Diagnostic Toolkit
Use this lightweight toolkit to triage issues before you invest in builds.
Master diagnostic
Problem unclear → Run Problem Validation Interviews → Evidence of active solution seeking?
└─ No → Strengthen Problem Fit first
└─ Yes → Behavior unclear → Run Behavioral Observation → Will users perform behavior in context?
└─ No → Choose a different behavior or change context
└─ Yes → Prototype solution → Time to first behavior acceptable?
└─ No → Reduce friction and steps
└─ Yes → Verify Product Fit and unit economics
Next: Use the Four-Fit Evidence Readiness Checker to see which evidence records and pre-registered thresholds are missing. It does not judge initiative viability. Then use the BOS Calculator.
Advanced Diagnostics
Problem Diagnosis Tool (programmatic)
class ProblemDiagnosticTool:
"""
Check behavioral assumptions before a build.
"""
def __init__(self):
self.diagnostic_questions = {
'problem_validation': [
"Can users clearly articulate the problem?",
"Are users actively seeking solutions?",
"Have users tried multiple workarounds?",
"Would users pay (time/money) for solution?",
"Is problem frequent and painful?"
],
'behavior_validation': [
"Have you observed target behaviors in natural context?",
"Does observed completion clear a pre-registered threshold?",
"Do behaviors align with user motivations?",
"Is behavioral frequency sustainable?",
"Are behaviors measurable?"
],
'solution_validation': [
"Does every feature map to validated behavior?",
"Is time to first behavior within a pre-registered target?",
"Is the behavioral path obvious?",
"Are behavioral triggers built-in?",
"Do users feel successful after behavior?"
]
}