Dt Methods
MicrosoftOfficialPublished by Microsoft
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- Business and productivity
- MIT
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Written by AutoGineer from the skill’s own files, not by the author
The dt-methods skill provides a structured reference system for AI agents to coach teams through the Design Thinking process. It organizes guidance into three layers: core method references for day-to-day activities, deep references for advanced facilitation and recovery, and industry-specific context to tailor vocabulary and constraints. The skill covers nine major industries, including energy, healthcare, and financial services, ensuring that coaching is grounded in the specific operational realities and regulatory environments of the user's sector.
What it does
- Provides step-by-step guidance for nine core Design Thinking methods.
- Offers advanced facilitation techniques and recovery strategies for complex scenarios.
- Maps Design Thinking concepts to industry-specific terminology and constraints.
- Integrates telemetry expectations for session artifacts to ensure observable outcomes.
- Supplies industry-specific empathy tools and stakeholder considerations.
- Supports tailoring of coaching based on the active method and identified industry context.
When to use it
- When facilitating a Design Thinking session and requiring method-specific guidance.
- When a team needs advanced troubleshooting or recovery techniques during a workshop.
- When applying Design Thinking within a specific industry to ensure relevant vocabulary and constraints are respected.
- When defining telemetry or audit trails for Design Thinking session artifacts.
Advantages
- Ensures consistent coaching across the entire Design Thinking lifecycle.
- Reduces friction by using industry-appropriate language and concepts.
- Provides a clear path for scaling from basic methods to advanced facilitation.
- Integrates operational and regulatory awareness into the design process.
Usage examples
- “How should I facilitate a brainstorming session for a team in the energy sector?”
- The agent will load the brainstorming method reference and the energy industry context, providing guidance that uses energy-specific terms like 'reliability concern' and 'forced outage rate' while emphasizing safety and regulatory constraints.
- “We are stuck during the user research phase; what advanced techniques can we use?”
- The agent will access the deep reference for the Design Research method to provide advanced facilitation strategies and recovery techniques to help the team overcome their current roadblock.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/dt-methods/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip dt-methods.zip -d .agents/skills
Documentation by Microsoft
Design Thinking Methods Skill
Entrypoint for Design Thinking method coaching knowledge. The dt-coach agent loads the method reference matching the active method in coaching state, the matching deep reference when advanced technique is needed, and the industry reference when an industry context applies.
How to use this skill
Read the method reference for the method currently active in coaching state to ground day-to-day coaching.
Read the matching deep reference when the conversation needs advanced facilitation, recovery techniques, or expert frameworks beyond the core method guidance.
Read the industry reference when the team has identified one of the nine covered industries as their context, and weave its vocabulary, constraints, and empathy tools into method-specific guidance.
Read dt-coach-telemetry.md when DT session artifacts need observable telemetry expectations grounded in
telemetry-foundations.
Method references
| Method | Name | Core reference | Deep reference |
|---|---|---|---|
| 1 | Scope Conversations | method-01-scope.md | method-01-deep.md |
| 2 | Design Research | method-02-research.md | method-02-deep.md |
| 3 | Input Synthesis | method-03-synthesis.md | method-03-deep.md |
| 4 | Brainstorming | method-04-brainstorming.md | method-04-deep.md |
| 5 | User Concepts | method-05-concepts.md | method-05-deep.md |
| 6 | Low-Fidelity Prototypes | method-06-lofi-prototypes.md | method-06-deep.md |
| 7 | High-Fidelity Prototypes | method-07-hifi-prototypes.md | method-07-deep.md |
| 8 | User Testing | method-08-testing.md | method-08-deep.md |
| 9 | Iteration at Scale | method-09-iteration.md | method-09-deep.md |
Industry context references
Load the matching reference when the team identifies its industry context.
| Reference | When to load |
|---|---|
| industry-energy.md | Energy-sector vocabulary, constraints, empathy tools, and reference scenario. |
| industry-financial-services.md | Financial services vocabulary, constraints, empathy tools, and reference scenario. |
| industry-healthcare.md | Healthcare vocabulary, constraints, empathy tools, and reference scenario. |
| industry-manufacturing.md | Manufacturing vocabulary, constraints, empathy tools, and reference scenario. |
| industry-nonprofit-social-impact.md | Nonprofit and social impact vocabulary, constraints, empathy tools, and reference scenario. |
| industry-pharmaceuticals-life-sciences.md | Pharmaceuticals and life sciences vocabulary, constraints, empathy tools, and reference scenario. |
| industry-professional-services.md | Professional services vocabulary, constraints, empathy tools, and reference scenario. |
| industry-public-sector.md | Public sector and government vocabulary, constraints, empathy tools, and reference scenario. |
| industry-retail-cpg.md | Retail and consumer goods vocabulary, constraints, empathy tools, and reference scenario. |
Skill layout
.
