AI fluency is the skill of knowing when to use AI, how to guide it, and when to step in yourself. Like language fluency, it’s less about theory and more about practical competence: clear intent, useful constraints, and good judgment.
This directory collects concrete examples of humans excelling with AI—from healthcare triage to venture investing—so you can study what good collaboration looks like in practice.
The AIM framework
We analyze each example using three lenses that capture the shape of human‑AI collaboration:
Allocate: how humans and AI divide work. Iterate: how they refine output through feedback and iteration. Mediate: how humans maintain oversight, interface AI output to the world, and ensure quality.
Allocate
Great allocation leverages strengths: AI for speed, pattern recognition, and scale; humans for judgment, context, and accountability. The best systems are explicit about what AI should and shouldn’t do.
Iterate
Iteration is where performance comes from: better prompts, better evaluation, better workflows. In most real deployments, the “secret sauce” is the loop—humans shaping AI behavior over time.
Mediate
Mediation is the human‑world interface: verification, escalation paths, quality metrics, and governance. It’s how teams prevent failure modes and maintain trust.