Assumption Grading

RISK — What's the impact if we're wrong?

• High: Project fails, major wasted resources, wrong direction
• Medium: Significant rework needed, delays, budget impact
• Low: Minor adjustments, easy to correct

3. Prioritize Validation

Focus on assumptions that are:

1. Low certainty + High risk — VALIDATE IMMEDIATELY
2. Low certainty + Medium risk — Validate before major commitments
3. Medium certainty + High risk — Validate before proceeding
4. High certainty + Low risk — Can proceed with monitoring

4. Plan Validation

For each high-priority assumption, define:

• What would prove this true or false?
• What's the cheapest/fastest way to test it?
• Who can provide evidence?
• When do we need to know?

5. Update currentstate.json

Record each assumption with:

{
  "id": "a1",
  "description": "Users want automated reporting",
  "certainty": "low",
  "risk": "high",
  "validation_plan": "Interview 5 users about reporting needs and current workflows",
  "status": "open"
}

Example Assessment

Assumption: "Users will adopt mobile app over desktop"

• Certainty: Low (based on industry trends, not our users)
• Risk: High (entire platform strategy depends on this)
• Priority: VALIDATE IMMEDIATELY
• Validation Plan: Interview current users about device usage patterns and preferences

Assumption: "API can handle 1000 requests/second"

• Certainty: Medium (vendor specs, but not tested)
• Risk: High (performance is core requirement)
• Priority: Validate before prototyping
• Validation Plan: Load testing with production-like data

Assumption: "Users understand technical jargon"

• Certainty: Low (no evidence)
• Risk: Low (can adjust language easily)
• Priority: Test during iteration, easy to fix

Tips

• Be explicit about what you're assuming
• Don't confuse hope with certainty
• High certainty still means "could be wrong"
• Update grades as you learn
• Re-grade assumptions at phase transitions