ceo-weekly-review
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
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
- Read
MEMORY.md— current wedge, stage, hypotheses, constraint - Read
memory/hypotheses.json— experiment status - Read daily logs for this week (
memory/YYYY-MM-DD.mdx 7) - If an analytics tool is available — query key metrics for the week
Step 2: CEO Weekly Dashboard (Bible Section H.1)
Build the dashboard across 9 categories. Use your analytics tool for 2,3,5,6,9. The rest — ask the founder.
Header: Current stage | Wedge | System constraint | Biggest risk this week
1. Learning (ASK FOUNDER):
- Qualified conversations this week (target: 8-12)
- Repeated pain rate (same problem/trigger recurring?)
- What changed our beliefs?
2. Product (analytics):
- TTFV: median time from signup to first meaningful interaction
- Activation: progression through activation funnel stages
- Funnel: signup -> activated -> return -> regular -> power (compare to last week)
3. Usage (analytics):
- Retained active: weekly active user count
- Core feature weekly active users
- Power feature usage (e.g., multi-repo, advanced modes)
4. Pipeline (ASK FOUNDER):
- New pipeline in wedge
- Win rate trend
- Sales cycle
5. Retention (analytics + manual):
- Healthy accounts: users/orgs at regular usage stage or above
- Expansion pull: team invitation or sharing activity
6. B2C -> B2B (analytics — KEY):
- Target signups: new accounts with qualified attributes
- Active companies: unique company/org count
- Companies with 2+ users
- Same-company emergence rate
7. Execution (ASK FOUNDER):
- Experiment cycle time, belief changes this week
8. Economics (ASK FOUNDER):
- Burn/runway
9. PMF signals (MIX):
- Wedge repeatability (last wins look alike?)
- Organic pull (sharing events, inbound, referrals)
Attribution (analytics):
- Top acquisition sources for activated users
Step 3: 10 Weekly Questions (Bible Section P)
Go through each question and provide a brief answer based on gathered data:
- What did we learn this week that actually changed our beliefs?
- Which segment showed the strongest pain, fastest value, and repeatability?
- Did I personally talk to enough customers, buyers, and lost prospects?
- Which metric moved, and what decision follows from it?
- Is the B2C layer creating enterprise signal or just activity?
- Are recent wins becoming more similar or more bespoke?
- Is time-to-first-value decreasing?
- Are healthy accounts asking for more on their own?
- What are we calling progress because it feels good?
- 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:
- Only warm intros convert?
- Traffic/signups grow, but target-cohort activation doesn't?
- Calling pilot revenue "ARR"?
- Every early customer wants a different product?
- Buyers love demos but don't use the product?
- Annual contracts look OK, but engagement is dead?
- Hiring because learning feels slow?
- Founder can't explain the last 5 deals?
- B2C grows, but doesn't create accounts or pipeline?
- 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:
- Consistency: do my dashboard conclusions contradict my answers to the 10 questions?
- Proxy skepticism: am I assessing real progress toward PMF or convenient metrics?
- Constraint alignment: do my next-week recommendations exploit the constraint (market learning speed)?
- Inversion: what would have to happen next week for the company 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.
Output Format
Don't send everything in one message. Split into 3-4 short ones:
- Dashboard summary (5-7 lines)
- Key answers + self-deception flags (5-7 lines)
- 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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