed the cost of building. The cost of being wrong did not change. Find out why building the wrong thing faster is the new startup risk.
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Developers blame the model when their AI coding agent reverts fixes, hallucinates features, or loses context. The data says the bottleneck is further upstream than that.
Read postA practical workflow for moving from a week of messy product, sales, and marketing signals to typed focus, budget, and metric decisions your portfolio can act on.
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