agentleFS
Sign inStart free
CodeAlive-AICodeAlive-AI/ceo-ai-os/skills/decision-playbook/SKILL.md

decision-playbook

Skill9 starsChanged 6 months agoMITView on GitHub

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.

1 other project uses a version of this, 1 of them edited.

Adopted by

Most recently taken up by

The file

Show its rules and text

We split this skill into the rules it gives an agent

14 rules. About 0 are common, 13 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈13

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

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

    line 9
  2. Distinctive:

    Only when all three proofs converge:

    line 15
  3. Distinctive:

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

    line 32
  4. Distinctive:

    Exception: keep if clear unlock for wedge.

    line 55
  5. Distinctive:

    Do NOT scale if:

    line 61
  6. Distinctive:

    Don't have ~10-25 real customers or equivalent repeatability

    line 63
  7. Distinctive:

    Every win depends on founder charisma or heroic customization

    line 67
  8. Distinctive:

    When: repeatability signal exists + founder is the bandwidth bottleneck + deals are understandable + retention is not broken.

    line 87
  9. Distinctive:

    Prefer: player-coach / technical seller, NOT big-company VP Sales.

    line 88
  10. Distinctive:

    When: one narrative works + one ICP is clear + 1-2 channels show signal + the job is scaling execution, not inventing market.

    line 91
  11. Distinctive:

    When: founder already has deep market understanding + customer signal volume overwhelms + engineering trade-offs are rising.

    line 95
  12. Very specific:

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

    line 125
  13. Distinctive:

    When the founder describes a situation:

    line 131
  14. Distinctive:

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

    line 137

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Decision Playbooks (CEO Bible Section I)

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

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.

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.

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.

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.

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

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.

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.

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)

9. Diagnosing "Low Conversion"

Where lowMost likely problemInspect first
Traffic -> signupPositioning / channel / trustLanguage-market fit, source quality, proof, CTA
Signup -> activationProduct / onboarding / TTFVSteps to first value, templates, friction
Activation -> paidOutcome proof / buyer / pricingIs value clear? Right buyer? Value-based pricing?
Paid -> retainedProblem frequency / workflow embedJob important + recurring? Product in workflow?
Retained -> expansionNarrow value / weak multi-userTeam hooks, second use case, packaging

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

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).

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

Check your setup, free