“The post-AI worker is the interface between human intent and machine execution. AI handles the How; you provide the Why and the What.”
When agents can execute almost anything, the bottleneck moves to translation: turning fuzzy human intent into instructions a machine can run, and turning machine output back into human judgment. The worker becomes an API.
Intent, taste, and constraints are your endpoints. No model generates these; it can only request them from you.
Execution, drafting, search, computation, the implementation details flow to agents.
Output comes back for judgment, not rubber-stamping. The interface is only as good as its reviewer.
A marketing lead stops writing campaigns and starts "exposing endpoints": the brand's non-negotiables, the audience truth, the one metric that matters. Agents generate twenty routes; she rejects eighteen on taste in minutes. Her throughput 10×s, but only because her interface is sharp.
A clean API with a weak operator behind it just ships bad decisions faster. The model assumes the human actually has a Why and the taste to judge the return. Garbage intent in, garbage at scale out.
What are the three "endpoints" only you can provide on your work, and are they written down anywhere?