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Opportunities

Action items derived from Knowledge-First and AI-First principles.

Total opportunities

Completed

Pending

Priority Queue

#	Opportunity	Impact	Status
1	Build Worca Community Playbooks	Unblock failing project	Pending
2	Document Coach Frameworks	Reduce dependency, compound knowledge	Pending
3	Connect Research to Writings Pipeline	Leverage existing knowledge for content	Pending
4	Evaluate Jim & Fenny for AI-First	Potential to reduce collaborators	Pending
5	Evaluate Angel Pipeline Frontend	Simplify if AI can replace	Pending
6	Cross-Business Knowledge Sharing	Compound insights across ventures	Pending
7	Anna Playground Knowledge Layer	Personalize teaching with AI	Pending

Detailed Breakdown

Build Worca Community Playbooks

High Priority

Problem

Discord community is failing. Lydia lacks expertise, falling behind.

Solution

Build knowledge first, then AI can execute.

Target Structure

worca/community/
├── CLAUDE.md           # Goals, voice, what success looks like
├── playbooks/
│   ├── weekly-engagement.md
│   ├── onboarding-new-members.md
│   └── event-promotion.md
└── templates/
    └── announcement.md

Steps

Define community goals and success metrics
Document what "good engagement" looks like
Create playbooks for recurring activities
Test AI execution on one playbook
Transition from Lydia to AI-first

Document Coach Frameworks

Problem

Luke (GTM) and Doyle (Sales) provide valuable expertise, but it lives in their heads and your call notes.

Solution

After each session, capture frameworks as reusable knowledge.

Target Structure

worca/strategy/
├── CLAUDE.md
├── gtm-frameworks/          # From Luke
│   ├── positioning.md
│   ├── channel-strategy.md
│   └── messaging.md
└── sales-frameworks/        # From Doyle
    ├── closing-playbook.md
    ├── objection-handling.md
    └── pipeline-management.md

Steps

After next Luke session, document one framework
After next Doyle session, document one framework
Test: Can AI apply framework to a real situation?
Over time, reduce coaching frequency as knowledge accumulates

Connect Research to Writings Pipeline

Problem

self/research/ has valuable thinking. work/writings/ needs content. No connection.

Solution

Make research a source for public writing.

Implementation

Add to writings/CLAUDE.md:

## Source Material

When generating content, reference:
- `self/research/writings/` — personal essays and thinking
- `self/research/ideas/` — raw ideas to develop
- `self/research/sources/` — external references

Transform private research into public content while
preserving appropriate boundaries.

Steps

Audit self/research/ — what's publishable vs. private?
Add cross-reference to writings/CLAUDE.md
Test: AI drafts one blog post from research material

Evaluate Jim & Fenny for AI-First

Problem

HIHQ was built without human devs. Why does Worca need Jim (tech) and Fenny (PM)?

Questions to Answer

What exactly does Jim do week-to-week?
What exactly does Fenny do week-to-week?
Could Claude Code do any of this with proper context?

Possible Outcomes

Outcome	Action
Work is AI-replaceable	Transition to AI-first, they become reviewers or redeploy
Work requires human judgment	Keep, but document their frameworks
Mixed	Split responsibilities — AI handles routine, humans handle judgment

Steps

List Jim's recurring tasks
List Fenny's recurring tasks
For each task, ask: Could AI do this with proper context?
Make decision

Evaluate Angel Pipeline Frontend

Problem

angel-pipeline/frontend/ exists. But knowledge-first suggests AI-generated reports might suffice.

Questions

What does the frontend do?
Who uses it? (Just you, or shared?)
Could AI generate the same insights from markdown deal files?

Decision Matrix

If...	Then...
Frontend is just for you	Replace with AI-generated summaries
Frontend is shared with others	Keep, but evaluate if needed
Frontend has unique value	Keep

Steps

Document what frontend provides
Test: Can AI generate equivalent from md files?
Decide: Keep, deprecate, or simplify

Cross-Business Knowledge Sharing

Problem

Three businesses (Worca, HIHQ, Angel) operate in silos. Potential synergies unexploited.

Synergies Identified

From	To	Knowledge Transfer
Angel	HIHQ	Founder pain points → product features
HIHQ	Worca	AI tools → talent operations
Worca	Angel	Talent patterns → founder evaluation

Options

Option A: Shared insights folder

work/insights/
├── founder-patterns.md   # From Angel
├── talent-signals.md     # From Worca
└── ai-applications.md    # From HIHQ

Option B: Cross-references in CLAUDE.md

Each business's CLAUDE.md points to relevant context in other businesses.

Steps

Identify one concrete insight that crosses businesses
Test: Document it, see if AI applies it correctly
Decide on structure (shared folder vs. cross-references)

Anna Playground Knowledge Layer

Problem

anna-playground/ is code projects. No knowledge layer for AI to understand Anna's learning context.

Solution

Add context so AI can personalize teaching.

Target Structure

family/anna-playground/
├── CLAUDE.md           # Anna's current level, learning style, goals
├── curriculum.md       # What she's learned, what's next
├── repos/              # Actual code projects
└── notes/              # Observations, breakthroughs, struggles

Example CLAUDE.md

# Anna's Coding Journey

## Current Level
- Comfortable with: HTML, basic CSS
- Learning: JavaScript fundamentals
- Struggles with: Loops, understanding why code runs in order

## Learning Style
- Prefers visual examples
- Needs to see "why" before "how"
- Short sessions (30 min max)

## Goals
- Build a simple game by summer
- Understand enough to modify existing projects

Steps

Write initial CLAUDE.md based on current understanding
Test: Does AI provide appropriate-level explanations?
Iterate as Anna progresses