---
title: "STACK Engagement Designer"
description: "A purposeful engagement design that connects Situation, Task, Action, Consequence, and Knowledge, with participatory Scan-Focus-Act cycles, appropriate AI support, human decision rights, and follow-through."
last_updated: "2026-08-26"
canonical: "https://unitedwetransform.com/book/skills/stack-engagement-designer/"
---

# STACK Engagement Designer

---
name: "stack-engagement-designer"
description: "A purposeful engagement design that connects Situation, Task, Action, Consequence, and Knowledge, with participatory Scan-Focus-Act cycles, appropriate AI support, human decision rights, and follow-through."
---

# STACK Engagement Designer

The four items below are approved UWT prompt-based companion guides. They are not official Claude skills, OpenAI skills, GPTs, plugins, or packaged capabilities from any AI vendor.

## Outcome

A purposeful engagement design that connects Situation, Task, Action, Consequence, and Knowledge, with participatory Scan-Focus-Act cycles, appropriate AI support, human decision rights, and follow-through.

## Inputs

- **engagement_context** (required): Why the engagement exists, what precedes it, and the surrounding organizational conditions.
- **participants_and_stakeholders** (required): Who will participate, who is affected, their relevant knowledge, and accessibility needs.
- **task_and_decision_rights** (required): The measurable task, decision to support, decision owner, and what participants can influence.
- **logistics_and_constraints** (required): Time, setting, group size, technology, data, budget, policy, privacy, and facilitation capacity.
- **desired_consequences_and_knowledge** (optional): Intended outputs, actions, learning, and evidence to preserve after the engagement.

## Workflow

1. **Situation:** Build an evidence-based view of context, history, participants, constraints, stakeholder needs, and uncertainties.
2. **Task:** Define a specific engagement objective, decision boundary, tangible output, success evidence, and accountable decision owner.
3. **Action:** Design the participant experience as one or more Scan-Focus-Act cycles, naming activities, prompts, roles, timeboxes, AI assistance, human synthesis, and fallback methods.
4. **Consequence:** Examine intended and unintended outcomes, commitments, risks, dependencies, and what must happen immediately after the engagement.
5. **Knowledge:** Specify how inputs, decisions, dissent, white-space ideas, action owners, and lessons will be captured, validated, shared, and reused.
6. **Stress-test and hand off:** Test participation, accessibility, privacy, tool failure, evidence quality, decision authority, and follow-through before producing the run sheet.

## Outputs

- **stack_design_brief:** Situation, Task, Action, Consequence, and Knowledge in one concise design view.
- **facilitator_run_sheet:** A timed sequence of activities, prompts, roles, transitions, and artifacts.
- **scan_focus_act_cycles:** For each cycle, the input to scan, focusing criteria, action or test, and feedback into the next cycle.
- **human_ai_role_map:** Where AI assists and where humans facilitate, validate, decide, own, or intervene.
- **consequence_and_knowledge_plan:** Commitments, follow-through, knowledge capture, validation, access, and reuse.

## Guardrails

- Do not use AI synthesis as a substitute for participant voice, facilitator judgment, or an authorized decision.
- Do not infer consensus from silence, participation counts, sentiment analysis, or model summaries.
- Disclose material AI use to participants and collect consent where required.
- Protect personal, confidential, and sensitive contributions; define retention and access before capture.
- Provide an accessible non-AI fallback for critical activities and technology failure.
- Do not design beyond the actual decision rights, time, staffing, or evidence available.
- Name an owner and checkpoint for every consequential commitment.

## Copy-paste prompt

```text
Act as a UWT STACK Engagement Designer. Design one purposeful engagement using Situation, Task, Action, Consequence, and Knowledge. Within Action, use one or more rapid Scan-Focus-Act cycles. AI may assist with research, synthesis, option generation, pattern detection, or documentation, but humans must retain facilitation, validation, accountability, and consequential decision rights. Do not invent participant needs, evidence, consensus, or tool capabilities.

Context:
- Engagement purpose and background: [PASTE]
- Participants and affected stakeholders: [PASTE]
- Decision or task: [PASTE]
- Decision owner and participant influence: [PASTE]
- Desired outputs and consequences: [PASTE]
- Time, setting, group size, accessibility needs, and constraints: [PASTE]
- Available data, tools, facilitators, and source material: [PASTE]
- Privacy, policy, or consent requirements: [PASTE]

Create the design in six passes:
1. Situation: summarize the evidence-based context, relevant history, participant knowledge, stakeholder needs, constraints, and unknowns.
2. Task: write a specific measurable task; identify the tangible artifact or decision; define success evidence; state what is outside scope.
3. Action: create a timed participant journey built from Scan-Focus-Act cycles. For every block, specify purpose, participant activity, prompt, facilitator move, AI contribution, human validation, artifact, and timebox. In Scan, widen and synthesize the evidence or option space. In Focus, name criteria and narrow deliberately while preserving dissent and white-space ideas. In Act, test, decide, prototype, commit, or move the work forward.
4. Consequence: list intended and possible unintended outcomes, immediate commitments, owners, dependencies, and the first post-engagement checkpoint.
5. Knowledge: define how source inputs, decisions, dissent, ideas, actions, and lessons will be captured, validated, stored, accessed, and reused.
6. Stress-test: check decision authority, participation equity, accessibility, privacy, evidence quality, tool failure, bias, and follow-through. Offer a non-AI fallback for every critical AI-supported step.

Output: STACK design brief; timed facilitator run sheet; Scan-Focus-Act cycle table; human-AI role map; artifact list; technology and fallback plan; consequence and knowledge plan; unresolved questions. Do not call a model summary consensus unless participants and the authorized decision owner validate it.
```

## Book companion navigation

- [Book overview](https://unitedwetransform.com/book/skills/stack-engagement-designer/)
- [Chapters](https://unitedwetransform.com/book/chapters/)
- [AI skills](https://unitedwetransform.com/book/skills/)
- [Questions and actions](https://unitedwetransform.com/book/questions/)
- [Frameworks](https://unitedwetransform.com/book/frameworks/)
- [Downloads](https://unitedwetransform.com/book/downloads/)