decision-playbook

name	decision-playbook
description	9 quick-reference decision frameworks from CEO Bible — when to double down, pivot, hire, kill features, diagnose low conversion. For deep multi-phase analysis of a specific decision, use strategic-review instead.
user-invocable	true

Decision Playbooks (CEO Bible Section I)

When the founder faces a strategic decision, apply the corresponding playbook.

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1. When to Double Down on a Segment

Only when all three proofs converge:

• Pain proof: same trigger/problem/workaround across multiple conversations
• Value proof: this segment reaches TTFV faster and retention is better
• Repeatability proof: recent wins look alike: same buyer, same objections, same onboarding

Actions: Rewrite homepage/deck -> publish proof asset -> re-score PQL traffic -> pause non-core exploration for 4-6 weeks.

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2. When to Change ICP

Change when:

• Problem is real, but no budget or owner at the current buyer
• Segment requires too much education
• Activation is slow, retention is weak despite support
• Another segment is clearly easier to message, close, and retain

Don't change after one bad month. Do change when multiple types of evidence align.

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3. When to Change Positioning

Change when:

• People use and stay in the product
• BUT top-of-funnel response, call-to-next-step, demo resonance are weak
• Objections sound like confusion, not rejection

Action: Interview recent signups -> capture exact words -> draft new messaging -> test comprehension -> validate quantitatively.

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4. When to Kill a Feature

Kill/freeze when ALL of these are true:

• Target-cohort usage is low
• Doesn't improve activation, retention, win rate, or outcome attainment
• Adds onboarding or roadmap complexity
• Demand from one noisy account, not from wedge

Exception: keep if clear unlock for wedge.

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5. When NOT to Scale Sales

Do NOT scale if:

• Can't explain how the last 5 deals happened
• Don't have ~10-25 real customers or equivalent repeatability
• Onboarding is still founder/engineer-heavy and bespoke
• Retention/health is weak
• Buyers love demos but don't achieve durable usage
• Every win depends on founder charisma or heroic customization

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6. When CEO Must Personally Handle Sales

CEO sells personally when:

• ICP, message, buyer, objections are still in discovery
• Product requires deep technical credibility
• Pricing is still being explored
• ROI proof is still being designed
• Key deals still teach the company something strategic

Even after the first sales hire — CEO stays in important/strategically revealing deals.

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7. When to Hire First Salesperson / Marketer / Product Person

First Salesperson

When: repeatability signal exists + founder is the bandwidth bottleneck + deals are understandable + retention is not broken. Prefer: player-coach / technical seller, NOT big-company VP Sales.

First Marketer

When: one narrative works + one ICP is clear + 1-2 channels show signal + the job is scaling execution, not inventing market. NOT to discover ICP or write the first real message.

First Product Person

When: founder already has deep market understanding + customer signal volume overwhelms + engineering trade-offs are rising. NOT to replace founder judgment pre-PMF.

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8. When a Pivot is Justified

Pivot when one of three proofs is structurally broken across multiple experiment cycles:

• Pain broken: nice but no urgency, budget, workaround, or owner
• Value broken: problem real but users don't reach meaningful outcomes
• Repeatability broken: some buy, but every sale/implementation/renewal is bespoke

Pivot hierarchy:

1. Change persona first (if workflow/value right but wrong user cares)
2. Change problem/promise (if capability useful but message wrong)
3. Change product/workflow (if market right but users don't get value)
4. Change category/direction (only when 1-3 exhausted)

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9. Diagnosing "Low Conversion"

Where low	Most likely problem	Inspect first
Traffic -> signup	Positioning / channel / trust	Language-market fit, source quality, proof, CTA
Signup -> activation	Product / onboarding / TTFV	Steps to first value, templates, friction
Activation -> paid	Outcome proof / buyer / pricing	Is value clear? Right buyer? Value-based pricing?
Paid -> retained	Problem frequency / workflow embed	Job important + recurring? Product in workflow?
Retained -> expansion	Narrow value / weak multi-user	Team hooks, second use case, packaging

AI-era extra: If user-level love strong but enterprise close rate weak -> inspect trust/compliance/procurement readiness.

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How to Use

When the founder describes a situation:

1. Identify which playbook is relevant
2. Apply the framework to current [YOUR_PRODUCT] data
3. Give a concrete recommendation: action + timeline + what to measure
4. Log the decision to memory/YYYY-MM-DD.md and update MEMORY.md if needed

Follow output preferences from USER.md (language, format, platform constraints).