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NAVIGATION

6 min read

Eden Project - AI Navigation Guide

Last Updated: January 20, 2026
Purpose: Help AI assistants quickly find relevant documentation

📂 Project Structure

tryeden/
├── agentic_workflows/          ← AI-powered data workflow system
│   ├── framework.md            ← Core philosophy & methodology
│   ├── slash_commands.md       ← Ready-to-use prompts for Cursor
│   └── quickstart.md           ← Get started in 4 hours
│
├── strategic_planning/         ← Leadership alignment & priorities
│   ├── elt_priorities_roadmap.md      ← What ELT wants vs what we've shared
│   ├── leadership_quick_reference.md  ← Quick reference for meetings
│   └── next_2_weeks_action_plan.md    ← Immediate tactical plan
│
├── case_studies/               ← Proven wins to reference
│   ├── affiliate_capabilities_comparison.md  ← 2025 vs 2026 improvements
│   └── affiliate_data_framework.md           ← How we built attribution system
│
├── learnings/                  ← /learning_moment outputs & pattern updates
│   └── learning_moment_2026-01-20_analysis_plan_patterns.md  ← Initiative-based plans, GS/Suggestion
│
├── test_runs/                  ← Slash-command sequence tests on analysis outlines
│   ├── README.md               ← How to run and evaluate
│   └── 2026-01-20_plan_level_unit_economics/  ← Plan-Level Unit Economics & Margin Accuracy test
│
├── linear_tickets/             ← Implementation tasks
│   └── ecommerce_best_practices.md    ← EdenOS data model work
│
├── analysis/                   ← Analysis plans & frameworks
│   ├── eden_strategic_data_analysis_roadmap.md
│   ├── eden_experimentation_analysis_outlines.md
│   └── eden_expand_telehealth_margins.md
│
├── meeting_transcripts/        ← Context from stakeholder meetings
│   ├── 2026-01-14_ELT x Brainforge Bi-weekly Check-In.md  ← Latest priorities
│   └── [140+ other transcripts]
│
└── data_platform/              ← Technical documentation
    └── [Platform specs, tracking plans, forecasting models]

🎯 Quick Reference: What to Read First

If you’re helping with:

Eden AI / Project Command Center (SL + eng):

  1. resources/eden-ai-command-center-project-plan.md — consolidated scope, phases, Linear milestone map, risks, and links (replaces scattered GitHub draft PRs for this program).

Strategic Planning:

  1. strategic_planning/elt_priorities_roadmap.md - What leadership wants
  2. strategic_planning/leadership_quick_reference.md - Meeting cheat sheet
  3. meeting_transcripts/2026-01-14_ELT x Brainforge Bi-weekly Check-In.md - Latest from leadership

Data Analysis:

  1. agentic_workflows/quickstart.md - How to use AI workflow
  2. agentic_workflows/slash_commands.md - Copy-paste prompts
  3. agentic_workflows/framework.md - Deep dive on methodology

Affiliate Work:

  1. case_studies/affiliate_data_framework.md - How attribution works
  2. case_studies/affiliate_capabilities_comparison.md - Before/after story

EdenOS / Data Infrastructure:

  1. linear_tickets/ecommerce_best_practices.md - Tickets for Shopify-level standards
  2. analysis/eden_strategic_data_analysis_roadmap.md - Strategic initiatives

🔍 Common AI Tasks & Where to Look

”Help me analyze [metric/channel/cohort]”

→ Start: agentic_workflows/quickstart.md (Hour 2: First Analysis) → Use: /discover, /plan_analysis, /execute_analysis commands → Reference: agentic_workflows/slash_commands.md for prompt templates

”Prepare for ELT meeting”

→ Read: strategic_planning/elt_priorities_roadmap.md - Top 5 priorities → Use: strategic_planning/leadership_quick_reference.md - Meeting prep → Bring: Wins that tie to 2x growth goal

”Review my SQL/analysis”

→ Use: /review command from agentic_workflows/slash_commands.md → Then: /peer_review with multiple models (Claude, GPT-4, Gemini)

“Build affiliate performance story”

→ Reference: case_studies/affiliate_data_framework.md - Technical details → Reference: case_studies/affiliate_capabilities_comparison.md - Win story → Use: /document_insights command for stakeholder deck

”Create Linear tickets for [project]”

→ Example: linear_tickets/ecommerce_best_practices.md - See template → Include: Business context, acceptance criteria, dependencies, estimates

”Run /learning_moment” or “Document learnings”

→ Use: /learning_moment from agentic_workflows/slash_commands.md → Save to: learnings/learning_moment_YYYY-MM-DD_[topic].md → Update: Slash commands, metric definitions, or patterns per “Update Knowledge Base” → Recent: learnings/learning_moment_2026-01-20_analysis_plan_patterns.md (initiative-based plans, GS/Suggestion)

“Test slash-command sequence on an analysis outline”

