The Human API
“The post-AI worker is the interface between human intent and machine execution. AI takes the how. You supply 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, then turning machine output back into human judgment. The worker becomes an API.
You expose the why
Intent, taste and constraints are your endpoints. No model generates these. It can only request them from you.
The machine handles the how
Execution, drafting, search, computation: the implementation details flow to agents.
You validate the return
Output comes back for judgment, not for a rubber stamp. The interface is only as good as its reviewer.
A marketing lead stops writing campaigns and starts exposing endpoints: the brand’s non-negotiables and the one metric that matters. Agents generate twenty routes. She rejects eighteen on taste in minutes. Her throughput goes up tenfold, 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 what comes back. Garbage intent in, garbage at scale out.
What are the three endpoints only you can provide in your work, and are they written down anywhere?
- You supply the why and the what. The machine supplies the how.
- Throughput is capped by the quality of your interface.
- A sharp reviewer is the scarce part of the system.