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CodeAlive-AICodeAlive-AI/ceo-ai-os/skills/ceo-weekly-review/SKILL.md

ceo-weekly-review

Skill9 starsChanged 6 months agoMITView on GitHub

Weekly CEO review — 10 questions, dashboard, self-deception check, next week focus

2 other projects use a version of this, 1 of them edited.

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17 rules. About 0 are common, 13 are distinctive, and 4 are 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.

  • 4

    Very specific

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

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    If compliance < 3/5 days → diagnose friction: "GTM X/5 дней.

    line 32
  2. Very specific:

    Read MEMORY.md — current wedge, stage, hypotheses, constraint

    line 40
  3. Very specific:

    Read memory/hypotheses.json — experiment status

    line 41
  4. Very specific:

    Read daily logs for this week (memory/YYYY-MM-DD.md x 7)

    line 42
  5. Distinctive:

    If PostHog is available — query key metrics for the week

    line 43
  6. Distinctive:

    Search/chat weekly active users

    line 63
  7. Distinctive:

    If we were starting the company today, would we choose the same wedge?

    line 107
  8. Distinctive:

    Only warm intros convert?

    line 113
  9. Distinctive:

    Every early customer wants a different product?

    line 116
  10. Distinctive:

    If 3+ signals fire — flag hard.

    line 124
  11. Distinctive:

    Before final recommendations — challenge your own analysis:

    line 128
  12. Distinctive:

    Consistency: do my dashboard conclusions contradict my answers to the 10 questions?

    line 130
  13. Distinctive:

    Constraint alignment: do my next-week recommendations exploit the constraint (market learning speed)?

    line 132
  14. Distinctive:

    If issues are found — fix recommendations BEFORE sending.

    line 135
  15. Very specific:

    Update MEMORY.md if any of these changed: stage, wedge, key learnings.

    line 149
  16. Distinctive:

    Don't send everything in one message.

    line 153
  17. Distinctive:

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

    line 158

≈ “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

CEO Weekly Review

Runs every Sunday evening (cron) or manually on the founder's command.

Process

Step 0: System Throughput (Critical Chain — DO THIS FIRST)

How many validated beliefs changed this week?

  • Hypotheses resolved (keep/kill/reframe): X
  • ICP assumptions updated: X
  • Decisions on pricing/positioning/message: X
  • Target: >= 1 meaningful change/week

Constraint check:

  • Read MEMORY.md -> System Constraint
  • CEO time on constraint-work (conversations, discovery, sales) vs non-constraint: X/Y hours
  • Target: >35% on constraint
  • Has the constraint shifted? If yes -> update MEMORY.md

Focus discipline (from memory/focus-state.json + memory/focus-history.jsonl):

  • GTM minimum completed: X/Y days this week
  • Waivers: N (list reasons — are they legit or avoidance?)
  • Streak: N days
  • Most common MVNA type completed (research/outreach/strategy)
  • If compliance < 3/5 days → diagnose friction: "GTM X/5 дней. Что мешало? (friction, RSD, energy, priorities)" — don't shame

WIP check:

  • Active hypotheses: X (limit: 3). Active experiments: X (limit: 2).
  • Relay race: are there hypotheses with enough evidence for a decision right now?

Step 1: Gather Data

  1. Read MEMORY.md — current wedge, stage, hypotheses, constraint
  2. Read memory/hypotheses.json — experiment status
  3. Read daily logs for this week (memory/YYYY-MM-DD.md x 7)
  4. If PostHog is available — query key metrics for the week

Step 2: CEO Weekly Dashboard (Bible Section H.1)

Build the dashboard across 9 categories. PostHog for 2,3,5,6,9. The rest — ask the founder.

Header: Current stage | Wedge | System constraint | Biggest risk this week

1. Learning (ASK the founder):

  • Qualified conversations this week (target: 8-12)
  • Repeated pain rate (same problem/trigger recurring?)
  • What changed our beliefs?

2. Product (PostHog):

  • TTFV: median timeSincePrevious for First Value Moment
  • Activation: funnel_next_stage_available -> first_value_delivered stage
  • Funnel: signup -> activated -> return -> regular -> power (compare to last week)

3. Usage (PostHog):

  • Retained active: Weekly Active milestone count
  • Search/chat weekly active users
  • Deep workflow usage: deep_workflow_started

4. Pipeline (ASK the founder):

  • New pipeline in wedge
  • Win rate trend
  • Sales cycle

5. Retention (PostHog + manual):

  • Healthy accounts: regular_usage+ stage
  • Expansion pull: team_invitation_sent events

6. B2C -> B2B (PostHog — KEY):

  • Target signups: Account Created + qualified filters
  • Active companies: unique organizationId
  • Companies with 2+ users
  • Same-company emergence rate

7. Execution (ASK the founder):

  • Experiment cycle time, belief changes this week

8. Economics (ASK the founder):

  • Burn/runway

9. PMF signals (MIX):

  • Wedge repeatability (last wins look alike?)
  • Organic pull (sharing events, inbound, referrals)

Attribution (PostHog):

  • Top sources by $initial_utm_source for activated users

Step 3: 10 Weekly Questions (Bible Section P)

Go through each question and provide a brief answer based on gathered data:

  1. What did we learn this week that actually changed our beliefs?
  2. Which segment showed the strongest pain, fastest value, and repeatability?
  3. Did I (the founder) personally talk to enough customers, buyers, and lost prospects?
  4. Which metric moved, and what decision follows from it?
  5. Is the B2C layer creating enterprise signal or just activity?
  6. Are recent wins becoming more similar or more bespoke?
  7. Is time-to-first-value decreasing?
  8. Are healthy accounts asking for more on their own?
  9. What are we calling progress because it feels good?
  10. If we were starting the company today, would we choose the same wedge?

Step 4: Self-Deception Check (Bible Section P)

Check 10 self-deception signals:

  1. Only warm intros convert?
  2. Traffic/signups grow, but target-cohort activation doesn't?
  3. Calling pilot revenue "ARR"?
  4. Every early customer wants a different product?
  5. Buyers love demos but don't use the product?
  6. Annual contracts look OK, but engagement is dead?
  7. Hiring because learning feels slow?
  8. Founder can't explain the last 5 deals?
  9. B2C grows, but doesn't create accounts or pipeline?
  10. Team is very busy, but beliefs and priorities don't change?

If 3+ signals fire — flag hard.

Step 5: Adversarial Self-Review

Before final recommendations — challenge your own analysis:

  1. Consistency: do my dashboard conclusions contradict my answers to the 10 questions?
  2. Proxy skepticism: am I assessing real progress toward PMF or convenient metrics?
  3. Constraint alignment: do my next-week recommendations exploit the constraint (market learning speed)?
  4. Inversion: what would have to happen next week for [YOUR_PRODUCT] to get WORSE? Do my bets protect against that?

If issues are found — fix recommendations BEFORE sending.

Step 6: Next Week

Formulate:

  • Top 3 bets for next week (tied to constraint)
  • Top 3 kills (what to stop — Jobs's subtraction)
  • Top 3 asks (what is needed from the founder or externally)

For each bet: reversibility (two-way / one-way door) and kill signal.

Step 7: Save

Log the result to memory/weekly/YYYY-WW.md. Update MEMORY.md if any of these changed: stage, wedge, key learnings.

Chat Output Format

Don't send everything in one message. Split into 3-4 short ones:

  1. Dashboard summary (5-7 lines)
  2. Key answers + self-deception flags (5-7 lines)
  3. Next week focus (3-5 lines)

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

Tone

Like an honest Chief of Staff: facts -> implications -> actions. Don't sugar-coat.

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