tractatus/docs/outreach/HUGGINGFACE-PRESENCE-PLAN.md
TheFlow 51a9f3ca7f docs: comprehensive social media and HF Space maintenance guide
Created detailed documentation for future Claude Code instances to maintain:
- Reddit presence (u/tractatus-framework, r/AI_Agents engagement)
- Facebook presence (Agentic Governance NZ page)
- Hugging Face Space (audit-log-viewer deployment)
- Deep Interlock coordination tracking implementation

New files:
- docs/outreach/SOCIAL-MEDIA-AND-HF-MAINTENANCE.md (full guide)
- docs/outreach/QUICK-REFERENCE-SOCIAL-MEDIA.md (quick commands)
- docs/outreach/HUGGINGFACE-PRESENCE-PLAN.md (initial setup plan)
- scripts/export-hf-audit-data.js (HF data export script)
- public/images/tractatus-reddit-avatar*.png (Reddit branding)

Key features documented:
- Weekly HF Space update procedure
- Daily Reddit engagement strategy
- Coordination tracking troubleshooting
- Performance metrics and goals
- Complete troubleshooting guide

All procedures include copy-paste commands for easy maintenance.

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-01 08:09:01 +13:00

387 lines
11 KiB
Markdown

# Hugging Face Presence Plan - Tractatus Framework
**Date**: 2025-10-31
**Purpose**: Establish Tractatus presence on Hugging Face to reach AI/ML research community
**Status**: Planning Phase
---
## Why Hugging Face?
**Strategic Fit:**
- Focus on AI ethics and governance aligns with Tractatus mission
- Research-oriented community (our target audience)
- Open-source first culture
- Models come with documentation about limitations/biases (governance mindset)
- Platform for ML practitioners, not just consumers
**Unique Opportunity:**
- Very few governance frameworks have Hugging Face presence
- Most content is models/datasets - governance tooling is underrepresented
- Community values transparency and ethical AI
- Tractatus can fill governance gap in HF ecosystem
---
## Phase 1: Account Setup (Week 1)
### 1.1 Create Personal Account
- [ ] Sign up at https://huggingface.co/join
- [ ] Verify email
- [ ] Complete profile:
- Name: [Your name or "Tractatus Team"]
- Bio: "AI governance researcher. Building architectural constraints for human agency."
- Location: Aotearoa New Zealand
- Website: https://agenticgovernance.digital
### 1.2 Create Organization
- [ ] Go to https://huggingface.co/organizations/new
- [ ] Organization name options:
- **Option A**: `tractatus-framework` (descriptive)
- **Option B**: `agentic-governance` (brand alignment)
- **Option C**: `tractatus` (simple, if available)
- [ ] Organization display name: "Tractatus AI Safety Framework"
- [ ] Organization description:
```
Architectural constraints for human agency in AI systems.
Open-source governance framework operating in production.
Developed in Aotearoa NZ.
```
- [ ] Set organization email domain (agenticgovernance.digital)
- [ ] Add avatar (use tractatus-reddit-avatar-hd.png)
---
## Phase 2: Documentation & Repository (Week 1-2)
### 2.1 Organization README
Create: `README.md` for organization landing page
**Content Structure:**
```markdown
# Tractatus AI Safety Framework
Architectural constraints for human agency in AI agent deployments.
## What is Tractatus?
Production-tested governance framework enforcing constraints through
structure, not training. Five architectural principles from Christopher
Alexander's pattern languages applied to AI safety.
## Why Architectural Governance?
Behavioral training can be manipulated through prompting. We're testing
structural enforcement: PreToolUse hooks that intercept actions before
execution, services that coordinate through mutual validation, gradient
responses to risk levels.
## Resources
- **Website**: https://agenticgovernance.digital
- **Documentation**: https://agenticgovernance.digital/docs.html
- **Architecture**: https://agenticgovernance.digital/architecture.html
- **GitHub**: [link]
- **License**: Apache 2.0
## Demos
- [Framework Audit Viewer](#) - Interactive audit log explorer
- [Governance Metrics Dashboard](#) - Real-time framework statistics
