RAI Prep
Prepare for the GARP Risk and AI certificate with practice exams and detailed explanations.
About
RAI Prep provides practice exams and study tools designed for professionals preparing for the GARP Risk and AI certificate. The platform offers multiple-choice practice questions, timed exams, and a dashboard that tracks pacing and topic-level accuracy to help candidates focus on weaker areas.
The service is built specifically for risk professionals and candidates studying AI governance, machine learning risk, and model risk management. It covers the five official GARP RAI syllabus domains, ranging from fundamentals of machine learning to SR 11-7 compliance and production AI deployment.
What sets RAI Prep apart is its focus on deep-dive explanations that reference core concepts like algorithmic bias and model interpretability rather than simple memorization. It offers flexible, one-time payment access options without recurring subscriptions.
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FounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
this specificity then leads to more noticeable outcomes which in turn strengthen the bond between you as the person that founded the community the person you helped and everyone else in the community who gets to see it micr communities like this prioritize depth over breadth which leads to a more meaningful exchange
Specificity → visible outcomes → stronger bonds → retention
The retention engine of a paid micro-community isn't "more content" — it's visible wins by members. When every win is on-thesis (someone shipped, someone made their first dollar, someone hit the next stair-step), other members see themselves in it and the trust compounds. Design rituals that surface those wins publicly inside the community: weekly progress threads, win channels, founder shoutouts. Visibility of progress IS the retention mechanic.
in the beginning we didn't monetize at all... people started to ask to work with their team and then we needed to provide a more complex real-time collaboration... monetization should not be a guess and should be response to your behavior
Watch usage patterns to find the feature actually worth charging for
Jonathan resisted guessing at a pricing model and instead watched how users' behavior evolved over time. When team collaboration naturally emerged as the workflow bottleneck, real-time multi-user editing became the paid tier. Pricing landed on something users already wanted enough to request, making the upgrade feel obvious rather than forced.
There's a play for whatever you're stuck on.
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