→ Use: test_runs/ and the run’s 04_test_protocol.md → Order: /prepare_analysis_input → /discover → /plan_analysis (gap) → /review (plan-adapted) → Input: Raw outline (PDF, doc); after /prepare_analysis_input: 00_input_proposal.md with Dataset cross-reference (baseline) vs data_platform/schema → Outputs: 01_discover_output.md, 02_plan_analysis_gap_output.md, 03_review_output.md → Evaluate: Effectiveness criteria in 04_test_protocol.md §3 → Example: test_runs/2026-01-20_plan_level_unit_economics/ (Plan-Level Unit Economics & Margin Accuracy)

📋 File Naming Conventions

Meeting Transcripts:

  • Format: YYYY-MM-DD_Meeting-Title.md
  • Example: 2026-01-14_ELT x Brainforge Bi-weekly Check-In.md

Analysis Documents:

  • Format: [client]_[topic]_[type].md
  • Example: eden_experimentation_analysis_outlines.md

Strategic Docs:

  • Format: [topic]_[subtype].md
  • Example: elt_priorities_roadmap.md

Learnings (/learning_moment):

  • Format: learning_moment_YYYY-MM-DD_[topic].md
  • Example: learning_moment_2026-01-20_analysis_plan_patterns.md

🤖 For AI Assistants: Best Practices

When Analyzing Data:

  1. Always start with /discover - Understand problem before building
  2. Reference meeting transcripts - Get stakeholder context
  3. Use multi-model review - Claude → GPT-4 → Gemini
  4. Document learnings - Use /learning_moment after each analysis

When Creating Deliverables:

  1. Know your audience - ELT vs Team Lead vs Self (different formats)
  2. Lead with business impact - “$X saved, Y% increase, Z decision enabled”
  3. Reference wins - Link to case studies for proof points
  4. Use /deslop_analysis - Remove AI verbosity before sharing

When Stuck:

  1. Check meeting transcripts - Stakeholder likely discussed this
  2. Reference case studies - Similar work probably exists
  3. Use /learning_moment - Turn confusion into teaching opportunity
  4. Ask “What decision does this inform?” - Clarify the “why”

🎓 Learning Resources

Core Methodology:

  • agentic_workflows/framework.md - 7 principles from AI-enabled PM
  • Sections: Planning > Execution, Slash Commands, Learning Faster, etc.

Immediate Implementation:

  • agentic_workflows/quickstart.md - 4-hour setup guide
  • Hour 1: Setup, Hour 2: First analysis, Hour 3-4: Second analysis

Command Reference:

  • agentic_workflows/slash_commands.md - All prompts
  • Core: /intake, /discover, /plan, /execute, /review, /document, /learn

📊 Eden Context: Key Facts

Business Model:

  • Telehealth + ecommerce (GLP-1, hair loss, hormone therapy, etc.)
  • Subscription-based with one-time purchases
  • Moving to unified healthcare platform (EdenOS)

2026 Goals:

  • 2x revenue growth
  • 3 new channel expansions
  • Marketing team scale (3 → 10+)
  • Product relaunches (not new launches)
  • Pharmacy + telehealth + health clubs integration

Key Stakeholders:

  • Mitesh: Marketing GM (needs LTV:CAC, channel performance)
  • Ryan: Experimentation Lead (needs 4 tests/month support)
  • Judd: Lifecycle Marketing (needs segment definitions, win-back campaigns)
  • Brad: Ops Lead (needs SLA tracking, operational metrics)
  • Surf: EdenOS Lead (needs ecommerce data model, best practices)

Top 5 Priorities (from Jan 14 ELT):

  1. Tell affiliate win story (they’re at conferences NOW)
  2. Support 4 experiments/month
  3. Enable self-service analytics (stop being inbox)
  4. Build for ecommerce best practices (Shopify standards)
  5. Prove channel ROI (LTV:CAC by channel)

Big Wins to Reference:

  • Affiliate program: $500K+ overpayment stopped, 15% approval rate increase
  • Attribution: Capturing 20% more data than before
  • Affiliates outperform all channels (best CVR, best retention)

🚀 Quick Start Commands

For AI helping with analysis:

1. Read: agentic_workflows/quickstart.md
2. Use: /discover [problem statement]
3. Then: /plan_analysis
4. Then: /execute_analysis
5. Then: /review + /peer_review
6. Then: /document_insights
7. Finally: /learning_moment

For AI helping with strategy:

1. Read: strategic_planning/elt_priorities_roadmap.md
2. Read: Latest meeting transcript in meeting_transcripts/
3. Reference: case_studies/ for wins to build on
4. Check: strategic_planning/next_2_weeks_action_plan.md for immediate tasks

📞 Update This File

When to update:

  • New folder created → Add to structure
  • New workflow discovered → Add to “Common AI Tasks”
  • New stakeholder → Add to “Eden Context”
  • New priority → Update from ELT meetings

Last major changes:

  • 2026-01-20: Initial creation, organized agentic workflows
  • [Future updates go here]

This navigation guide helps AI quickly understand the project structure and find relevant context. Keep it updated as the project evolves.

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