# Mind v5 - Roadmap to Launch

> From "works on my machine" to "works for everyone"

---

## Current State

```
User Experience Today:
1. Clone repo
2. Install Docker
3. Run docker-compose up
4. Configure Claude Desktop MCP manually
5. Hope it works
6. No feedback if it's learning
```

**Result:** Only developers can use it. High friction. No wow moments.

---

## Target State

```
User Experience Target:
1. Add Mind to Claude Desktop (one click)
2. Start chatting - Mind works automatically
3. See "Mind remembered this" indicators
4. Get weekly "Mind got smarter" updates
```

**Result:** Anyone can use it. Zero friction. Clear value.

---

## Phase 1: Foundation (Week 1-2)
### Make it Installable

#### 1.1 Create Mind Cloud API
**What:** Hosted version of Mind backend
**Why:** Users don't need Docker
**How:**
- [ ] Deploy Mind API to cloud (Railway/Fly.io/AWS)
- [ ] Add authentication (API keys)
- [ ] Add rate limiting (free tier limits)
- [ ] Add user signup flow
- [ ] Create api.mind.vibeship.ai endpoint

**Files to create:**
```
src/mind/cloud/
  auth.py          # API key validation
  rate_limiter.py  # Usage tracking
  signup.py        # User registration
```

#### 1.2 Publish MCP Package
**What:** `uvx mind-mcp` that connects to Mind Cloud
**Why:** One command to add Mind to any Claude setup
**How:**
- [ ] Create pyproject.toml for mind-mcp package
- [ ] Publish to PyPI
- [ ] Support both cloud and self-hosted modes
- [ ] Auto-detect API key from ~/.mind/config

**Package structure:**
```
mind-mcp/
  pyproject.toml
  src/mind_mcp/
    __init__.py
    server.py      # MCP server
    config.py      # API key management
    cloud.py       # Cloud API client
```

**Usage after publish:**
```bash
# First time - opens browser for signup
uvx mind-mcp

# After signup - just works
uvx mind-mcp
```

#### 1.3 Auto-Configure Claude Desktop
**What:** Script that adds Mind to claude_desktop_config.json
**Why:** Zero manual configuration
**How:**
- [ ] Detect Claude Desktop config location
- [ ] Add mind-mcp to mcpServers
- [ ] Restart Claude Desktop if running

**One-liner install:**
```bash
curl -fsSL https://mind.vibeship.ai/install | bash
```

---

## Phase 2: First Impressions (Week 2-3)
### Make the First 5 Minutes Amazing

#### 2.1 Welcome Experience
**What:** Friendly onboarding when Mind first runs
**Why:** Users need to know it's working

**Current response:**
```json
{"memory_id": "abc123", "effective_salience": 1.0}
```

**New response:**
```
Memory stored successfully!

I'll remember: "User prefers TypeScript"
Level: Identity (permanent preference)
Confidence: 100%

Your Mind now has 1 memory. I'll use this to give better recommendations.

Tip: The more you tell me, the smarter I get!
```

**Implementation:**
- [ ] Add `--friendly` mode to MCP (default on)
- [ ] Create response formatter
- [ ] Add contextual tips

#### 2.2 First Retrieval Celebration
**What:** Show when Mind influences a response
**Why:** Users need to SEE the value

**Add to Claude responses:**
```
[Mind activated: 2 memories influenced this response]
- "Prefers TypeScript" (high relevance)
- "Likes minimal dependencies" (medium relevance)
```

**Implementation:**
- [ ] Return metadata with retrievals
- [ ] Format for human readability
- [ ] Add relevance indicators

#### 2.3 Learning Confirmation
**What:** Show when Mind learns from feedback
**Why:** The core "aha!" moment

**When user gives feedback:**
```
Thanks! Mind learned from this.

Memory "Prefers TypeScript" is now stronger.
- Old confidence: 70%
- New confidence: 79%

This memory will rank higher in future retrievals.
```

**Implementation:**
- [ ] Add before/after to outcome response
- [ ] Show delta clearly
- [ ] Explain what it means

---

## Phase 3: Visibility (Week 3-4)
### Make Learning Visible

#### 3.1 Web Dashboard
**What:** mind.vibeship.ai/dashboard
**Why:** Visual way to see your Mind

**Features:**
- [ ] Memory browser (search, filter, edit)
- [ ] Learning timeline (salience changes over time)
- [ ] Decision history (what Mind influenced)
- [ ] Statistics (memories by level, success rate)

**Stack:** Next.js + Tailwind + Mind API

#### 3.2 Learning Digest
**What:** Weekly email/notification
**Why:** Show long-term value

**Content:**
```
Your Mind This Week

Memories:
- 5 new memories stored
- 3 memories got stronger
- 1 memory got weaker

Decisions:
- 12 decisions influenced
- 83% positive outcomes

Top performing memory:
"Prefers TypeScript" - helped 8 decisions

[View Dashboard]
```

