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Create the manufacturing industry context template, the first of three P0 industry templates for the DT coaching system. This template provides manufacturing-specific vocabulary, constraints, empathy tools, and reference scenarios that the coach loads alongside method instructions to tailor DT coaching for manufacturing contexts.
Manufacturing is the primary industry context with the richest source material: DT4HVE's 130+ manufacturing references and the validated manufacturing reference scenario.
Decision cadence: Shift-level (8-12 hours), production planning (weekly), capital investment (quarterly/annual)
Regulatory environment: OSHA, ISO 9001/14001, industry-specific standards (FDA for pharma manufacturing, IATF 16949 for automotive)
Vocabulary Mapping
Map DT concepts to manufacturing language:
DT Concept
Manufacturing Language
Stakeholder map
RACI chart / Responsibility matrix
Pain point
Downtime cause / Production bottleneck
User journey
Production workflow / Value stream
Prototype
Pilot run / Trial batch / Proof of concept
Iteration
Continuous improvement / Kaizen cycle
Empathy
Gemba walk / Operator perspective
Constraints and Considerations
Safety-first culture: Any DT activity must respect safety protocols; research observations require PPE compliance and designated observation areas
Shift-based operations: Stakeholders may be unavailable during certain hours; research must span shifts to capture different behaviors
Union considerations: Stakeholder engagement may require union representative inclusion
Data sensitivity: Production data, efficiency metrics, and incident reports may have access restrictions
Physical environment: DT activities may need adaptation for factory floor noise, space, and cleanliness requirements
Empathy Tools
Gemba walk framework: Structured observation on the factory floor, what to look for, how to engage respectfully with operators
Shift handoff observation: Watch shift transitions to identify information loss, miscommunication, and workaround patterns
Operator shadow protocol: Follow an operator through a shift to understand their actual (vs. documented) workflow
Safety incident narrative: Use anonymized incident reports as empathy artifacts, what led to the incident, what was the operator's experience
Reference Scenario
Manufacturing reference scenario adapted from DT4HVE research:
Context: Production line experiencing quality variance across shifts
Stakeholders: Day shift operators, night shift operators, quality engineers, shift supervisors
Discovery: Root cause is not equipment or process, it's information asymmetry between shifts
DT Journey: Methods 1-3 reveal the human factors; Methods 4-6 generate solutions for knowledge transfer; Methods 7-9 pilot and iterate
Token Budget
Target: ~1,500-2,000 tokens (on-demand tier, loaded when industry context is manufacturing)
Source Material
Attach these files as context for the task-researcher phase:
DT4HVE guidance files (all 9): design-thinking-for-hve-capabilities/guidance/01-scope-conversations.md through 09-iteration-at-scale.md, 130+ manufacturing references spread across all methods
Cumulative research: Design Thinking cumulative research, Part 7 (cross-industry strategy) for Industry Context Layer architecture and manufacturing parameterization patterns
RPI Pipeline Workflow
task-researcher: Deep dive into DT4HVE manufacturing references, extract vocabulary, constraints, empathy patterns, and the reference scenario. Cross-reference cumulative research Part 7 (cross-industry strategy).
task-planner: Plan the template, industry profile, vocabulary mapping, constraints, empathy tools, reference scenario.
task-implementor: Author following prompt-builder standards. Nativize DT4HVE manufacturing content for HVE Core. Ensure vocabulary mapping is bidirectional (DT→manufacturing and manufacturing→DT).
Research: /task-research — "Deep dive into DT4HVE manufacturing references — extract vocabulary mappings, constraints, empathy patterns, and the reference scenario. Attach all guidance files (01-09) and cumulative research Part 7 as context."
Overview
Create the manufacturing industry context template, the first of three P0 industry templates for the DT coaching system. This template provides manufacturing-specific vocabulary, constraints, empathy tools, and reference scenarios that the coach loads alongside method instructions to tailor DT coaching for manufacturing contexts.
Manufacturing is the primary industry context with the richest source material: DT4HVE's 130+ manufacturing references and the validated manufacturing reference scenario.
Target File
.github/instructions/dt-industry-manufacturing.instructions.mdFrontmatter
Note:
applyTois empty, loaded on-demand when the user specifies manufacturing as their industry context.Required Content
Industry Profile
Vocabulary Mapping
Map DT concepts to manufacturing language:
Constraints and Considerations
Empathy Tools
Reference Scenario
Manufacturing reference scenario adapted from DT4HVE research:
Token Budget
Target: ~1,500-2,000 tokens (on-demand tier, loaded when industry context is manufacturing)
Source Material
Attach these files as context for the task-researcher phase:
design-thinking-for-hve-capabilities/guidance/01-scope-conversations.mdthrough09-iteration-at-scale.md, 130+ manufacturing references spread across all methods01-scope-conversations.md(L57),03-input-synthesis.md(L59),04-brainstorming.md(L50),05-user-concepts.md(L50),06-low-fidelity-prototypes.md(L61),07-high-fidelity-prototypes.md(L155),08-user-testing.md(L68),09-iteration-at-scale.md(L52)RPI Pipeline Workflow
Starter Prompts
Prompt-Builder Compliance Checklist
Per
.github/instructions/prompt-builder.instructions.md:description:frontmatter present and descriptiveapplyTo: ''(empty, on-demand loading)Success Criteria
.github/instructions/dt-industry-manufacturing.instructions.mdapplyTo:(on-demand loading)collections/design-thinking.collection.ymlwith path and kind fieldscollections/hve-core-all.collection.ymlwith path and kind fieldsnpm run plugin:generaterun after updating collection manifests