Summary

A two-part prompt that first restructures a complex task into an AI-executable sequence, then deploys AI as the primary executor with human judgment flagged only at decision points. Based on the structural pattern behind the 11.4x productivity reduction documented in March 2026 research on complex task completion.

When to Use

Before starting any project that involves multiple steps, multiple tools, or multiple outputs. Use this instead of prompting AI directly at each stage.

Best Input

A clear description of the end goal and the tools or systems available in your workflow. The more specific the goal, the cleaner the subtask breakdown.

The Prompt

Step 1 -- Restructure the task first:

I need to complete the following: [describe your goal]. Break this into a sequence of subtasks where each subtask has: (1) a defined input, (2) a defined output, (3) a clear decision point where human judgment is required. Flag which subtasks AI can execute independently and which require my input before proceeding.

Step 2 -- Deploy AI as executor:

You are operating as my workflow assistant. Complete the task sequence we defined from start to finish. Document each step you take. Stop at every decision point we identified and wait for my input before proceeding. Do not make judgment calls on client preference, contractual constraints, or context only I have access to. Begin with: [first subtask].

How to Use

Run Step 1 first and review the subtask breakdown before starting Step 2. The decision-point flags in Step 1 are what keeps your judgment in the loop without requiring supervision at every step.

Strong Output

A numbered subtask list from Step 1 with clear input/output pairs and flagged decision points. A complete execution log from Step 2 with documented steps and decision stops where your input is requested.

Common Mistakes

Skipping Step 1 and going straight to execution. The restructuring is what produces the 11x gain. Without it, you are using AI as a drafting tool, not a system.

Operator Insight

Most operators are capturing 1.5-2x gains because they prompt AI at each step rather than handing it the full sequence. The structural work in Step 1 is what converts AI from assistant to executor.