├── SKILL.md
└── references/
├── method-01-scope.md
├── method-01-deep.md
├── method-02-research.md
├── method-02-deep.md
├── method-03-synthesis.md
├── method-03-deep.md
├── method-04-brainstorming.md
├── method-04-deep.md
├── method-05-concepts.md
├── method-05-deep.md
├── method-06-lofi-prototypes.md
├── method-06-deep.md
├── method-07-hifi-prototypes.md
├── method-07-deep.md
├── method-08-testing.md
├── method-08-deep.md
├── method-09-iteration.md
├── method-09-deep.md
├── industry-energy.md
├── industry-financial-services.md
├── industry-healthcare.md
├── industry-manufacturing.md
├── industry-nonprofit-social-impact.md
├── industry-pharmaceuticals-life-sciences.md
├── industry-professional-services.md
├── industry-public-sector.md
├── industry-retail-cpg.md
└── dt-coach-telemetry.mdFiles
- ATTRIBUTION.mdAdded by AutoGineer871 B
- LICENSELicence file added by AutoGineer1.1 KiB
- SKILL.md6.5 KiB
- references/dt-coach-telemetry.md1.5 KiB
- references/industry-energy.md9.1 KiB
- references/industry-financial-services.md10.7 KiB
- references/industry-healthcare.md7.7 KiB
- references/industry-manufacturing.md6.7 KiB
- references/industry-nonprofit-social-impact.md15.6 KiB
- references/industry-pharmaceuticals-life-sciences.md20.1 KiB
- references/industry-professional-services.md14.0 KiB
- references/industry-public-sector.md12.1 KiB
- references/industry-retail-cpg.md16.5 KiB
- references/method-01-deep.md10.4 KiB
- references/method-01-scope.md10.2 KiB
- references/method-02-deep.md15.6 KiB
- references/method-02-research.md7.0 KiB
- references/method-03-deep.md13.9 KiB
- references/method-03-synthesis.md8.9 KiB
- references/method-04-brainstorming.md13.6 KiB
- references/method-04-deep.md16.5 KiB
- references/method-05-concepts.md17.1 KiB
- references/method-05-deep.md17.7 KiB
- references/method-06-deep.md16.3 KiB
- references/method-06-lofi-prototypes.md17.2 KiB
- references/method-07-deep.md10.9 KiB
- references/method-07-hifi-prototypes.md9.8 KiB
- references/method-08-deep.md15.0 KiB
- references/method-08-testing.md11.5 KiB
- references/method-09-deep.md17.2 KiB
- references/method-09-iteration.md11.9 KiB
references/method-06-lofi-prototypes.md
title: 'DT Method 06: Low-Fidelity Prototypes' description: Design Thinking Method 06 (Low-Fidelity Prototypes) for building quick, testable artifacts to learn fast.
Method 6 makes concepts tangible through rapid, intentionally rough prototypes that test core assumptions before investment. Without lo-fi prototyping, teams invest heavily in building solutions before discovering fundamental constraints that cheap experiments would have revealed.
Method 6 is the final method in the Solution Space. Completion produces tested prototypes with documented constraint discoveries, narrowing to 1-2 directions for Method 7's high-fidelity implementation.
Purpose
Transform validated concepts from Method 5 into scrappy, testable prototypes that discover physical, environmental, and workflow constraints through real-environment testing with diverse users.
Coaching Identity Extension
Method 6 extends the foundational dt-coaching-foundation coaching-identity Think/Speak/Empower framework with prototyping-specific guidance:
Think: Assess prototype fidelity levels, assumption clarity, and testing readiness. Recognize when prototypes drift toward over-polish or when testing strategy lacks rigor.
Speak: Share observations about fidelity drift, assumption coverage, and feedback quality. "This prototype looks pretty complete, what's the one assumption it tests?" or "Before refining this further, have we shown it to anyone outside the team?"
Empower: Offer choices between building another prototype variation or testing what exists. Close with agency-preserving options about prototype direction.
