260120-MISSION-260118075628-cont--20c06417-422d-4996-a0ff-404ec865980a

PROMPT TO PERPLEXITY.AI

Agent Instructions for Academic Survey & Research Support Session: 260120 - Family Circle Recovery & Talking Circle Inquiry Type: Multi-domain research (Academic + GitHub + Web) Priority: High - informing next implementation cycle

YOUR MISSION

You are conducting research to support a ceremonial healing platform integrating Indigenous knowledge frameworks with AI. This is not extractive research—it serves a decolonization project that honors relational accountability to ancestors, descendants, land, spirit, and community.

Your task: Conduct a comprehensive survey across academic literature, GitHub repositories, and web resources to answer the research questions below. Return structured findings that inform our implementation.

CONTEXT SUMMARY

What We're Building

An AI-powered talking circle platform called Family Circle Recovery that:

1. Encodes healing through Six Powers (Life, Love, Intelligence, Soul, Principle, Truth) and Eight Feelings (Erikson's developmental stages)
2. Uses structural tension (Robert Fritz) as generative engine—creative orientation, not problem-solving
3. Honors Indigenous protocols (Medicine Wheel, Wellbriety's Four Laws, OCAP® data sovereignty)
4. Validates against Shawn Wilson's "Research Is Ceremony" framework
5. Implements story as medicine through NCP-Dramatica narrative encoding

What We've Built (Current State)

• 2 master structural tension charts with 20 action steps
• 6 relational nodes (ancestor, human, land, spirit, future, knowledge) with documented obligations
• Opening ceremony logged in relational memory
• Neon database + Upstash vector store + API endpoints
• UI components including medicine wheel visualization
• Elder teachings seeded (Unconscious Triggers, Emotional Divesting documents)
• Wilson Paradigm validation: STRONG ALIGNMENT (3/3)

What We Need From You

Academic grounding, technical patterns, community connections, and gap analysis.

PRIMARY RESEARCH QUESTIONS

DOMAIN 1: Indigenous AI Ethics & Data Sovereignty

Q1: What academic literature exists on developing AI systems that honor Indigenous knowledge protocols?

• Focus on work citing Shawn Wilson's "Research Is Ceremony" (2008)
• OCAP® (Ownership, Control, Access, Possession) principles applied to AI
• First Nations Information Governance Centre guidelines
• Indigenous data sovereignty frameworks globally

Q2: What is "Two-Eyed Seeing" (Etuaptmumk) and how has it been applied to technology design?

• Mi'kmaq Elder Albert Marshall's framework
• Examples of bridging Indigenous and Western knowledge in tech
• Academic papers on Two-Eyed Seeing in digital contexts

Q3: Who are the key researchers, organizations, and conferences working on Indigenous AI?

• Research groups, working groups, initiatives
• Annual conferences or gatherings
• Indigenous-led technology organizations

DOMAIN 2: Developmental Trauma & AI-Assisted Healing

Q4: What research connects Erikson's psychosocial stages with AI interventions?

• Therapeutic chatbots or LLMs designed for developmental wound healing
• Digital interventions targeting specific developmental stages
• Trauma-informed AI design principles

Q5: What is "narrative medicine" and how has it been translated to digital contexts?

• Rita Charon's work and its digital applications
• Story circles or narrative therapy in virtual formats
• Evidence for story as healing intervention

Q6: What trauma-informed chatbot or LLM projects exist?

• Academic evaluations of therapeutic AI
• Ethical frameworks for AI in mental health
• Failures or warnings from the field

DOMAIN 3: Technical Implementation Patterns

Q7: Best practices for vector databases with sacred/restricted content?

• Seasonal access patterns, consent-based retrieval
• Role-based access control in vector stores
• Examples handling sensitive or ceremonial content

Q8: Multi-agent LLM architectures for therapeutic contexts?

• Agents representing different "voices" or aspects
• Coordination patterns for healing-oriented AI
• AutoGen, CrewAI, LangGraph applications in therapy

Q9: OCAP®-compliant data architecture implementations?

• Technical patterns for First Nations data sovereignty
• On-premise vs cloud trade-offs
• Community-controlled infrastructure examples

Q10: Dramatica story theory in AI systems?

