we unpack one of the fastest built experimentation engines i've seen!! In this episode, I sit down with Kameron Tanseli (Growth Engineering) and Rosie Hoggmascall (Growth & Product) from Fyxer.ai and we retrace the steps of building a 500+ /year experimentation program.
We go deep into:
Why their first onboarding experiments actually made things worse
The tooling shift from PostHog to GrowthBook (and why it mattered)
How decentralized ownership (no PM, no heavy process) unlocked serious speed
Why every engineer acts like a founder
How Slack transparency builds experimentation culture
Using AI agents to automate experiment reporting, analysis, and cleanup
What “time to value” really means in an AI product
The emotional side of onboarding (“inbox shock”) and how it impacts retention
How to prioritize when you’re scaling from 5 → 70+ people
We also explore:
➤ The difference between growth and product prioritization
➤ How to surface insights across support, sales, and product
➤ What’s still impossible to automate in experimentation
➤ The tracking challenges of building inside Gmail and Outlook and of other AI tools
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