BJS Labs Game Strategy Skill

Strategic decision-making framework for BJS Labs. Treats business as a game with clear state, moves, and win conditions.

When to Use This Skill

Before making a significant business decision
After completing a major action (close client, ship feature, etc.)
Weekly strategic review
When feeling uncertain about priorities
Keywords: strategy, decision, priority, should we, next move, game state

Core Files

Game State: ~/.openclaw/workspace/memory/bjs-game-state.md
Decision Log: Embedded in game state file
Win Conditions: Level 1 = $300K ARR, Level 2 = $500K, Level 3 = $1M

Pre-Decision Protocol

Before any significant move, ask:

1. State Check

What is our current state?
- MRR: $X
- Clients: N
- Team capacity: Y%
- Runway: Z months

2. Move Analysis

What move are we considering?
- Expected effect: [+/- what metrics]
- Cost: [time/money/opportunity]
- Risk: [what could go wrong]
- Reversibility: [easy/hard to undo]

3. Goal Alignment

Does this move get us closer to Level 1?
- Revenue impact: [+/-/$0]
- Capacity impact: [+/-/0]
- Learning value: [high/medium/low]

4. Alternative Moves

What else could we do instead?
- Option A: [move] → [expected outcome]
- Option B: [move] → [expected outcome]
- Do nothing: → [what happens]

Post-Decision Protocol

After completing a significant action:

1. Record the Move

| Date | Move | Expected | Actual | State Change |
|------|------|----------|--------|--------------|
| YYYY-MM-DD | ACTION | Expected | Result | +/- metrics |

2. Update State

Adjust MRR, client count, capacity
Note any surprises
Identify new information learned

3. Recalculate Distance

Are we closer to Level 1?
Did new moves become available?
Did any moves become blocked?

4. Identify Triggers

Did we hit a transformation trigger?
What unlocked?

Move Categories

🟢 High-Impact (Do These)

Close paying client
Get referral
Ship feature clients asked for
Automate manual bottleneck

🟡 Medium-Impact (Consider)

Content marketing
New integrations/skills
Process improvements
Team training

🔴 Low-Impact (Avoid Unless Strategic)

Features nobody asked for
Premature optimization
Hiring before revenue
Building vs. selling

Quick Evaluation Framework

For any proposed action, score 1-5:

| Criteria | Score | Weight | |----------|-------|--------| | Revenue impact | ? | 3x | | Learning value | ? | 2x | | Capacity cost | ? | 1x | | Risk level | ? | 1x |

Weighted Score = (Revenue × 3) + (Learning × 2) - Capacity - Risk

Score > 10: Strong yes
Score 5-10: Consider carefully
Score < 5: Probably skip

Weekly Review Questions

What moves did we make this week?
What was the actual vs expected outcome?
Are we closer to Level 1 than last week?
What did we learn that changes our model?
What's the highest-impact move for next week?

Transformation Triggers to Watch

These fundamentally change the game:

[ ] First paying client
[ ] First referral
[ ] $10K MRR
[ ] 10 active clients
[ ] Agent handles issue autonomously
[ ] Client churn (learning opportunity!)

Example Decision Flow

Situation: Should we build Feature X?

1. STATE CHECK
   - Current MRR: $0
   - Clients requesting: 0
   - Capacity available: Yes

2. MOVE ANALYSIS
   - Expected: +value prop
   - Cost: 2 weeks dev time
   - Risk: Nobody uses it
   - Reversible: Yes (can deprecate)

3. GOAL ALIGNMENT
   - Revenue impact: $0 direct
   - Capacity impact: -2 weeks
   - Learning value: Low (no client feedback)

4. ALTERNATIVES
   - Option A: Build it → Might attract clients
   - Option B: Talk to prospects → Learn what they need
   - Do nothing: → No change

5. DECISION
   Score: (0×3) + (1×2) - 2 - 1 = -1
   → SKIP. Talk to prospects first.

Commands

Check Game State

cat ~/.openclaw/workspace/memory/bjs-game-state.md

Log a Decision

Append to the Decision Log table in bjs-game-state.md

Update Metrics

Edit the Core Metrics table after state changes