AI native marketing | Live workshop: Workflow redesign: Validate experiment ideas with competitive intelligence
AI made building faster.
Redesign your workflow so testing keeps up.
Build the validation layer that filters weak test ideas before you build them, using evidence instead of gut feel.
- Score three to four of your ideas in minutes using tools like DoWhatWorks
- Let AI flag which competitor tests are worth copying, and which are traps
- Rank your roadmap instantly with an automated prioritization map
- Leave with a testing protocol built for speed: run length, winner criteria, a learnings repository
Workshop date: Wednesday, 26 August 2026 | 11 AM CT / 4 PM UTC | 1.5 hours
Trusted by marketers at
Meet your instructors:
Casey Hill
Head of growth @ Bonjoro
Drives 30–40% of DoWhatWorks’ enterprise wins via LinkedIn, doubled Bonjoro trials, and built a podcast program tied to $250K+ ARR.
Building cycles move faster than ever: the bottleneck is knowing which ideas are worth building.
Most testing programs run on gut feel. An idea sounds good in a meeting, someone builds it, and three weeks later the data says it never had a shot.
This workshop gives you a validation layer. Trusted sources instead of generic LLM output, simulated test data from DoWhatWorks, and your own first-party research triangulated before you build anything.
You leave with a prioritization map for your current test ideas, a read on which competitor tests are worth learning from, and a protocol for running and qualifying future tests.
📅 Wednesday, 26 August 2026 | 11 AM CT / 4 PM UTC | 1.5 hours
Part 01: Ground AI research in sources you can trust
You start by building the validation layer itself: how to restrict AI research to trusted, vetted sources, how simulated test data from tools like DoWhatWorks gives you a confidence read before you build anything, and why your own first-party data should ground every hypothesis.
- How to restrict any LLM to trusted, vetted sources only
- How simulated test data gives you a confidence read before you build
- Outcome: A validation layer you can run any test idea through
Part 02: Stress test your own test ideas
You bring a problem you are currently working on, run it through the validation layer, and leave the session with 3 to 4 test ideas scored and ranked, not just brainstormed.
- Review meaningful test examples from Fin, MongoDB, Kit, and Sage
- Select and refine 3 to 4 test ideas from your own current problem
- Outcome: A prioritization map ranking your own test ideas
Part 03: Turn competitor data into testing ideas
You learn why copying a competitor’s current page is often copying their losing variant, and how to read competitive intelligence for what to learn from instead of what to imitate.
- Why blind competitor copying can mean copying a losing test
- How to score your own competitors’ pages for testable ideas
- Outcome: A list of validated ideas pulled from competitor intelligence
Part 04: Fold the validation layer into your CRO program
You compare a CRO program that runs without a validation layer against one that has it built in, then integrate the layer into your own prioritization, research, and testing process. You leave with a GitHub repo of Claude Code skills that has this methodology baked in and ready to run.
- See a CRO program with and without the validation layer, side by side
- Integrate the validation layer into your own prioritization and research process
- Outcome: A GitHub repo of Claude Code skills with the validation layer methodology built in
What you need to make the most of the workshop?
- A free Miro account
- A free GitHub account
- A Pro account on Claude preferable (alternatively: Codex)
- CXL will provide access to any additional tools needed for the session
THIS TRAINING IS PART OF THE AI NATIVE MARKETER SUBSCRIPTION:
Become the AI native marketer who ships the work of three.
Every two weeks, CXL helps you build one AI native workflow you can actually use at work. You only prep what matches your level, then build live with a top 1% operator.
AI ASSISTED
AI makes you faster at tasks you already did. The work itself has not changed.
You can tell because: you use AI for drafts and research, then hand off exactly as before.
AI INTEGRATED
You have rebuilt whole workflows around AI and ship work that used to need a specialist.
You can tell because: you no longer wait on a designer, a writer, or an analyst for your core work.
AI NATIVE
You build systems other people run and cover scope that used to take two or three people.
You can tell because: your team runs on workflows you designed.
There are 3 types of marketers. Which one are you?
Learning AI is a second job for most marketers. Join this program. 2hrs per week. CXL does the heavy lifting.
Without this program
Wiith this program
*Inspired by Kieran Flanagan’s U-curve of AI productivity chart.
Build one shipped AI native workflow every two weeks. Without having to figure it out alone.
Here’s why marketers choose CXL
Need some more convincing?
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