AI native marketing | On-demand course: Build your AEO research pipeline
Build the system that tracks what’s shifting in SEO and AEO/GEO.
Set up a validation framework for AEO tactics, three agents that apply it, and a PXL-scored experiment backlog ready to run.
- Build a validation framework for AEO and AI search tactics specifically
- Monitor the authors and sources tracking what works in organic AI search
- Validate any AEO tactic against your framework before it enters your log
- Cross-reference logged tactics and surface patterns strong enough to test
- Score identified patterns using PXL to build a ranked experiment backlog
This course is available within our on-demand subscription plan.
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Meet your instructors:
4x’d efficiency & leads CXL’s growth, experimentation & product. Trained 25k+ marketers with 80+ courses, 4000+ blogs & playbooks.
SEO and AEO advice is everywhere. Almost none of it is validated. The gap is a framework that tells you which tactics are worth your time before you act.
AI search is not stable enough to rely on last quarter’s playbook. What earns citations in AI Overviews changes. What Google surfaces in SGE shifts. Teams optimising against yesterday’s signals are not just behind. They are building in the wrong direction entirely.
The problem is not a shortage of takes on what to do. It is that most of them are unverified opinion dressed up as practitioner insight. Separating the two requires a consistent method for evaluating source authority and evidence quality, applied before anything makes it into your strategy.
Part 01: What a research system looks like when it works
Before you build anything, you see the full architecture. Five components, how they connect, and what the outputs look like at each stage. Most research systems fail at the same point: tactics get collected but never validated, or validated but never cross-referenced into patterns.
- The five components of a research-to-action pipeline
- Where most research systems break down and why
- Outcome: A clear picture of what you are building before you write a line of code
Part 02: Build your validation framework
This is the most important artifact in the system. Everything else evaluates against it. You define what makes a tactic worth acting on: source authority, evidence quality, sample relevance, recency, and applicability to your context.
- What makes a tactic credible versus noise
- How to write scoring criteria tight enough for an agent to apply consistently
- Outcome: A validation framework saved as a markdown file, ready to use in every subsequent step
Part 03: Build the author monitoring agent
You build an agent that checks your list of trusted authors daily, surfaces new content, and proposes new authors to evaluate. The agent applies your validation framework to assess whether a proposed author meets your criteria before surfacing the recommendation.
- How to define and maintain a list of trusted sources
- How to structure the daily output so it takes under two minutes to review
- Outcome: A working author check skill file and a Slack-formatted daily output
Part 04: Build the tactic extraction and validation agent
You build an agent that takes any piece of content, extracts discrete tactics, and validates each one against your framework. Validated tactics get a structured card: one-sentence summary, source quote, validation score per criterion, and confidence level.
- How to extract tactics from dense content without losing nuance
- How to structure validation output so you can accept or reject in seconds
- Outcome: A working tactic extraction skill file you can run on any content you paste in
Part 05: Build the experiment prioritization system
Validated tactics get logged and cross-referenced against everything already collected. Patterns that appear across multiple credible sources get scored using the PXL framework: traffic potential, signal confidence, implementation ease, and speed to data. The output is a ranked experiment backlog, not a list of observations.
- How to cross-reference tactics and identify patterns strong enough to test
- How to score AEO and SEO patterns using PXL to prioritize by impact and ease
- Outcome: A ranked experiment backlog of AEO and SEO tests scored and ready to run
What do you need to make the most of the course?
- A free Miro account
- A free GitHub account
- Pro account on Claude preferable (alternatively: Codex)
- CXL will provide access to any additional tools needed for the session
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.
This is what marketers said after our live 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.”
Here is what other marketers said
Need some more convincing?
Listen to this agency owner explain why he trains his team at CXL
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