How Fyxer.ai ran 512 Experiments in a year by using AI
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How Fyxer.ai ran 512 Experiments in a year by using AI
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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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