Pre-mortem — fail-it-before-you-build-it
A retrospective for a project that hasn't happened yet. Surfaces real
risks that "list every risk" prompts miss.
Originated in Gary Klein's research at MIT Sloan, now standard at AWS
and other ops-mature orgs.
The 5-step pre-mortem
Step 1. Imagine you're 6 months in the future
The project shipped. It is a clear, public failure. There's a Reddit
thread about it. The CEO is asking what went wrong.
Step 2. Write the post-mortem newspaper headline
One sentence. Concrete. Specific. Examples:
- ❌ Bad: "We had some quality issues."
- ✅ Good: "On 2026-09-12, the Stripe webhook handler deduplicated by raw body hash, so 30K customers were double-charged after Stripe retried delivery during a network blip."
The headline forces you to name the failure mode SPECIFICALLY.
Step 3. List every individual reason this exact failure happened
Brainstorm 10-15 reasons. Be specific. Each item should reference:
- A real component / file
- A real failure mode (race condition, schema mismatch, expired credential)
- A real human factor (oncall didn't see alert, runbook was outdated)
Reject hand-waves like "testing was insufficient." Replace with "we
didn't write a property-based test for the dedup-key collision case."
Step 4. Rank by likelihood × severity
For each cause, score:
- Likelihood: 1-5 (1=once-in-a-decade, 5=monthly)
- Severity: 1-5 (1=cosmetic, 5=data loss / regulatory breach)
- Risk score: likelihood × severity
Top 3 by risk score → these are your highest-priority mitigations.
Step 4b. Classify risks — Tigers / Paper Tigers / Elephants
After scoring, classify each risk into one of three types:
🐯 Tigers — Real problems you personally believe could derail the project
- Based on evidence, past experience, or clear logic
- Should keep you awake at night
- Require concrete action
- Classify each Tiger by urgency:
- Launch-Blocking: Must be resolved before shipping (broken core feature, regulatory blocker, data integrity risk)
- Fast-Follow: Must be resolved within 30 days post-launch (performance issues, secondary features)
- Track: Monitor post-launch, fix if it becomes an issue (edge cases, nice-to-haves)
📄 Paper Tigers — Concerns others might raise that you don't believe are real risks
- Valid-sounding on the surface but unlikely or overblown
- Not worth significant resource investment
- Worth documenting to align stakeholders and avoid repeated debates
- For each: explain WHY you don't believe it's a real risk
🐘 Elephants — Things the team knows about but isn't discussing openly
- Uncomfortable concerns: technical debt, team tension, unrealistic timeline, design that nobody likes
- Uncertain — you're not sure if it's a problem, but nobody is investigating
- Deserve explicit surfacing before launch — silent elephants become Tigers post-launch
Step 5. For each top-3 cause, write a guardrail in the plan
Each guardrail is a concrete change to the plan:
- A test that would have caught it
- A circuit breaker / feature flag
- A runbook entry
- A monitoring alert with specific SLO
If a top-3 cause CANNOT be mitigated within the time/budget, escalate to
the user: "This plan accepts the risk of X with no mitigation."
Template — add to PLAN-*.md
## Pre-mortem
Six months from now, this project failed. Headline:
> <one-sentence failure headline>
### Top reasons (likelihood × severity)
| Cause | L | S | Risk | Mitigation in plan |
|---|---|---|---|---|
| <specific cause> | 4 | 5 | 20 | <Task #N: write idempotency test> |
| ... | | | | |
### 🐯 Tigers (real risks — require action)
| Tiger | Classification | Mitigation | Owner | Due |
|-------|---------------|-----------|-------|-----|
| <risk> | Launch-Blocking | <concrete action> | <team/person> | <date> |
| <risk> | Fast-Follow | <concrete action> | <team/person> | <date> |
| <risk> | Track | <monitoring approach> | <owner> | post-launch |
### 📄 Paper Tigers (overblown — document to align stakeholders)
- **<concern>**: Not a real risk because <reason>. If <condition> changes, revisit.
### 🐘 Elephants (unspoken — needs open discussion)
- **<concern>**: Nobody is talking about this. Suggested conversation: "<how to raise it>".
### Accepted risks (no mitigation)
- <risk> — accepted because <budget/scope reason>. Owner: <name>.
Common failure modes by archetype
Quick start — most-common pre-mortem causes per archetype:
| Archetype | Common failure |
|---|
| fintech / commerce | Idempotency-key collision; double-charge during retry storm |
| healthcare | PHI leak via debug log; BAA not signed with vendor |
| web3 | Oracle staleness; flash-loan exploit on bonding curve |
| mlops | Training/serving skew; model drift undetected |
| iot-embedded | OTA bricks devices in a region with no recovery path |
| data-platform | Late-arriving data overwrites correct values |
| ai-system / agent-product | Prompt injection exfiltrates other users' data |
| enterprise-saas | Cross-tenant data leak via RLS gap |
| cli-tool | Destructive flag with no confirmation (rm -rf equivalent) |
| library | Breaking change in minor version bump |
Anti-patterns in pre-mortems
❌ Vague risks. "Performance might be a problem." Be specific: which
operation, at what load, what's the SLO.
❌ Cosmic risks. "AWS could go down." Yes, but that's not actionable.
Focus on what you can mitigate.
❌ Defensive list. Listing risks you've already mitigated to look
thorough. Only list risks the current plan does NOT yet address.
❌ Skip the headline. Without the headline, the team won't believe
the failure scenario is real.
When to skip
- nano project_size — pre-mortem is overhead.
- Pure refactor with full test coverage — guardrails already exist.
- Bug-fix with one-line repro — risk is well-bounded.