- [Boundary Decision Explorer](#) - See how services coordinate
## Datasets
- [Audit Decision Corpus](#) - 3500+ anonymized governance decisions
- [Framework Evolution Log](#) - How principles emerged from failures
```
### 2.2 Link GitHub Repository
- [ ] Add GitHub repo to organization (if repo is public)
- [ ] Or create "mirror" documentation repo on HF
- [ ] Sync README between GitHub and HF
---
## Phase 3: Spaces - Interactive Demos (Week 2-3)
### 3.1 Space 1: Audit Log Viewer (Priority 1)
**Purpose**: Show framework in action through real audit decisions
**Tech Stack**: Gradio (Python, easy to deploy)
**Features:**
- Search audit logs by service, date, decision type
- Filter by pressure level (NORMAL/ELEVATED/HIGH/CRITICAL)
- Show service coordination for multi-service decisions
- Visualize decision patterns over time
**Data**: Anonymized subset of audit logs (remove file paths, specific code)
**Value**: Makes "3500+ audit decisions" tangible and explorable
---
### 3.2 Space 2: Governance Metrics Dashboard (Priority 2)
**Purpose**: Real-time framework statistics visualization
**Tech Stack**: Streamlit or Gradio
**Features:**
- Context pressure distribution over time
- Service activation patterns
- Boundary enforcement statistics
- Framework version evolution timeline
- "27027 incident" case study deep-dive
**Data**: Aggregated metrics from production use
**Value**: Shows operational reality, not theoretical concepts
---
### 3.3 Space 3: Boundary Decision Simulator (Priority 3)
**Purpose**: Interactive demonstration of how services coordinate
**Tech Stack**: Gradio with flow diagram visualization
**Features:**
- Input: Simulated AI action (e.g., "Edit values.html")
- Output: Step-by-step service coordination
- Visual flow: BoundaryEnforcer → CrossReference → ContextPressure → Decision
- Show how different pressure levels change outcomes
**Value**: Educational - helps people understand Deep Interlock principle
---
## Phase 4: Datasets (Week 3-4)
### 4.1 Audit Decision Corpus
**Dataset**: Anonymized audit logs from production use
**Format**: JSON Lines (.jsonl)
**Content:**
```json
{
"timestamp": "2025-10-31T10:00:00Z",
"service": "BoundaryEnforcer",
"decision": "ask",
"boundary": "12.2 Innovation",
"context_pressure": "NORMAL",
"coordination": ["CrossReferenceValidator", "ContextPressureMonitor"],
"outcome": "human_approval_required"
}
```
**Size**: 3500+ decisions (current corpus)
**Purpose**:
- Research dataset for governance pattern analysis
- Training data for governance service development
- Evidence of production deployment
**License**: CC BY-SA 4.0 (attribution + share-alike)
---
### 4.2 Framework Evolution Log
**Dataset**: How architectural principles emerged from failures
**Format**: Markdown + structured timeline
**Content**:
- Incident reports (e.g., 27027 incident)
- Service additions and rationale
- Framework version changes
- Living Process principle in action
**Purpose**: Show evidence-based evolution (inst_093)
---
## Phase 5: Model Cards / Documentation (Week 4)
### 5.1 Framework "Model Card"
Even though Tractatus isn't a model, HF supports documentation pages
**Create**: `model-card.md` explaining:
- What problem it solves
- How it works architecturally
- Limitations and known issues
- Intended use cases
- Evaluation metrics (audit log analysis)
- Ethical considerations (human agency preservation)
### 5.2 Blog Posts
Hugging Face allows blog posts for organizations
**Topics:**
- "Architectural Constraints vs Behavioral Training for AI Governance"
- "The 27027 Incident: How Production Failures Drive Framework Evolution"
- "Five Architectural Principles from Christopher Alexander Applied to AI Safety"
- "3500 Governance Decisions: What We Learned"
**Frequency**: 1 per month
---
## Phase 6: Community Engagement (Ongoing)
### 6.1 Participate in HF Discussions
- Comment on AI ethics/governance discussions
- Share audit log insights
- Respond to questions about governance approaches
### 6.2 Collaborate with Other Projects
- Projects working on AI safety
- Governance framework developers
