Four competencies, three interaction modes, six prompting techniques. A practical model for how knowledge workers get from knowing about AI to using it well in their daily work.
The phrase “AI literacy” gets used a lot. It means almost nothing, because it conflates knowing what an AI is with being any good at using one. Fluency is the more useful word. Fluency means you can do work with an AI that you couldn’t do without one, reliably, in your own context.
The framework has three layers.
The four competencies
Fluency is the intersection of four skills, none of which can substitute for the others.
Delegation. Knowing what to give the AI in the first place. The fluent user has internalized which kinds of tasks return signal and which return slop, and matches the tool to the task.
Description. Specifying the work clearly enough that the model can do it. This is the deeper version of the prompt-engineering skill: writing a clear spec for the work.
Discernment. Reading the output critically. Catching hallucinations, recognizing plausible-but-wrong answers, knowing when to push back and when to accept.
Diligence. Closing the loop. Verification, attribution, the small disciplines that turn a draft into a defensible artifact.
A team that’s strong on description but weak on discernment ships confident garbage. A team that’s strong on discernment but weak on delegation never starts.
The three interaction modes
Fluent users move between three modes deliberately:
Automation. The AI does the task end-to-end, and the human checks the output. Best for high-volume, low-stakes work with clear quality criteria.
Augmentation. The human and the AI co-produce the work in turns. Best for thinking work where the human’s judgment is the bottleneck.
Agentic. The AI takes multi-step actions in the world (tools, files, APIs), and the human supervises the trajectory. Best for processes where the steps are well-defined but tedious.
Most people get stuck in one mode and try to use it for everything. Fluency means moving between the three modes on purpose.
The prompt formula and six techniques
The base formula: role + task + context + format + constraints. Six techniques layer on top: chain-of-thought, few-shot, self-critique, decomposition, structured output, and tool use. Fluent users pick the technique that fits the failure mode in front of them.
The whole framework exists because most “AI training” teaches the techniques without teaching the underlying competencies. People walk out of those sessions able to copy a prompt template and unable to recover when the template doesn’t work. The competencies are what let them recover.
Synthesized from Anthropic Academy material (March 2026) and tested against L&D consulting practice.