Executable Experience Model

When execution is no longer the bottleneck, learning happens by making, not by planning forever.

Workflows still assume making is slow, expensive, and risky.

Double Diamond and similar models earned their place. They assume learning must happen through planning and alignment before anything real ships.

That assumption is breaking. AI-assisted execution collapses the cost of making. The workflow has to change with it.

“When execution is no longer the bottleneck, the workflow itself has to change.”
AI-enabled
Traditional
Drag to compare · Execution absorbs uncertainty · Production commits to validated solutions

Five stages. One learning loop.

Uncertain inputs move through execution into judged solutions, then deliberate production. Not a waterfall: a governed cycle.

EEM five-stage model: Input, Execute, Solution, Governance Gate, Production
  1. 01
    Input

    Variable quality, incomplete, and actionable, including design-system constraints.

  2. 02
    Execute

    The heart. Uncertainty collapses through making, not planning. Designers direct AI agents so stakeholders react to real options.

  3. 03
    Solution

    Multiple validated variants: realized strategy examples ready for judgment.

  4. 04
    Governance

    Human judgment selects what advances. Non-negotiable; format is yours.

  5. 05
    Production

    Deliberate commitment to ship, not the default outcome of activity.

Read the five-stage model Read the Execute stage

Built in four hours.

One sentence concept. ChatGPT, Figma, and Cursor. A functional Wealthsimple goals prototype ready for validation and handoff. Not theater.

Input
One sentence concept
Tools
ChatGPT · Figma · Cursor
Output
Testable prototype

Open the prototype See case evidence

Clarity before you rebuild the workflow.

If this names something real in your organization, book a free 90-minute discovery. No pitch. Just a sharper next move.

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