Pre-Mortem Analyst: Business & Marketing for Claude Code | AI Skill Market | AI Skill Market

Pre-Mortem Analyst: Business & Marketing for Claude Code | AI Skill Market | AI Skill Market

Pre-Mortem Analyst

Why Pre-Mortem > Risk Assessment

Risk Assessment: "What MIGHT go wrong?" → Optimism bias filters answers Pre-Mortem: "It's 6 months later. It FAILED. Why?" → Liberates honest analysis

Research: Pre-mortems increase problem identification by 30%.

The Process

Set the scene: "It's [date]. This has failed completely."
Brainstorm causes: List 10+ failure reasons (no filtering)
Categorize: People, Process, Technology, External
Rate: Likelihood × Impact (H/M/L)
Prevent: Top 3 get specific mitigation actions
Monitor: Define early warning signs

Output Format

PROJECT: [Name]
FAILURE SCENARIO: "It's [date]. [Project] has completely failed."
WHY IT FAILED:
👥 PEOPLE: [Cause] - L×I: H/H | Prevent: [x] | Warning: [y]
⚙️ PROCESS: [Cause] - L×I: M/H | Prevent: [x] | Warning: [y]
💻 TECHNOLOGY: [Cause] - L×I: L/H | Prevent: [x] | Warning: [y]
🌍 EXTERNAL: [Cause] - L×I: M/M | Prevent: [x] | Warning: [y]
TOP 3 PRIORITIES:

[Risk] → [Specific action]
[Risk] → [Specific action]
[Risk] → [Specific action]

WARNING SIGNS TO MONITOR:
□ [Early indicator 1]
□ [Early indicator 2]

Common Failure Categories

Category	Common Causes
People	Key person leaves, skill gaps, misalignment, low buy-in
Process	Aggressive timeline, scope creep, dependency issues
Tech	Doesn't scale, integration fails, security breach
External	Market shift, competitor move, regulation change

Integration

Compounds with:

inversion-strategist → Create systematic avoidance strategies
second-order-consequences → Project impact of prevented failures
first-principles-decomposer → Question hidden assumptions
mspot-generator → Validate MSPOT projects before committing

See references/examples.md for Artem-specific pre-mortems