Coaching Hats
Two specialized coaching hats provide focused expertise within Method 6. The coach switches hats based on activation triggers detected in user conversation.
Prototype Builder
Construction and enforcement expertise. Guides concept-to-prototype translation, variation generation, and fidelity enforcement.
Activation triggers:
User analyzes concepts from Method 5 for prototyping.
User plans or builds prototype approaches.
User asks about materials, formats, or prototype scope.
User produces an artifact that looks over-polished for lo-fi stage.
User fixates on a single prototype approach without generating alternatives.
Coaching focus:
Concept-to-prototype translation: identify the core assumption in each concept and design the simplest artifact that tests it.
Multiple approach generation: facilitate generating 3-5 prototype variations per concept using different formats and interaction modes.
Scrappy enforcement: redirect polished artifacts back to rough drafts and apply Progressive Hint Engine for "Too Nice Prototype" escalation.
Material and format selection: match prototype type to assumption category (paper, cardboard, markdown stub, conversation script).
Single-assumption focus: each prototype tests exactly one core belief, not multiple hypotheses.
Build-time constraint: minutes to hours, not days.
Feedback Designer
Testing strategy and observation expertise. Guides hypothesis-driven question design, participant selection, and structured result capture.
Activation triggers:
User plans testing strategy or selects test participants.
User writes questions for prototype feedback sessions.
User reports vague or surface-level feedback results.
User tests only with accommodating or friendly participants.
User asks how to capture or analyze prototype test results.
Coaching focus:
Hypothesis-driven question design: frame each test around a specific assumption with leap-enabling questions rather than opinion requests.
User selection strategy: include edge-case users, stressed users, and varying skill levels rather than only accommodating testers.
Real-environment testing: test where the solution will actually be deployed, not in lab conditions.
Behavioral observation over opinion: watch what users do, capture hesitations and workarounds, not just verbal responses.
Response capture format: structured observation templates documenting assumption tested, behavior observed, constraints discovered, and severity.
Constraint pattern analysis: identify recurring barriers across multiple test sessions for Method 7 handoff.
Sub-Method Phases
Method 6 organizes into three sequential phases. Each phase produces distinct artifacts and activates different coaching behaviors. Phases 2 and 3 often interleave as teams build-test-iterate. During interleaved work, Feedback Designer takes precedence when live user testing is active; Prototype Builder resumes when the coach returns to building or revising prototypes.
Phase 1: Prototype Planning
Analyze concepts from Method 5 and design prototype approaches before building. Identify core assumptions and select formats.
Activities:
Concept analysis from Method 5.
Core assumption identification per concept.
Prototype approach brainstorming (3-5 formats per concept).
Material and format selection.
Test user identification.
Environment mapping for real-world testing.
Exit criteria:
Each concept has at least one identified core assumption.
Multiple prototype approaches documented with materials selected.
Test users identified with environment requirements noted.
AI pattern: Silent Observer, processes inputs and provides convergent synthesis without directing, for processing Method 5 concept inputs and generating prototype approach variations.
Coaching hat: Prototype Builder.
Phase 2: Prototype Building
Build scrappy prototypes using selected formats. Enforce deliberate roughness and single-assumption focus.
Activities:
Build prototypes using selected formats.
Enforce build-time constraint (minutes to hours).
Generate competing variations.
Apply lo-fi enforcement rules.
Iterate rapidly between build-test-learn cycles.
Exit criteria:
3-5 prototype variations exist per concept, each testing one core assumption.
All prototypes use deliberately rough materials and formats.
Build time per prototype stays within minutes-to-hours range.
AI pattern: Backup Generator, intervenes during energy stalls while preserving human momentum, for producing alternative prototype approaches when the team fixates on one format.
Coaching hat: Prototype Builder (primary), Feedback Designer activates when user begins informal testing during build.
Phase 3: Feedback Planning
Design and execute hypothesis-driven testing with real users in real environments. Capture structured observations and prepare Method 7 handoff.
Activities:
Hypothesis-driven test plan creation.
Leap-enabling question design.
Participant selection (edge cases, stress conditions, skill diversity).
Real-environment test execution.
Behavioral observation.
Structured result capture.
Constraint pattern identification across sessions.
Severity assessment.
Constraint pattern documentation in
constraint-discoveries.md.Method 7 handoff preparation.
Exit criteria:
Prototypes tested with real users in real environments.
Constraint discoveries documented across physical, environmental, and workflow categories.
Assumptions explicitly validated or invalidated with evidence.
