Production Line: Digital Talent

Production Line: Digital Talent

Author: Pablo (Production Line Architect) Based on: Elena's Production Line Architecture Blueprint Version: 1.0 Date: 2026-03-18 Status: Active


1. Identity

Field Value
Line name digital-talent
Purpose Produce configured, tested digital talent for SMB clients
Product types Any Claude Code agent: EA, data governance, compliance, project management, DevOps, etc.
Target segment SMBs who need specialist capabilities but cannot justify a full-time hire

2. What This Line Produces

A standalone digital talent -- a Claude Code agent deployed to the client repository with:

Standard Deliverable Set (all products)

Artifact Description
CLAUDE.md Client-specific agent configuration: role definition, workspace rules, conventions, model selection
.claude/commands/*.md Domain-specific skill commands tailored to client methodology and outputs
.claude/commands/templates/ Output templates appropriate to the product domain
content-in/ Reference materials: methodology docs, domain knowledge, checklists
workflows/ Orchestration workflows (if the product uses orchestration)
Client documentation User guide, configuration guide, skill reference

Capabilities Vary by Product Type

The specific capabilities are defined in the work order, not in this line. Examples:

Product Type Example Capabilities
Enterprise Architecture Requirements capture, solution design, diagram generation, decision records, validation
Data Governance Data discovery, classification, lineage mapping, quality rules, governance reporting
Compliance Policy analysis, gap assessment, audit preparation, evidence collection
Project Management Planning, status tracking, risk assessment, stakeholder reporting

3. Pipeline

INTAKE -> REQUIREMENTS -> PATTERN SELECT -> BUILD -> QA GATE -> DEPLOY -> DELIVER -> BILLING -> FEEDBACK

Nine stages, eight blocking gates. See stages/ for details. Follows Elena's Production Line Architecture Blueprint.


4. Customization Dimensions

What varies per work order -- the dials Pablo turns when configuring a new digital talent instance.

Dimension What Varies Examples
Product type Domain and capability set EA agent, data governance agent, compliance agent
Domain skills The specific skills built into .claude/commands/ EA: orientation, solution, diagrams. Data: discovery, lineage, quality
Methodology Client's domain framework TOGAF, COBIT, ISO 27001, PMBOK, custom
Language Working language for all deliverables English, French Canadian, Spanish
Repository/tool integration Client's existing domain tool LeanIX, Ardoq, Collibra, Jira, none
Publication target Where outputs are published Confluence, SharePoint, Notion, markdown
Template library Domain-specific output templates Draw.io diagrams, schemas, report templates
Model selection Cost/quality preference Haiku for execution, Sonnet for analysis, Opus for orchestration
Quality thresholds Client-specific quality criteria Tool completeness scores, coverage metrics
Naming conventions Client artifact naming Deliverable codes, request numbering, decision format

5. Standard vs. Custom Components

Standard Components (reused across all products)

Component Description
Agent architecture CLAUDE.md structure, command layout, workspace conventions
Skill template Markdown skill template with standard sections (frontmatter, inputs, processing, outputs, quality checks)
Verification framework Structural checks, smoke tests, CLAUDE.md consistency
Documentation templates User guide, config guide, and skill reference card templates
Model selection guidance Cost-optimization matrix for model routing
Quality gate framework Gate criteria structure and scoring rubric

Custom Components (built per work order)

Component Description
Domain skills Skills specific to the product type, built from solution spec
Methodology references Client domain framework documentation loaded into content-in/
Tool integration Client tool meta-model, validation rules, API integration
Output templates Templates matching client visual and document standards
Publication pipeline Integration with client documentation platform
Orchestration Product-specific orchestrator skill (if the workflow requires one)
Naming conventions Client artifact codes, request numbering, file naming
Language configuration All prompts, templates, and outputs in client language

6. Capacity

Metric Estimate
New product type, first client 5-8 days
Same product type, new client 1-3 days (clone + customize)
QA cycle 1-2 days
Deployment 0.5 day

7. Work Orders

Each client engagement creates a work order in production-lines/orders/{client-slug}/. The work order contains all product-specific and client-specific configuration that this generic line needs to produce the talent.

See production-lines/orders/ for active and completed work orders.


9. Request Type Routing

Not all requests go through this production line. Four request types exist — the factory handles Types 1-3. Type 4 goes directly to the deployed talent.

Type Description Route Pipeline
Type 1 New talent, new client Full pipeline All 9 stages
Type 2 New talent, existing client Full pipeline, abbreviated intake All 9 stages — Stage 1 pulls from client registry instead of full discovery
Type 3 Enhancement to deployed talent Lightweight pipeline Requirements → Build → QA → Deploy (skip intake, pattern selection, billing, feedback)
Type 4 Work request for deployed talent Not this line Goes directly to the deployed talent in the client environment

How to Route

Is this about BUILDING or CHANGING a digital talent?
  YES → Is the client new?
    YES → Type 1 (full pipeline, full intake)
    NO  → Is this a NEW talent for the client?
      YES → Type 2 (full pipeline, abbreviated intake)
      NO  → Type 3 (enhancement — delta pipeline)
  NO → Type 4 (talent does the work — factory not involved)

Type 2: Existing Client Path

When the client already has a profile in production-lines/clients/{client-slug}/:

  • Skip discovery session (1.1) — client context is known
  • Skip organizational questions in intake (1.2) — pull from profile.md
  • Focus intake on the new product type and any changes since last engagement
  • Still requires full requirements, pattern selection, build, QA, deploy, deliver

Type 3: Enhancement Path

When the client requests changes to an already-deployed talent:

  • Start with a delta requirements capture — what's changing and why
  • Skip pattern selection (unless the enhancement introduces a new pattern)
  • Build only the changed components
  • QA covers regression (existing capabilities still work) + new capability validation
  • Deploy as an update to the existing talent repository

Type 4: Not Our Problem (In a Good Way)

Type 4 means the talent is working. The client is using the talent to do real work — requirements capture, analysis, design, etc. This is the success case. The factory built it, the talent does it.

Example: "Capture requirements for Azure Dataset" → the deployed EA talent runs /ea-exigences-intrant, not the factory.

Client Context Registry

Client profiles persist at production-lines/clients/{client-slug}/ to support Type 2 abbreviated intake and track deployments across engagements.

See TFD-0006 for the decision record.


8. Dependencies

Dependency Source Status
Pattern catalog Ada (Agentic Pattern Designer) Available
Production line blueprint Elena (Enterprise Architect) Available
QA framework Quinn (QA Engineer) Available
Deployment standards Diego (Deployment Specialist) Available
Client intake process Camille (Client Intake Manager) Available
Naming conventions Nora (Nomenclature Specialist) Available