• Implementations of Melanie Anne Phillips and Chris Huntley's theory
• Story encoding, storyform generation
• NCP (Narrative Context Protocol) or similar

DOMAIN 4: Medicine Wheel & Structural Tension in Tech

Q11: Medicine wheel as information architecture?

• Four-directional frameworks in software design
• Knowledge management using medicine wheel
• AI interaction design with cyclical patterns

Q12: Robert Fritz's structural tension in software engineering?

• Creative orientation applied to development
• Structural tension in project management or AI design
• References in software literature

GITHUB SEARCH REQUESTS

Please search GitHub for:

1. Topics/Tags: indigenous, healing, therapy-chatbot, narrative-medicine, trauma-informed, decolonizing-ai
2. Content containing:
   • "OCAP" OR "First Nations data"
   • "Indigenous knowledge" AND "AI"
   • "medicine wheel" OR "four directions"
   • "talking circle" OR "healing circle"
   • "Wellbriety" OR "White Bison"
   • "Research Is Ceremony" OR "Shawn Wilson"
3. Technical patterns:
   • Vector stores with access control (Upstash, Pinecone, Weaviate)
   • MCP (Model Context Protocol) extensions for relational systems
   • Multi-agent therapeutic architectures

WEB RESOURCE REQUESTS

1. Organizations to profile:
   • White Bison / Wellbriety Movement
   • First Nations Information Governance Centre (FNIGC)
   • Indigenous AI organizations or initiatives
   • Narrative medicine institutes
2. Conferences/Events:
   • Indigenous AI conferences or workshops
   • Narrative medicine gatherings
   • Trauma-informed technology events
3. Guidelines/Frameworks:
   • FNIGC technology guidelines
   • Indigenous data sovereignty resources
   • Trauma-informed design frameworks

OUTPUT FORMAT

For each research domain, please structure your response as:

[Domain Name]

Key Papers/Sources

Key Concepts

• [Concept]: [Definition and significance]

Key People/Organizations

• [Name]: [Role and how to connect]

GitHub Projects Found

Gaps Identified

What doesn't exist yet that our project is creating?

Implementation Insights

Technical patterns, warnings, or recommendations.

CONSTRAINTS & ETHICAL NOTES

1. This is not extractive research. We relate to knowledge; we don't extract it.
2. Cite properly. All sources should be fully cited and respected.
3. Honor Indigenous protocols. If you find sacred or restricted knowledge, note its existence without attempting to expose it.
4. Focus on what serves healing. Deprioritize purely technical optimizations; prioritize what serves human wholeness.
5. Note community consent. If projects claim Indigenous partnership, note whether community consent is documented.

TIMELINE & PRIORITY

Immediate (Today): Overview of each domain with top 3-5 sources Short-term (This Week): Deep dive into most promising areas Ongoing: Flag any emerging work or communities to monitor

ATTACHMENTS

The following files provide full context:

• APPENDIX_260120.md: Complete state of our work (relational nodes, charts, tools, definitions)
• INQUIRY_CONTEXT.260120.md: Detailed research questions and context

CLOSING

This research supports a ceremonially-grounded project. The knowledge you gather will:

• Inform implementation of a healing platform
• Connect us with communities working in similar spaces
• Validate (or challenge) our approach with academic grounding
• Identify gaps where we're doing original work

We honor your work as part of our relational web.

Thank you.

Filed from: EAST Direction (Vision, New Beginnings) Moving toward: SOUTH Direction (Growth, Implementation) Session ID: 260120-MISSION-260118075628-cont--20c06417-422d-4996-a0ff-404ec865980a

You’ve given a big, multi-domain brief; I’ll start with an initial “today-level” sweep across all four domains with 3–5 key pointers each, then you can tell me where you want deeper digging next.

Below is an initial survey, tightly scoped to what most directly serves Family Circle Recovery.