Narrowed to 1-2 directions for Method 7 handoff.
AI pattern: Silent Observer, processes inputs and provides convergent synthesis without directing, for constraint pattern analysis across test sessions.
Coaching hat: Feedback Designer.
Reverse-transitions: return to Phase 1 when testing reveals untested assumption categories. Return to Phase 2 when testing reveals insufficient prototype diversity or when a new approach is needed.
Lo-Fi Enforcement Mechanisms
Lo-fi enforcement is the defining characteristic of Method 6. Every coaching intervention reinforces deliberate roughness.
Build constraints: minutes to hours, not days. Paper, cardboard, simple tools. Each prototype tests one core assumption. If build time exceeds a few hours, the prototype is too polished.
Scrappy principle: deliberately rough materials prevent feedback on aesthetics rather than functionality. Rough artifacts invite structural criticism; polished artifacts invite cosmetic criticism.
"Too Nice Prototype" escalation uses the Progressive Hint Engine:
Level 1 (Broad): "This looks pretty complete. What's the one assumption it tests?"
Level 2 (Contextual): "Before refining the wording, want to check whether [stakeholder] would use this interaction pattern?"
Level 3 (Specific): "This formatting looks production-ready, but we haven't tested whether users need [section]. Strip it back to the core interaction?"
Level 4 (Direct): "This has crossed into implementation territory. Create a new rough artifact testing only [assumption], and save this version for Method 7."
AI Artifact Enforcement
AI prototype artifacts (markdown files) look identical to production artifacts. Enforcement relies on content completeness, tooling usage, and time invested rather than material roughness.
Fidelity boundary: an environment with model invocation crosses into Method 7 territory. Human-simulated examples without model execution remain Method 6.
Prototype Types
Physical Prototypes
| Type | What It Tests | Materials | Build Time |
|---|---|---|---|
| Paper Prototyping | Information shape, layout | Paper, markers, sticky notes | 15-60 min |
| Cardboard | Physical form, spatial layout | Cardboard, tape, tools | 1-4 hours |
| Wizard of Oz | Interaction patterns | Scripts, human simulation | 30-90 min |
| Role Playing | Clarity for non-authors | People, scenario scripts | 15-45 min |
| Storyboarding | User journey, sequence | Paper, markers | 30-60 min |
AI-Assisted Prototypes
| Traditional | AI/HVE Equivalent | What It Tests | Lo-Fi Signals |
|---|---|---|---|
| Paper Prototype | Markdown document prototype | Information shape | No frontmatter, no linting, no formatting |
| Storyboarding | User journey narrative | Conversation flow | Plain prose numbered list, no diagrams |
| Wizard of Oz | Human-simulated AI response | Output usefulness | Human-written in <15 min, no model call |
| Role Playing | Stakeholder perspective sim | Clarity for non-authors | No test framework, people reading files |
| Cardboard | Stub agent files | Information architecture | Placeholder content, TODO markers |
Feedback Planning
Every test session begins with a stated hypothesis: "We believe [stakeholder] needs [capability] because [evidence]."
Leap-Enabling Questions
| Category | Pattern | Example |
|---|---|---|
| Behavioral walk-through | "Walk me through how you would..." | "Walk me through how you'd use this when the machine acts up" |
| Barrier discovery | "What would prevent you from..." | "What would prevent you from using this during typical work?" |
| Environmental fit | "Does this work in..." | "Does this work in the actual environment where it's used?" |
| Workflow integration | "When and how does this fit..." | "When does this fit into your current work process?" |
| Observable interaction | "Show me how..." | "Show me how you would interact with this" |
Avoid leap-killing patterns: "Do you like...?" generates agreement without insight. "What do you think?" elicits surface opinion. "Is this useful?" produces binary responses with no constraint data.
Observation Capture Template
Hypothesis: [assumption being tested]
Prototype: [which variation, format]
Participant: [role, context, edge-case category]
Environment: [where tested, conditions]
Observed behavior: [what user did, hesitations, workarounds]
Constraint discovered: [physical / environmental / workflow]
Severity: [blocker / friction / minor]
Assumption status: [validated / invalidated / inconclusive]Capture observations in test-observations.md; see Artifacts for file paths and storage.
Quality Standards
Lo-Fi Fidelity
Prototypes remain deliberately rough, testing assumptions not aesthetics. When users begin over-detailing, apply the "Too Nice Prototype" escalation.
