OpenCMO

The open-source CMO. Growth playbooks from 16 experts who actually ran the numbers — Cursor, Notion, Linear, Deel, Canva, Lovable, Grammarly, Wispr Flow — packaged as an installable skill for your AI agent.

Covers the whole growth stack: paid ads (Google · Meta · LinkedIn) · out-of-home & ABM · SEO & programmatic SEO · launches & Product Hunt · pricing & monetization · creator & influencer programs · PLG→enterprise · attribution & tracking · growth engineering with agents

The experts

Sixteen people who ran growth at companies you know, each distilled from first-hand sources — podcast transcripts, bylined essays, their own posts. Every claim carries a link back to where they said it.

Person	Background	One line to remember them by	Find them
Rex Gelb	Paid media, Cursor	Don't buy ads before PMF; after AI took over bidding, creative/tracking/landing pages are the three levers left	in
Matt Swulinski	Wispr Flow → Viktor	Ran $1M/month solo; "creative is the targeting"; caps AI-generated creative at 5%	in · X
Elena Verna	CPO, Lovable	"60–70% of traditional growth tactics don't apply anymore"; PMF is a treadmill, not a destination	in · X
Meltem Berkowitz	CGO, Deel	0→$300M in 3 years, profitably; the SEO traffic-light framework; "no successful paid ads on a 4-second site"	in · X
Yuriy Timen	Grammarly, 9 years	The oil-wells theory of channels; admits the best content doesn't always win — and why brands shouldn't chase the shortcut anyway	in · X
Karri Saarinen	CEO, Linear	$35K total marketing spend to a $1.25B valuation; the methodology is the marketing	in · X
Lena Waters	CMO, Notion	"We used to sell to humans who researched with tools. Now we sell to tools that report to humans"	in
Ben Lang	Early Notion / Cursor	Full-length creator videos over ad reads; evergreen signup flywheels	in · X
Morgane Palomares	ex-VP Marketing, Vercel	Replaced SDRs with technically-trained Product Advocates	in · X
Holly Chen	ExponentialX (ex-Slack, Google, Loom, Miro)	Channel choice follows ARR stage; PLG and sales-led converge past $20M	in · X
Phil Carter	Elemental Growth (ex-Quizlet)	80% of trials start on day zero — the first session is the whole game	in · X
Jared Liu (宗源)	Growth engineer, YouMind	Aggregation-site flywheels; "growth while you sleep" via agent automation	X
Frank	AI product, 5M users	The four-pillar system: SEM validates, SEO builds the asset, GEO rides along, social amplifies the brand	in
Austin Lau	Growth, Anthropic	Cut ad production from 30 minutes to 30 seconds by building his own tools, having never opened a terminal before	in · X
Grant Lee	CEO, Gamma	Won Product Hunt, still called it no-PMF; rebuilt the first 30 seconds and went to 20K signups/day with zero marketing	in · X
Chris Pedregal	CEO, Granola	A year in closed beta, ~150 hand-onboarded users, no built-in growth loops — it spread through VC circles anyway	in · X

Why this exists

Ask any AI assistant "should we start running ads?" and you get a balanced, reasonable, useless answer.

Ask an agent with OpenCMO installed, and you get four experts who disagree:

Expert	Position	Their precondition	Track record
Matt Swulinski (Wispr Flow)	Start immediately	Conversion tracking works + 50 conversions banked	$2M→$50M ARR in 12 months
Rex Gelb (Cursor)	Not before PMF	Week-4 retention >20%	Runs paid media at Cursor
Elena Verna (Lovable)	Year one is a death trap	Payback period under 3 months	$400M ARR in 18 months
Meltem Berkowitz (Deel)	Foundations first	Site loads <4s, findable, content to catch demand	0→$300M in 3 years, profitably

Paid ads are just the demo — every area listed at the top gets the same treatment.

Real growth knowledge looks like this: conditional, contextual, and contradictory. Average the disagreements away and you get soup.

Three rules govern everything in here:

Named people, direct quotes. No anonymous "experts say." Every claim has a person, a date, and a link.
Conflicts stay visible. When experts disagree, we build a comparison table instead of picking a winner. The disagreement is the information.
Evidence gets graded. First-hand quote, media coverage, company self-report, or third-party estimate — every number is labeled. We also debunk: the file on Jasper exists mostly to show why the "Google penalized their AI content" story doesn't survive contact with the evidence.

Install

curl -fsSL https://raw.githubusercontent.com/About-Intelligence/OpenCMO/main/install.sh | bash

Add -s -- --project to scope it to the current repo instead of your home directory. Re-run it any time to update. Prefer to see what you're running? Read the script or just git clone this repo into ~/.claude/skills/.

Then ask it real questions — "should we turn on Google Ads?", "how many Meta creatives per month at $100k?", "is a billboard worth it, and how would we attribute it?" — and it answers by citing specific people and the conditions they set, not by averaging advice into mush.

What's inside

open-cmo/
├── SKILL.md                     # entry point: expert index + scenario navigation
└── references/
    ├── experts/    16 experts          # theses, verbatim quotes, contrarian takes, conflicts
    ├── cases/       4 teardowns (10+ companies)  # PSEO canon, Canva deep-dive, OpenRouter, Jasper debunk
    ├── channels/    4 channels           # Google, Meta, LinkedIn, out-of-home
    ├── topics/      9 topics             # timing, creative, attribution, SEO, pricing, launches...
    └── guides/      4 guides             # growth 101, PLG→enterprise, meta-patterns, why experts disagree

The meta-patterns

The most useful file in the repo is deep-insights.md: eleven patterns you can only see with all the experts side by side, ending in decision tables — what works by company type, by stage, and the single variable that settles each famous expert fight. A sample of the patterns:

The Amplifier Law. Every paid channel amplifies; none of them generate. The four "when to start ads" positions above are one answer wearing four hats.
The Moat Migration Law. Content volume stopped being a moat. Proprietary data replaced it. Extractability — whether an AI can quote you — is replacing that.
The Asymmetric Loss Function Law. Your strategy space is set by your downside risk, not by what's technically possible. This is why brands can't copy spammer tactics, in SEO, on Product Hunt, or with bought GitHub stars.
Attribution Humility. Direct traffic is lagged paid spend. Self-reported attribution flatters. The goal of measurement isn't precision, it's preventing self-deception.

How this compares

	Growth books & courses	Asking a generic AI	OpenCMO
Freshness	Dated at print	Training cutoff	Updated continuously, everything timestamped
Sources	Sometimes	Untraceable	Every claim linked
Disagreements	One author's view	Averaged into mush	Preserved, with comparison tables
How you use it	You read it	You chat with it	Your agent cites it inside your actual decisions

Contributing

Found a good first-hand interview or teardown? See CONTRIBUTING.md for the evidence standards. The biggest gaps right now: enterprise B2B (CMO-level experts), consumer products, and non-US markets.

Roadmap

More experts: Bill Macaitis (ex-Slack CMO), Kipp Bodnar (HubSpot), consumer growth leads
Retention & lifecycle topic file
MCP server so agents can query the library by expert × scenario
Chinese translation

License

MIT for the repo structure and original analysis — see LICENSE.

Quotes belong to their original authors and publications. We quote briefly, for research and education, and link every source in full. If you're a rights holder and want something changed or removed, open an issue and we'll handle it quickly. Third-party traffic figures (Ahrefs, Semrush, SimilarWeb) are labeled as estimates and are not official company data.

Maintained by Soku, the agentic workspace for marketing teams. We built OpenCMO because our own agents needed it.