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docs: rename approved content to AI reference library
Reframe the curated document corpus for broader stakeholder use and multi-platform LLM ingestion by flattening the structure, renaming recruiter-specific paths to stakeholder-focused naming, and removing leftover legacy directories. Made-with: Cursor
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.claude/plans/data-model-and-knowledge-base.md

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---
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## Workstream E — Approved Content Library (Lean, Immediate)
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## Workstream E — AI Reference Library (Lean, Immediate)
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The goal is immediate curation, not framework design. Keep this folder simple and flat so it stays maintainable for a one-person part-time workflow.
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The goal is immediate curation, not framework design. Keep this library simple and flat so it stays maintainable for a one-person part-time workflow while still supporting multiple stakeholders and LLM platforms.
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### Current directory structure
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```text
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data/generated/approved-content/
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data/generated/reference-library/
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├── README.md
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├── INDEX.md
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└── artifacts/
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├── resumes/
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├── case-studies/
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└── recruiter-qa/
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├── resumes/
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├── case-studies/
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└── stakeholder-qa/
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```
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### Operational rules
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- [ ] Keep only approved source artifacts you want to curate and ingest.
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- [ ] Keep filenames readable; avoid deep nested date folders.
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- [ ] Update `INDEX.md` whenever files are added/replaced.
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- [ ] Save recruiter clarifications as standalone markdown files in `artifacts/recruiter-qa/`.
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- [ ] Save stakeholder clarifications as standalone markdown files in `stakeholder-qa/`.
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- [ ] Ignore Windows `:Zone.Identifier` files.
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- [ ] Keep documents platform-agnostic for ingestion by Claude, Bedrock, and Gemini/Vertex.
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### Deferred by design
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## Seed Entry for Future Ingestion (Approved Recruiter Clarification)
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## Seed Entry for Future Ingestion (Approved Stakeholder Clarification)
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Source artifact:
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- `data/generated/approved-content/artifacts/recruiter-qa/faq-employment-timeline-ey-2026-03.md`
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- `data/generated/reference-library/stakeholder-qa/faq-employment-timeline-ey-2026-03.md`
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Recommended destination tables:
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data/generated/approved-content/INDEX.md

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data/generated/approved-content/README.md

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data/generated/approved-content/artifacts/README.md

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data/generated/approved-content/artifacts/recruiter-qa/README.md

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# AI Reference Library Index
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Last updated: 2026-03-09
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## Resumes
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- `resumes/Paul-Prae-Resume-20260305.md`
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- `resumes/Paul-Prae-Resume-20260305.docx`
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- `resumes/Paul-Prae-Resume-20260305.pdf`
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## Case Studies
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- `case-studies/BCG AI Factory Case Studies Paul Prae.docx`
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- `case-studies/McKinsey AI Solution Architect Case Studies Paul Prae.docx`
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- `case-studies/Paul-Prae-AI-Agent-Portfolio-Airtable.docx`
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## Stakeholder Q/A
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- `stakeholder-qa/faq-employment-timeline-ey-2026-03.md`
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## Notes
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- Ignore and do not commit `:Zone.Identifier` files copied from Windows.
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# AI Reference Library
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This is a curated, platform-agnostic document library for AI assistants and LLM workflows.
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Primary consumers include stakeholders across recruiting and delivery: recruiters, hiring managers, peers, colleagues, and startup collaborators.
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## Current structure
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```text
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data/generated/reference-library/
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├── README.md
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├── INDEX.md
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├── resumes/
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├── case-studies/
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└── stakeholder-qa/
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```
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## Operating rules
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- Keep this tree flat and easy to scan.
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- Store only approved, public-safe, stakeholder-safe documents.
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- Keep filenames human-readable and stable for retrieval.
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- Update `INDEX.md` every time files are added, removed, or replaced.
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- Ignore Windows `:Zone.Identifier` artifacts.
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## Naming guidance
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- Resumes: `Paul-Prae-Resume-YYYYMMDD.<ext>`
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- Stakeholder Q/A: `faq-<topic>-<yyyy-mm>.md`
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- Case studies: preserve descriptive source filenames
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## LLM/platform compatibility
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This library is designed to be ingestion-ready for:
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- Anthropic Claude
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- AWS Bedrock
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- Google Gemini / Vertex AI
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Each document should stand alone, include clear context, and avoid private data.

data/generated/approved-content/artifacts/case-studies/BCG AI Factory Case Studies Paul Prae.docx renamed to data/generated/reference-library/case-studies/BCG AI Factory Case Studies Paul Prae.docx

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data/generated/approved-content/artifacts/case-studies/McKinsey AI Solution Architect Case Studies Paul Prae.docx renamed to data/generated/reference-library/case-studies/McKinsey AI Solution Architect Case Studies Paul Prae.docx

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data/generated/approved-content/artifacts/case-studies/Paul-Prae-AI-Agent-Portfolio-Airtable.docx renamed to data/generated/reference-library/case-studies/Paul-Prae-AI-Agent-Portfolio-Airtable.docx

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