- Ethical AI initiatives
- Open-source AI tooling
### 6.3 Update Datasets Quarterly
- Add new audit decisions
- Document framework evolution
- Show Living Process in action
---
## Technical Requirements
### Development Environment
- Python 3.9+ (for Gradio/Streamlit Spaces)
- Gradio or Streamlit library
- MongoDB access (to export audit logs)
- Data anonymization scripts
### Data Preparation
1. **Audit Log Anonymization**
- Remove file paths
- Remove specific code snippets
- Keep: service names, decisions, timestamps, coordination patterns
- Script: `scripts/export-anonymized-audits.js`
2. **Metrics Aggregation**
- Context pressure distribution
- Service activation counts
- Boundary enforcement statistics
- Script: `scripts/export-metrics.js`
### Space Deployment
- Create requirements.txt for Python dependencies
- Write app.py for Gradio/Streamlit interface
- Test locally before deploying
- Deploy to HF Spaces via git push
---
## Success Metrics
### Phase 1 (Setup) - Week 1
- [ ] Organization created
- [ ] Profile complete with branding
- [ ] README published
### Phase 2 (Content) - Week 2
- [ ] At least 1 Space deployed (Audit Log Viewer)
- [ ] 1 dataset published (Audit Decision Corpus)
- [ ] GitHub repo linked
### Phase 3 (Engagement) - Month 1-3
- [ ] 100+ Space views
- [ ] 50+ dataset downloads
- [ ] 5+ community discussions participated in
- [ ] 1 blog post published
### Phase 4 (Impact) - Month 3-6
- [ ] Other projects referencing Tractatus dataset
- [ ] Citations in research papers
- [ ] Community contributions (issues, questions, collaborations)
- [ ] Cross-promotion with similar governance projects
---
## Resources Needed
### Time Investment
- **Setup (Week 1)**: 4-6 hours
- Account creation, organization setup, branding
- **Space Development (Week 2-3)**: 12-16 hours
- Build Audit Log Viewer in Gradio
- Test and deploy
- **Dataset Preparation (Week 3-4)**: 8-10 hours
- Anonymization scripts
- Data export and formatting
- Documentation
- **Ongoing (Monthly)**: 4-6 hours
- Dataset updates
- Blog posts
- Community engagement
### Skills Required
- Python (Gradio/Streamlit) - for Spaces
- Data anonymization - for datasets
- Technical writing - for documentation
- Community engagement - for discussions
### Content Preparation
- [ ] Anonymize audit logs
- [ ] Export metrics aggregations
- [ ] Prepare incident case studies
- [ ] Write framework documentation
- [ ] Create visualization diagrams
---
## Risks & Mitigation
### Risk 1: Low Engagement
**Mitigation**:
- Cross-promote from website/Reddit/Facebook
- Collaborate with existing HF governance projects
- Regular updates (quarterly dataset releases)
### Risk 2: Data Privacy Concerns
**Mitigation**:
- Thorough anonymization
- No customer/user data
- Only framework decisions (internal operations)
- Clear documentation of what's included/excluded
### Risk 3: Maintenance Burden
**Mitigation**:
- Start with 1 Space (Audit Log Viewer)
- Automate data exports
- Quarterly updates, not daily
- Community contributions welcome
---
## Next Steps (Immediate)
1. **Create personal HF account** (5 min)
2. **Decide organization name** (tractatus-framework vs agentic-governance)
3. **Create anonymization script** for audit logs
4. **Build minimum viable Audit Log Viewer** Space
5. **Export first dataset** (500-1000 anonymized decisions)
---
## Long-Term Vision
**Year 1**: Establish presence, publish datasets, deploy 2-3 Spaces
**Year 2**: Regular blog posts, community collaborations, dataset citations
**Year 3**: Reference implementation for governance frameworks on HF
**Goal**: Make Tractatus the go-to governance framework example on Hugging Face, showing how architectural constraints can work in production.
---
**Alignment with Tractatus Values:**
- **Transparency** (inst_010): Public audit logs, open datasets
- **Community** (inst_012): Open collaboration, knowledge sharing
- **Evidence-Based** (inst_086): Real operational data, not theory
- **Candid About Limitations** (inst_088): Honest about what works/doesn't
**Status**: Ready to proceed with Phase 1