The Absorption Test: Will AI Absorb Your Business?
The real moat question is not whether AI can do what you do. It is whether anyone still pays you after it does. Here is the Absorption Test and how to pass it.
Field notes from four reinventions — a $200M exit, two unicorns, and building AI-native. Published as I learn.
The real moat question is not whether AI can do what you do. It is whether anyone still pays you after it does. Here is the Absorption Test and how to pass it.
AI is great at the how and silent on the what. The skill that atrophies is initiative: deciding what to do when nothing prompts you. Here is how to protect it.
AI agent costs do not just shrink payroll. They change its shape, turning a fixed salary into variable metered compute. Here is the margin trap and the fix.
AI agents reach production in regulated, auditable work first. The moat is the audit trail, not the model. Here is the deployment order and why.
AI burnout is not about working too little or resting too much. It is the bar for enough rising faster than you can meet it. Here is how to define enough.
Revenue per employee became the number investors trust, and headcount growth turned into a warning sign. How the signal inverted, and how to hire lean.
AI agent evaluation is where demos lie. Why agents pass benchmarks yet fail in production, and how to measure real production readiness before you ship.
Decision fatigue is the hidden tax on AI output. Cheap execution multiplies your decisions, and deciding is the one skill that gets worse the more you use it.
Computer-use agents can automate any software a human can see, but they are slow, costly, and brittle. The Interface Ladder shows founders when to use them.
Automation bias is the operating risk that shows up when your team quietly stops checking AI output. How it compounds, and where to make checking mandatory.
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