product-management-human-data-platform

Original：🇺🇸 English

Translated

Guides product management for human data platforms—annotation and labeling products, workforce workflows, task design, quality systems (gold sets, adjudication, inter-annotator agreement), customer ML-team project delivery, contributor experience, and privacy-safe handling of human-generated training data. Use when prioritizing roadmap for labeling/RLHF/eval data platforms, writing PRDs for annotation or QA features, defining success metrics for throughput and quality, scoping enterprise customer workflows, or balancing cost-quality-speed tradeoffs—not for hands-on model training (data-scientist), warehouse/analytics pipelines (data-warehouse-engineer), generic BRD workshops without product lens (business-analyst), AI solution architecture for copilots (applied-ai-architect-commercial-enterprise), or control implementation for audits (compliance-engineer). UX flows: product-designer. Eval harnesses: prompt-engineer-agent-prompts-evals. Pricing/packaging for platform: product-management-monetization.

2installs

Sourcedaemon-blockint-tech/agentic-enteprises-skill

Added on2026-05-20

NPX Install

npx skill4agent add daemon-blockint-tech/agentic-enteprises-skill product-management-human-data-platform

SKILL.md Content

View Translation Comparison →

Product Management — Human Data Platform

When to Use

Define vision, roadmap, and prioritization for labeling, RLHF, or human-eval products
Write PRDs for annotation UI, project setup, QA, workforce, or export/API features
Design annotation tasks (taxonomy, instructions, rubrics, edge cases)
Specify quality programs: gold tasks, consensus, adjudication, rejection reasons
Scope customer workflows (ML teams): projects, batches, SLAs, delivery formats
Improve contributor/annotator productivity, fairness, and trust/safety product surfaces
Set metrics: throughput, quality, cost per label, time-to-delivery, contributor retention
Partner on privacy and ethics requirements for human-submitted data (PII, consent, locale)

When NOT to Use

Facilitate generic process maps and BRDs without product ownership →
```
business-analyst
```
Wireframes and visual design only →
```
product-designer
```

RAG/copilot enterprise architecture →

applied-ai-architect-commercial-enterprise

Build eval harnesses and judges in code →
```
prompt-engineer-agent-prompts-evals
```
SOC/ISO evidence automation →
```
compliance-engineer
```
Data warehouse modeling →
```
data-warehouse-engineer
```
Cross-team delivery RAID without product discovery →
```
technical-program-manager
```

Related skills

Need	Skill
BRD/user story format	`business-analyst`
Annotator and customer UX	`product-designer`
How labels feed model programs	`applied-ai-architect-commercial-enterprise`
Golden sets and regression evals	`prompt-engineer-agent-prompts-evals`
Privacy controls and audit evidence	`compliance-engineer`
Taxonomy/ontology for labels	`ontology-engineer`
Analytics for product teams	`analytics-data-engineering-manager-product`

Core Workflows

1. Vision, roadmap, and prioritization

Outcomes, segments, themes, RICE/ICE.

See
references/roadmap_prioritization.md
.

2. Annotation task and taxonomy design

Instructions, rubrics, schema, edge cases.

See
references/annotation_task_design.md
.

3. Quality systems

Gold sets, IAA, adjudication, rejection taxonomy.

See
references/quality_systems.md
.

4. Customer (ML team) delivery

Projects, pipelines, exports, SLAs.

See
references/customer_ml_workflows.md
.

5. Contributor and workforce product

Task UX, payments, trust, locale.

See
references/contributor_workforce_product.md
.

6. Privacy, ethics, and policy

PII, consent, retention, labor.

See
references/privacy_ethics_policy.md
.

Output standards

PRDs state persona, problem, success metrics, non-goals, and launch tier
Task specs include worked examples (gold, borderline, reject)
Quality bar defined as measurable thresholds, not "high quality"
Every feature maps to cost, quality, or speed lever
Escalate legal/labor questions; do not ship policy in product copy alone

When to load references

Roadmap →
```
references/roadmap_prioritization.md
```
Tasks →
```
references/annotation_task_design.md
```
Quality →
```
references/quality_systems.md
```
Customers →
```
references/customer_ml_workflows.md
```

Contributors →

references/contributor_workforce_product.md

Privacy →
```
references/privacy_ethics_policy.md
```