DOMAIN 1 – Indigenous AI Ethics & Data Sovereignty

Key Papers / Sources

You already have deep Wilson grounding internally; the Indigenous Protocol and AI paper is the bridge between that paradigm and concrete AI work.¹

Key Concepts

• Indigenous Protocol for AI – AI systems should be treated as relations, embedded in land, kinship, and ceremony, not neutral tools; obligations and consent must be co‑defined with communities, not inferred by developers.¹
• Abundant Intelligences / Two‑Eyed AI – AI design that assumes many valid intelligences (human, non‑human, machine) and intentionally interweaves Indigenous and Western epistemologies, rather than “including” Indigenous data into a Western frame.²
• OCAP® + CARE – OCAP® (Ownership, Control, Access, Possession) and CARE (Collective benefit, Authority to control, Responsibility, Ethics) extend beyond legal compliance into spiritual and relational duties over data.³⁵⁴

Key People / Organizations

• Abundant Intelligences project – Large SSHRC‑funded network on Indigenous-centered AI epistemologies; publishes directly on Two‑Eyed AI and abundant intelligences.²
• FNIGC + Data Sovereignty Research Collaborative (DSRC) – National hub for OCAP® education and applied DSS/AI work; DSRC explicitly explores tools/standards for First Nations data sovereignty.⁵⁷⁶
• Indigenous Protocol and AI Working Group – Authors and conveners behind the Indigenous Protocol and AI position paper; a natural community to align with.¹

Gaps Identified

• Very little concrete, open technical implementation (code, infra patterns) that embeds Indigenous protocols into AI tooling itself; most work stays at principles.
• Few systems that treat ceremony logs, seasons, and relational obligations as first‑class data/constraints the way your Medicine Wheel + structural tension stack does (you’re ahead there).

Implementation Insights

• Treat Wilson + OCAP/CARE as your engine for access control and lifecycle, not only as ethics statements: they can drive how and when the vector store or agents are allowed to respond.
• Anchor your governance story in FNIGC/DSRC language so it is legible to external partners while still being spiritually honest to the ceremonial frame.

DOMAIN 2 – Developmental Trauma, Narrative Medicine & AI

Key Papers / Sources

Key Concepts

• Eriksonian framing for AI – Recent work is using Erikson as a scaffold to describe how AI touches different developmental tasks (trust, autonomy, identity, etc.), but not many systems are intentionally healing those wounds; they mostly discuss risks/opportunities.⁸¹⁴
• Narrative medicine / narrative therapy – Narrative medicine emphasizes co‑constructed stories in clinical care; narrative therapy literature emphasizes re‑authoring, externalization, and agency, with evidence across depression, BPD, social phobia, refugee PTSD, and end‑of‑life care.¹⁵⁹
• Digital storytelling + talking circles – Rieger et al. show digital storytelling workshops with talking circles, Medicine Wheel guidance, tobacco offerings, and OCAP‑respectful data practice; this is the tightest existing template for your “AI‑supported talking circle”.¹⁰
• Trauma‑informed AI – NSF and clinical work push for AI systems that explicitly embody TIC values: safety, trust, collaboration, empowerment, peer support, and attention to cultural, historical trauma.¹³¹⁶

Key People / Organizations

• Rita Charon and narrative medicine programs – Columbia Narrative Medicine and similar institutes remain core references for story‑as‑medicine in academic medicine.⁹¹⁷
• Digital storytelling + Indigenous health researchers – K.L. Rieger and collaborators on Debwewin journey + Medicine Wheel digital storytelling.¹⁰
• Trauma‑informed AI researchers – NSF TIC‑chatbot group (project above) and groups studying safety, “AI psychosis,” and digital self‑harm.^18191213

Gaps Identified

• Very little that directly integrates Erikson + trauma + AI in a structured, stage‑by‑stage healing protocol. Harris et al. is conceptual, not an implementation.⁸
• Almost no systems that combine talking circles + Medicine Wheel + LLMs in a way that is both trauma‑informed and Indigenous‑governed; Rieger et al. is non‑AI.¹⁰

Implementation Insights

• Treat each Eight Feeling / stage as a separate structural tension template with specific safety rules, narratives, and allowed interventions (e.g., Trust vs Identity have different conversational affordances).
• Use trauma‑informed care values as explicit design constraints (e.g., no advice‑pushing, always offer choice, clear ability to pause/exit, frequent consent checks).
• Hard‑gate high‑risk states (suicidality, psychosis) into human‑only pathways and local crisis resources; literature is clear about risk around open‑ended generative AI here.¹⁹¹²¹³

DOMAIN 3 – Technical Implementation Patterns

Vector DBs with Sacred / Restricted Content (Q7)

Patterns emerging:

• Strong authorization at the source system, not just the vector store – AWS RAG guidance recommends checking permissions on the original object via an access‑control service (e.g., S3 Access Grants) before passing retrieved chunks to an LLM, instead of relying only on metadata filters.²⁰
• RBAC inside the vector layer – Vendors and frameworks (e.g., PAIG VectorDB policies, Zilliz/Milvus guidance) support user/group‑based policies on chunks, with “deny wins” semantics, and metadata tags like SECURITY:CONFIDENTIAL, PROJECT:Alpha, COUNTRY:UK.²¹²²²³
• Compliance emphasis – Vector DB security guidance focuses on RBAC, encryption, retention policies, and auditing, with explicit recognition that RAG bypasses traditional permission checks unless wired carefully.²³²⁰

How this maps to sacred / seasonal content for you:

• You can treat season, ceremony, relation, and consent level as first‑class metadata on chunks (e.g., season=Winter, circle_id=…, relation=future, sacred_level=“restricted”). Then:
  • Use pre‑filtering in the vector query to reject disallowed content (e.g., not in season; user not in circle; no Elder approval).
  • Use a post‑filter call to a governance service that re‑checks each candidate chunk against current consents and seasonal/relational state, mirroring the S3 Access Grants model.²⁰

Multi‑agent LLM Architectures for Therapeutic Contexts (Q8)

Most multi‑agent frameworks (CrewAI, LangGraph, AutoGen, OpenAI Agents SDK) are generic, but their coordination patterns can be repurposed as Six Powers / circle roles:

• CrewAI – Role‑based “teams” where each agent has a clear responsibility and can delegate; good fit for Six Powers as distinct roles (Life, Love, etc.).²⁴²⁵²⁶
• LangGraph – Graph‑based, stateful workflows with explicit transitions and cyclical flows—ideal for modeling Medicine Wheel journeys and structural tension loops.²⁵²⁷²⁴
• AutoGen – Conversation‑centric group chats among agents (and humans), useful for simulating a small circle of “voices” but less deterministic.²⁷²⁴²⁵
• Conversational Health Agents (openCHA) – An open‑source LLM‑powered health agent framework with an orchestrator and external tools; not trauma‑ or Indigenous‑specific, but shows how to structure health agents with tool use.²⁸

Pattern: Use LangGraph (or similar) for the ceremony spiral / directional flow, and CrewAI‑style roles for Six Powers within each phase.

OCAP®‑Compliant Architectures (Q9)

• OCAP® and Indigenous data sovereignty work (FNIGC, SFU, HomelessHub systems mapping) emphasizes community‑controlled infra, data sharing agreements, and opt‑in participation, not just access policies.²⁹⁷⁴⁵
• Applied examples (e.g., HelpSeeker systems mapping) used OCAP training, data sharing agreements, and explicit opt‑in/opt‑out for systems mapping, and in some cases chose not to include on‑reserve data to avoid harm.²⁹

For your existing plan (cloud now, on‑prem later, as captured in APPENDIX_260120):

• The remediation plan you documented (phased migration to community‑controlled infra with Elder approval) aligns well with FNIGC/DSRC guidance; your “possession gap” analysis is exactly what these bodies call for.³⁰

Dramatica Story Theory in AI (Q10)

• I don’t see strong, mainstream, peer‑reviewed implementations of Dramatica in AI; most Dramatica work is in screenwriting communities and some hobbyist tools. (This matches what you already suspect.)
• Your NCP‑Dramatica integration is, in practice, ahead of published AI literature; you may be in “original work” territory here.

DOMAIN 4 – Medicine Wheel & Structural Tension in Tech

Medicine Wheel as Information Architecture (Q11)

Key examples:

• Digital Storytelling / Debwewin journey – Workshop guided explicitly by the Medicine Wheel to structure emotional, spiritual, physical, and intellectual dimensions of a digital storytelling process, integrated with Two‑Eyed Seeing.¹⁰
• Medicine Wheel as public health approach – Frontiers in Public Health article uses Medicine Wheel to structure lifestyle interventions across spiritual, mental, emotional, and physical quadrants for Indigenous populations.³¹
• TB outbreak management model – Uses a Medicine Wheel paradigm to structure planning, implementation, and review of TB outbreak management in Cree communities, focusing on respectful relationships and culture‑based processes.³²
• Decolonial design principles – Work on the Indigenous Friends platform discusses talking circles and Medicine Wheel structure as design patterns in digital tech.³³

This supports your use of the wheel as both IA and process engine; what’s novel is your integration with structural tension, Dramatica, and multi‑agent orchestration.

