AI native marketing | Live workshop: Company marketing brain
Build a personalized team AI system and get people to use it. Find out where it breaks and fix it.
The AI governance framework behind it: one versioned source every AI tool draws from, with permissions and a rollout plan.
- Rebuild your personal library as a team library, sized to your team and disciplines
- Set permissions so positioning and claims are not edited by accident
- Feed the brain from your competitive, customer and performance builds
- Catch silent failures, cap runaway cost, and keep customer data out of it
- Sequence a rollout and an onboarding path around workflows people already run
Replaces: Everyone’s private prompts, and the colleague who knows where the answer lives.
Workshop date: Tuesday, 3 November 2026 | 4 PM CET / 9 AM CST / 3 PM UTC | 90 minutes
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Meet your instructors:
4x’d efficiency & leads CXL’s growth, experimentation & product. Trained 25k+ marketers with 200+ courses, 4000+ blogs & playbooks.
If you are the only person who can run your AI system, that is not a system. That is a dependency.
A GitHub repository context library built for a team has to work for people who did not build it. That means shared context files, named owners, and quality rules that hold when you are not reviewing every output yourself.
In Wynter’s January 2026 panel of 100 B2B marketing leaders, 32% name bandwidth as a top pain. They are running enterprise-level programs on mid-market headcount, which is exactly when a system only one person can operate stops being an asset.
You leave with a library your team can clone, contribute to, and improve through pull requests.
📅 Tuesday, 3 November 2026 | 4 PM CET / 9 AM CST / 3 PM UTC | 90 minutes
Part 01: Scale the personal library to your team
What works for one person breaks the moment a second contributor arrives. You restructure the library for people who did not build it, and decide who can change what.
- Restructure the library so a new contributor can find and trust the right file
- Name owners per area, and set permissions so positioning and claims are not edited by accident
- Run changes through pull requests so every edit has a reason attached
- Outcome: A team-shaped library with owners, permissions and a review flow
Part 02: Keep it current with feeds from your other builds
A shared brain is accurate at launch and wrong by quarter two unless something keeps feeding it. The builds from earlier weeks are that something.
- Wire in the competitive intelligence agent, the customer intelligence pipeline and your performance data
- Hold the full context set: positioning, ICP, voice, proof, competitive, brand and performance history
- Outcome: A brain that updates itself from the systems already running
Part 03: Run it safely, on cost and on data
The dangerous failure is the confident answer nobody checked, and the second most dangerous is the invoice nobody watched. You put both under control before the team depends on it.
- Alert on silent failure, where the output looks fine and the source underneath broke
- Set cost controls so a shared brain feeding every tool does not run up an unwatched bill
- Handle PII: what customer data never enters the library, and how you enforce it
- Put human-in-loop checkpoints where an answer goes to a customer
- Outcome: Monitoring, cost limits and a documented data policy on your library
Part 04: Get the team to use it
Adoption decides whether any of this mattered. You finish with the rollout and the onboarding path, not the build.
- Sequence the rollout by the workflows people already run, not by folder
- Write the onboarding path so a new joiner is productive in the library on day one
- Pick the adoption metrics worth watching, and what to do when they flatten
- Outcome: A rollout plan you can start next week, with owners and adoption metrics
What you need before you start
- You should be comfortable with: running campaigns and reading your own performance data. No coding needed.
- You do not need: prior Claude Code, n8n or GitHub experience. Every build starts from a template.
- A paid LLM account, Claude Code preferred, plus free GitHub and Miro accounts.
- The Monday prep in the app, matched to your level by the quiz.
- Any other tool is explained live, with alternatives. You are not locked into one stack.
What marketers say after our workshops and courses
AI-Forward Marketing Executive
“I was in your workshop 12 hours ago. I already have a workflow live… I feel like a freaking WIZARD!”
Growth Marketer | MBA | Product Owner
“What a great session, and what an incredible week at CXL… what I enjoy the most is this:
Being around curious minds, leaving inspired to test, putting ideas into practice. having conversations that sharpen your thinking, asking (a lot of) questions, sorry, not sorry…
The SEO + n8n session gave me a lot to think about… honestly, I feel like a machine.”
AI/B2B Marketing Programs
“Officially CXL Certified in Redesigning Marketing Workflows for AI.
A great deep-dive into building AI into marketing the right way… rethinking the workflows from the ground up.”
PR & Marketing | MBA
“How is AI affecting the role of a marketer? I have seen this question asked a hundred times and rarely seen a credible answer. CXL ran a webinar this week that actually delivered one.
It had a bit of a cold shower effect, just data and a clear-eyed look at where things are.”
Growth Experimentation | 500+ A/B Tests
“CXL changed my life. I’m not exaggerating, it actually did…
I got so deep in the content that a year later, in a completely unexpected turn of events, I was hired by Speero. Boom. Easily a 50x ROI right there.
CXL doesn’t mess around. They prioritize quality over quantity to make a real impact on your career.”
Take this 1 session workshop on its own, or join the 6 week cohort.
It runs standalone, and as week 6 of the AI Native Marketer cohort: five working workflows across six weeks. Cohort enrollment closes before the first workshop.
Join our next AI native marketer cohort
Six weeks. Five working workflows. Starts 28 September 2026.
4PM CEST / 9AM CDT / 2PM UTC
Marketing Brain
You buildA context system on a GitHub repository: your ICP, positioning, voice and proof, wired into Claude Code and n8n via MCP, which connects AI to your tools.
It replacesPasting context into every prompt, and the generic drafts that come back when you don’t.
4PM CEST / 9AM CDT / 2PM UTC
Campaign engine with a quality gate
You buildAn automated workflow: one brief in, a full campaign out (emails, social, enablement, sequences) with sources and a brand voice check before it ships.
It replacesThe generic first draft, and the reviewer who catches what AI made up.
4PM CEST / 9AM CDT / 2PM UTC
AI visibility and AI-era measurement
You buildA share-of-model baseline, how often ChatGPT, Gemini and Perplexity name you, plus AI traffic grouped in GA4 and a citation-gap list of pages to write.
It replacesThe SEO specialist’s monthly report, which misses where buyers now shortlist.
3PM CET / 9AM CDT / 2PM UTC
Marketing insight and reporting agent
You buildAn agent that reads your ad platforms, GA4, CRM and email, then posts one weekly summary: what changed, why it matters, what to do about it.
It replacesThe weekly report you build by hand, and the analyst who explains it.
4PM CET / 9AM CST / 3PM UTC
Company Marketing Brain
You buildThe same context system customized for your team: one versioned source every AI tool draws from, with permissions and a rollout plan.
It replacesEveryone’s private prompts, and the colleague who knows where the answer lives.
Build one AI native workflow every week that you use at work.
You build a context brain your AI draws from, a campaign engine with a quality gate, an AI search visibility baseline, a weekly reporting agent, and the team version of the brain.
Here’s why marketers choose CXL
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