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AI Deep-Research Control Map

Purpose

This page is the bounded atlas bridge for Ledger's AI deep-research control cluster.

Use it to answer one narrow question:

  • when the repo is using ChatGPT or another external AI research source, which curated Ledger research note should you read next?

This page is:

  • research navigation
  • not canon
  • not runtime governance truth
  • not a raw intake viewer

Truth Boundary

Keep these surfaces distinct:

  • research/intake/ai-planning/ holds retained planning-only AI output
  • research/intake/ai-synthesis/ holds bounded AI synthesis output that is not actual Deep Research
  • research/intake/ai-deep-research/ holds actual launched research-mode output
  • research/intake/external-ai/ remains a legacy compatibility surface for older external-AI control-package material
  • research/strategy/ holds the curated Smart Ledger control notes for this cluster
  • this MkDocs page is only an orientation layer over those stronger repo-backed notes

Working rule:

  • use this page to find the right curated note quickly
  • do not treat this page as the primary maintained explanation
  • do not treat atlas visibility as approval, promotion, or implementation authorization

Raw intake is not published here by default.

Cluster Shape

flowchart TD
    A["AI deep-research control cluster"] --> B["Control package"]
    A --> C["Intake and provenance"]
    A --> D["Curation and maturity"]
    A --> E["Placement and family"]
    A --> F["MkDocs projection"]
    A --> G["Validation and stewardship"]

    B --> B1["Integrated operating rule"]
    C --> C1["Raw intake boundary"]
    D --> D1["Research maturity states"]
    E --> E1["Destination-family routing"]
    F --> F1["Atlas visibility boundary"]
    G --> G1["Low-noise control and ownership"]

Curated Control Notes

Curated note What it answers Truth level
LEDGER_AI_DEEP_RESEARCH_CONTROL_PACKAGE.md integrated Smart Ledger control package and phased implementation order research
LEDGER_EXTERNAL_AI_DEEP_RESEARCH_INTAKE_AND_PROVENANCE_MODEL.md how raw external AI research enters Ledger and what provenance it must preserve research
LEDGER_AI_DEEP_RESEARCH_CURATION_AND_MATURITY_MODEL.md how raw intake becomes Ledger-authored research and what maturity states mean research
LEDGER_AI_DEEP_RESEARCH_PLACEMENT_AND_FAMILY_MODEL.md where curated AI-assisted research belongs and how destination-family routing works research
LEDGER_AI_DEEP_RESEARCH_MKDOCS_PROJECTION_MODEL.md what site-docs/ may project and what must stay out of the atlas research
LEDGER_AI_DEEP_RESEARCH_VALIDATION_AND_STEWARDSHIP_MODEL.md which stewardship layers and validation boundaries keep the model safe research

Reading Paths

If you need the whole control model

  1. Start with LEDGER_AI_DEEP_RESEARCH_CONTROL_PACKAGE.md.
  2. Drop into the supporting notes only when one control boundary needs more precision.

If you need to handle a new external AI report

  1. Read LEDGER_EXTERNAL_AI_DEEP_RESEARCH_INTAKE_AND_PROVENANCE_MODEL.md.
  2. Then read LEDGER_AI_DEEP_RESEARCH_CURATION_AND_MATURITY_MODEL.md.
  3. Use the v1 intake-family READMEs when deciding whether the returned artifact belongs under planning, synthesis, or actual Deep Research intake.
  4. Use research/intake/external-ai/HANDOFF_TO_CURATED_RESEARCH.md only when normalizing legacy external-AI material.

If you need placement or atlas decisions

  1. Read LEDGER_AI_DEEP_RESEARCH_PLACEMENT_AND_FAMILY_MODEL.md.
  2. Then read LEDGER_AI_DEEP_RESEARCH_MKDOCS_PROJECTION_MODEL.md.
  3. Return to Research Indexes when you need a broader research entrypoint again.

Working Conclusion

Use this bridge page to find the right curated Smart Ledger note for AI deep-research handling.

If precision matters, leave the atlas immediately and read the linked repo-backed research note.