**Implementation:**
- [ ] Create digest generator
- [ ] Set up email service (Resend/Postmark)
- [ ] Weekly cron job

#### 3.3 Session Continuity
**What:** Remember context across sessions
**Why:** Makes Mind feel intelligent

**On new session:**
```
Welcome back!

Last session (2 hours ago):
- You were working on the API project
- Made 3 decisions Mind influenced
- All had positive outcomes

Ready to continue?
```

**Implementation:**
- [ ] Store session summaries
- [ ] Surface on reconnect
- [ ] Link to relevant memories

---

## Phase 4: Delight (Week 4-5)
### Create "Wow" Moments

#### 4.1 Proactive Warnings
**What:** Mind warns about past failures
**Why:** Prevents mistakes, shows intelligence

**Example:**
```
Hold on - I found a relevant memory:

3 months ago, you tried MongoDB for a similar project.
The outcome was negative: "Too complex for simple use case"

Should I:
1. Proceed anyway
2. Suggest alternatives
3. Tell me what's different this time
```

**Implementation:**
- [ ] Negative outcome detection
- [ ] Similarity matching
- [ ] Warning generation

#### 4.2 Pattern Discovery
**What:** Mind finds trends you didn't notice
**Why:** Creates genuine insight

**Example:**
```
I noticed a pattern!

Your successful projects often have:
- TypeScript (87% success)
- No ORM (82% success)
- REST over GraphQL (79% success)

Should I factor this into recommendations?
```

**Implementation:**
- [ ] Pattern extraction from decisions
- [ ] Statistical significance testing
- [ ] User-friendly presentation

#### 4.3 Explainability
**What:** Mind explains its reasoning
**Why:** Builds trust

**Example:**
```
Why I recommended Express:

Memories that influenced this:
1. "Prefers well-documented libraries" (40% weight)
2. "Values stability" (30% weight)
3. "TypeScript preference" (20% weight)

Historical context:
- You chose Express in 3 past projects
- All had positive outcomes

Confidence: 78%
```

**Implementation:**
- [ ] Attribution breakdown
- [ ] Confidence explanation
- [ ] Historical context

---

## Phase 5: Growth (Week 5-6)
### Make it Shareable

#### 5.1 Public Patterns (Opt-in)
**What:** Share anonymized patterns with community
**Why:** Collective intelligence

**Example:**
```
Community Insights:

Top patterns from Mind users:
1. "TypeScript + Zod for validation" - 94% success
2. "PostgreSQL for structured data" - 91% success
3. "pnpm over npm" - 88% success

[Apply to my Mind]
```

**Implementation:**
- [ ] Pattern anonymization
- [ ] Differential privacy
- [ ] Community aggregation

#### 5.2 Team Sharing
**What:** Share Mind across team
**Why:** Enterprise value

**Features:**
- [ ] Team workspaces
- [ ] Shared patterns
- [ ] Individual + team memories
- [ ] Admin controls

#### 5.3 Referral System
**What:** Share Mind, get rewards
**Why:** Viral growth

**Features:**
- [ ] Referral links
- [ ] Free months for referrals
- [ ] Leaderboard

---

## Implementation Priority

### This Week (Highest Impact)
1. [ ] Deploy Mind Cloud API
2. [ ] Publish mind-mcp to PyPI
3. [ ] Create install script
4. [ ] Add friendly responses

### Next Week
5. [ ] Build web dashboard MVP
6. [ ] Add memory attribution to responses
7. [ ] Create welcome experience

### Week After
8. [ ] Weekly digest emails
9. [ ] Session continuity
10. [ ] Pattern discovery

---

## Success Metrics

### Week 1
- [ ] 10 beta users installed
- [ ] 100 memories stored
- [ ] 50% return after 24 hours

### Week 2
- [ ] 100 users installed
- [ ] 1,000 memories stored
- [ ] 30% weekly retention

### Month 1
- [ ] 1,000 users
- [ ] 10,000 memories
- [ ] First paying customers
- [ ] NPS > 50

---

## Technical Debt to Address

1. [ ] Response format standardization
2. [ ] Error messages user-friendly
3. [ ] Logging for debugging user issues
4. [ ] Rate limiting implementation
5. [ ] API versioning (v1 stable)

---

## Questions to Answer

1. **Pricing:** Free tier limits? Pro price point?
2. **Privacy:** What data do we see vs user only?
3. **Branding:** Mind? MIND? mind? Logo?
4. **Domain:** mind.vibeship.ai? getmind.ai? mindmcp.com?

---

*Goal: From "git clone" to "it just works" in 2 weeks.*
