The Symptom Layer Discovery

Use it for

Ontology Is Not a Buzzword — It’s a Clarity Machine

The prompt

# The Symptom Layer Discovery

Map the gap between what you sell and what your clients actually experience before they know they need help — surfacing pre-awareness symptoms, client-language queries, and content blind spots.

MY EXPERTISE: $ARGUMENTS

MY IDEAL CLIENT: [BRIEF DESCRIPTION. Say "you decide" to infer]

STEP 0 — PERSPECTIVE SELECTION: Adopt at minimum: the CLIENT's inner monologue + an ONTOLOGY ANALYST mapping the structural gap. Additionally, select perspectives revealed by the specific expertise.
STEP 1 — ROOT CAUSE MAPPING: Identify 3-5 root cause problems. Distinguish STRUCTURAL root cause from EXPERIENTIAL root cause.
STEP 2 — SYMPTOM EXCAVATION: For each root cause, map 3-5 pre-awareness symptoms. Must be: observable, felt, and pre-diagnostic. Test: would this person describe it to a friend over drinks?
STEP 3 — CLIENT-LANGUAGE QUERIES: For each symptom, 3 queries ranging from vague/emotional to specific/situational to AI-conversational.
STEP 4 — CONTENT GAP ANALYSIS: Assess each symptom-query pair: COVERED, PARTIALLY COVERED, or BLIND SPOT.
STEP 5 — VERIFICATION: Are symptoms genuinely pre-awareness? Are queries realistic? Am I projecting assumed psychology or grounding in behavior?

OUTPUT FORMAT: Table (Root Cause → Symptom → Query x3 → Gap Status) + Top 5 blind spots ranked by search volume × connection to offering, with specific content piece suggestions.

Worked example

No worked example recorded yet.