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A stray AI editing note in a legislative speech shows why exploration, production and delivery need clear boundaries.
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Two Prune uses realistic work simulations to produce structured assessment evidence—not automated employment decisions.
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3 August 2026 · 3 min read
Her assessment revealed a workflow shaped by early corporate AI training: use AI to write, then manually check everything.

28 July 2026 · 5 min read
Two Prune is beginning a research programme—and inviting academic collaboration—to develop task-bounded AI-fluency assessment into a responsible measurement method.

Research with 319 knowledge workers found that using generative AI shifts critical-thinking effort away from direct execution and toward activities such as verification, integration and oversight.2 In other words, once AI helps produce the work, controlling the workflow becomes part of the work.
This is why AI fluency cannot be inferred from prompt technique or a polished output alone. It also depends on whether someone can frame the task, choose the right role for AI, keep working material separate from final material, verify the result and control what gets delivered.
Two Prune uses timed, realistic work simulations to create structured evidence of those behaviours across Context Framing, Evidence Navigation, AI Orchestration, Verification & Risk Control, Judgment & Synthesis, and Communication & Delivery. The resulting evidence is task-bounded and intended for human interpretation.
The question for organisations is no longer only whether people can get useful answers from AI. It is whether they can manage the transitions between thinking with AI and delivering work they are prepared to own.
21 July 2026 · 3 min read
A participant case note showing why a strong AI-assisted synthesis still needs a separate, deliberately sceptical verification pass against its sources.