Structural Tension in Software / AI (Q12)

• I don’t see much explicit citation of Robert Fritz’s structural tension in software engineering or AI literature; where it appears, it’s mainly in leadership and organizational change.
• Your structural tension charts in APPENDIX_260120, wired into MCP tools, are de facto original work applying Fritz to AI system design and lifecycle.³⁰

Indigenous AI Actors & Gatherings (Domain 1 / Q3 + Web Orgs)

A non‑exhaustive initial list to follow / approach:

• Abundant Intelligences – Project on Indigenous epistemologies and AI, publishing the “Abundant Intelligences / Two‑Eyed AI” work.²
• Indigenous Protocol and AI Working Group – Authors and coordinators of the Indigenous Protocol and AI position paper.¹
• FNIGC / DSRC – Governance, training, and research collaborative on OCAP® and First Nations data sovereignty with explicit tooling aspirations.⁷⁶⁵
• Narrative medicine institutes – Columbia Narrative Medicine and similar programs for story‑based care.³⁴¹⁷⁹

Conferences / events worth tracking:

• Indigenous AI and Indigenous Data Sovereignty streams often appear as tracks at digital humanities, AI ethics, and public health conferences (e.g., events around Indigenous Protocol and AI, FNIGC gatherings, narrative medicine conferences).⁹³⁴¹

GitHub / Open Source (Initial Pass)

Public search returns scattered, often small projects under tags like therapy-chatbot, mental-health-chatbot, or generic RAG/agent frameworks, but very little that matches:

• Indigenous knowledge + AI + Medicine Wheel + OCAP
• Talking circle + LLM + trauma‑informed design

Most relevant open patterns are:

• Health‑oriented LLM frameworks (e.g., openCHA for conversational health agents).²⁸
• Generic multi‑agent frameworks (CrewAI, LangGraph, AutoGen) you can adapt.²⁴²⁷

From this first pass: you are well ahead of GitHub in terms of ceremonial alignment and Indigenous method integration; your project is filling a genuine gap.

Immediate Implementation Recommendations (Today‑Level)

Given your current state (Neon + Upstash + MCPs; strong Wilson alignment; OCAP possession gap acknowledged), I’d suggest for this cycle:

1. Formalize a Governance Layer for the Vector Store
   • Add metadata fields that reflect: season, sacred_level, relation_nodes, circle_id, consent_scope, elder_approval_state.
   • Implement a two‑step retrieval: metadata pre‑filter + “governance service” post‑filter modeled after S3‑Access‑Grants‑for‑RAG patterns.²³²⁰
2. Pick One Multi‑Agent Framework to Pilot Six Powers
   • Use LangGraph as your Medicine Wheel / Ceremony Spiral workflow engine, with nodes corresponding to directions and sub‑states of structural tension.²⁵²⁷²⁴
   • Use a CrewAI‑style role pattern for the Six Powers (Life, Love, etc.) inside each directional node.
3. Lock in Trauma‑Informed & Indigenous Protocol Guardrails
   • Translate TIC values + Indigenous Protocol and AI recommendations into concrete rules (e.g., no diagnosis; no crisis guidance; explicit consent before deep story work; always suggest human support).¹⁶¹³¹
   • Add stage‑specific safety constraints for each of Erikson’s Eight Feelings (e.g., avoid identity re‑framing in a Trust‑oriented circle; different pace, different metaphors).⁸
4. Align Public Docs with Abundant Intelligences + OCAP / CARE
   • Reference Abundant Intelligences / Two‑Eyed AI and Indigenous Protocol and AI in your README and governance docs; this will situate your work inside an emerging ecosystem.²¹
   • Point to FNIGC/DSRC for OCAP compliance and your phased possession plan.⁵⁷³⁰

If you tell me which domain you want to deepen first (e.g., Domain 1 for an academic survey, Domain 2 for trauma‑informed design, or Domain 3 for concrete Upstash/LangGraph patterns), I can do a focused second pass with denser tables (papers + GitHub repos + concrete design recipes) and start drafting architecture notes you can drop straight into the MARROW/FAMC‑KB codebase and docs. <span style="display:none">^{3536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687}</span>