AI native marketing | Live workshop: Workflow redesign: Pre-test experimentation ideas
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
Expert: Casey Hill, hosted by CXL’s Hesh Fekry
Casey drives 30–40% of DoWhatWorks’ enterprise wins via LinkedIn, doubled Bonjoro trials, and built a podcast program tied to $250K+ ARR.
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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?
- Paid or Pro account on Claude, ChatGPT, or Gemini
- CXL will provide access to any additional tools needed for the session
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.
What to expect:
THIS TRAINING IS PART OF THE AI NATIVE MARKETER PROGRAM:
Become the marketer who can ship the work of three.
You do not need more AI tips. You need shipped AI-native workflows in just 2 hours/week.
After one session you will have shipped one new AI workflow you need on the job.
Every session after, your output and efficiency compounds.
Ship working AI workflows you need on the job:
2hrs /week
1. Find your current AI level
2. Ship AI ready workflows
3. CXL does the heavy lifting, you join the program.
Close the gap between the AI skills you have and the ones your job now requires.
Which level are you?
You might be…
AI ASSISTED
You use AI for tasks like drafts and research. Your workflows and who you hand work to haven’t changed.
Or…
AI INTEGRATED
You’ve rebuilt workflows from scratch and ship work that used to need a specialist. You’re beyond a collection of prompts.
your target iS…
AI NATIVE
You design systems others run and cover scope that used to take two or three people.
After one session you will have shipped one new workflow you need on your job. Every session after, your output and efficiency compounds.
Here’s why marketers choose CXL
Need some more convincing?
Listen to this agency owner explain why he trains his team at CXL