Single-Assumption Testing
Each prototype tests one core belief. Testing multiple assumptions simultaneously produces ambiguous results that cannot inform Method 7.
Real-Environment Validation
Prototypes are tested where solutions will actually be deployed, not in artificial lab conditions that mask real-world constraints.
Behavioral Evidence
Observations capture what users do (hesitations, workarounds, abandonment) rather than what users say they would do.
Multiple Variations
Generate 3-5 prototype variations per concept. Fewer than 3 risks single-prototype fixation. More than 5 suggests insufficient assumption focus.
Prototyping Goals
Accomplish
Constraint discovery: every prototype session surfaces at least one physical, environmental, or workflow barrier.
Multiple variations: test 3-5 approaches per concept to avoid single-prototype fixation.
Scrappy fidelity: all artifacts stay deliberately rough, testing assumptions not aesthetics.
Real-environment testing: prototypes are tested where solutions will actually be deployed.
Hypothesis-driven feedback: every test session has a stated assumption and structured observation.
Avoid
Over-polishing: detailed prototypes that invite aesthetic feedback instead of functional discovery.
Friendly-user bias: testing only with accommodating participants who confirm assumptions.
Single-prototype fixation: investing in one approach without generating competing alternatives.
Lab-condition testing: testing in artificial environments that mask real-world constraints.
Opinion-driven feedback: collecting "do you like it?" responses instead of behavioral observation.
Success Indicators
During Prototyping
Multiple prototype formats generated per concept (3-5 variations).
Build time per prototype stays within minutes-to-hours range.
Each prototype targets one core assumption.
Test sessions use leap-enabling questions with behavioral observation.
Prototypes tested in real environments with diverse users.
After Prototyping
Constraint discoveries documented across physical, environmental, and workflow categories.
Assumptions explicitly validated or invalidated with behavioral evidence.
Narrowed to 1-2 directions for Method 7 handoff.
Feedback Designer observation templates completed for each test session.
Method 6 Completion
Method 6 is complete when:
3-5 prototype variations tested per concept with real users in real environments.
Constraint discoveries documented across physical, environmental, and workflow categories with severity assessment.
Assumptions explicitly validated or invalidated with behavioral evidence.
Narrowed to 1-2 directions with
constraint-discoveries.mdprepared for Method 7 handoff.
Input from Method 5
Prioritized user concepts with core value propositions
Stakeholder alignment on which concepts to prototype
Concept selection rationale and evaluation criteria
Environmental and workflow context from earlier methods
Output to Method 7
Physical, environmental, and workflow constraint discoveries as technical requirements
Validated interaction approaches as implementation specifications
Assumption testing results indicating which core beliefs were proven or disproven
User behavior patterns observed during real-environment prototype testing
See constraint-discoveries.md in the Artifacts section for handoff format.
Artifacts
Create and maintain Method 6 prototyping artifacts under the folder:
.copilot-tracking/dt/{project-slug}/method-06-lofi-prototypes/
Within this folder, produce and update these files:
.copilot-tracking/dt/{project-slug}/method-06-lofi-prototypes/prototype-plan.mdDocument concept analysis, assumptions identified, prototype approaches selected, materials and formats, and test user profiles..copilot-tracking/dt/{project-slug}/method-06-lofi-prototypes/prototype-variations.mdCapture 3-5 prototype variations per concept with format, assumption tested, and build notes..copilot-tracking/dt/{project-slug}/method-06-lofi-prototypes/feedback-plan.mdDocument hypothesis-driven test plans with leap-enabling questions, participant selection, and environment requirements..copilot-tracking/dt/{project-slug}/method-06-lofi-prototypes/test-observations.mdCapture structured observation data per test session using the response capture template..copilot-tracking/dt/{project-slug}/method-06-lofi-prototypes/constraint-discoveries.mdDocument cross-session constraint patterns with severity assessment, categorized by physical, environmental, and workflow, with Method 7 handoff notes.All DT coaching artifacts are scoped to
.copilot-tracking/dt/{project-slug}/. Never write DT artifacts directly under.copilot-tracking/dt/without a project-slug directory.
Requirements and compatibility
Written for: GitHub Copilot, Claude Code
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Claude Code frontmatter
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- Published by
- Microsoft
- Publisher
- Microsoft (Official)
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- microsoft/hve-core · .github/skills/design-thinking/dt-methods · commit f425e94
- Licence
- MIT License (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- ATTRIBUTION.md (written by AutoGineer)
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