Architecting Prompt Workflow Systems

Given a rough draft prompt or raw concept, don't immediately expand it. First run the Post-Mortem Evaluation (see Workflow Step 1) to score it and expose structural gaps. Only after that, build the 5-Phase Prompt System (Steps 2-6). Output as chunked, sequential deliverables if the full system would exceed context — state "Remaining pending responses: N of N" at the end of each chunk.

Example invocation pattern:

Input: "Generate a market forecast using all data sources, be accurate and novel, 
list what's missing from this prompt too."
Output: Scoring matrix + gap analysis + tactical rewrite recommendations
        → then, on request, the full 10-prompt phased system

Progress:

• Step 1: Post-mortem score the seed prompt/concept
• Step 2: Phase 1 — Ingestion & Strategic Scoping
• Step 3: Phase 2 — Human-in-the-Loop Triaging & Filtering
• Step 4: Phase 3 — Adversarial Stress-Testing (Red Team)
• Step 5: Phase 4 — Product/Concept Conceptualization & Blueprinting
• Step 6: Phase 5 — Execution & Continuous Monitoring
• Step 7: Advanced Concept Matrix (emergent/second-order effects)

Step 1: Post-Mortem Evaluation (always do this first)

Diagnose the seed prompt for conflated meta-goals — the most common failure is commanding the AI to execute a task and audit itself in the same breath. This causes execution drift.

Produce:

1. Quantitative Scoring Matrix — score 5-6 dimensions (e.g., Methodological Intent, Data Silo Architecture, Variables & Modularity, Operational Feasibility, Prompt Telemetry & Safety) on a 0-10 scale, each with a one-line bottleneck note. Compute a composite score.
2. Structured Gap Analysis — numbered list, each gap has: Why it's essential + Mechanism of Failure (how, mechanically, the LLM breaks without it).
3. Tactical Recommendations — concrete rewrites: bracketed variable blocks, explicit negative constraints ("strictly forbid X"), and a two-pass architecture split (meta-prompt generator vs. execution prompts) if goals were conflated.

Never skip straight to "building the system" without this diagnostic — it anchors every downstream phase's guardrails.

Step 2-6: Build the 5-Phase System

Each phase = 2 prompts. Each prompt follows this exact template shape:

System Role: [Persona + one-sentence task]
Variables to Insert: [BRACKETED_TOKENS] with example values
Objective: [one sentence, outcome-oriented]
Deterministic Logic Chain: [3 numbered steps, each a concrete operation not a vague goal]
Output Blueprint: [named artifacts, e.g., "Scorecard Table", "Forensic Report" — never "a summary"]

Phase 1 — Ingestion & Strategic Scoping

• Contextual Anchor: converts org constraints (budget, moat, timeline, exclusions) into a Boundary Matrix + Moat Alignment Index.
• Exhaust Map Validator: audits candidate data channels for noise-to-signal ratio, manipulation risk (bots/SEO/PR), and proxy validity before any pattern-matching begins.

Phase 2 — Human-in-the-Loop Triaging

• Signal Sieve: scores raw AI-discovered anomalies against human conviction input; outputs Proceed/Pivot/Kill decisions via a Velocity ÷ Friction index.
• Bricolage Recombinator: forces pairing of Signal A (mechanic from unrelated domain) with Signal B (underserved pain point) into a novel hybrid concept.

Phase 3 — Adversarial Stress-Testing

• False Positive Dissector: actively tries to debunk the trend — checks for bot/seasonal/echo-chamber artifacts, outputs an "Artificially Inflated" probability score.
• Narrative Counter-Weight: builds the Bear Case — incumbent asymmetry, fatal barriers, and a falsification thesis (the exact metric that would kill the idea).

Phase 4 — Product Conceptualization & Blueprinting

• Meso-Scale Translator: bridges macro trend + micro signal into functional specs, respecting MVP constraints; outputs a Fragmented Task Log.
• Value Proposition Matrix: mirrors target-user vocabulary exhaust, contrasts against bloated incumbents, anchors pitch in a non-speculative value metric.

Phase 5 — Execution & Continuous Monitoring

• Exhaust Tracking Dashboard Spec: defines Safe/Warning/Critical thresholds per data channel; detects signal decay via rolling-window comparison to baseline.
• Feedback Loop Calibration: audits variance between projection and reality, isolates where the original prompt logic over-fit or hallucinated, outputs corrected prompt fragments to paste back into Phase 1-2.

Step 7: Advanced Concept Matrix (optional extension)

After the lifecycle system is specified, generate emergent/second-order effects: what new properties appear once all 5 phases run continuously (e.g., cross-domain epistemological bridges, asynchronous multi-agent decomposition, compounding calibration effects). Present as a short causal chain diagram + 3 numbered "Emergent Property → Second-Order Effect" entries.