You can watch the full session here: https://www.skool.com/ai-systems-for-coaches/classroom/eee4e47c?md=c88638af119c4aac8a36addacabfbcdc

Thanks everyone for joining the event yesterday, I had a great time with you all! (For the ones that were not present, a recording of the full event will be published here next week) As promised here you can find the slides of the presentation: https://gamma.app/docs/AI-Masterclass-jqq20omdfexrixg Inside you’ll find the Gifts 🎁: - Personal Brand Builder GPT - System Audit GPT - and in this community you can post and tag me to get a custom mini audit on a specific problem you’d like to automate in your business. To your success, Ruben

I don’t usually share "small" tests. But this one matters. I recently deployed an outbound AI voice agent inside my own business and ran it on a reactivation list we hadn’t touched in months (some leads were years old). Results in 15 days: • 11,423 outbound dials • 2,825 unique leads contacted • 542 real conversations • 22 qualified appointments booked • 2 deals closed • $6,800 in real revenue • $457 in AI costs → 14.9x ROI No ads. No new leads. No extra human appointment setters. This wasn’t a demo environment. This wasn’t simulated data. This was money collected from real clients. Why this is bigger than it looks: AI was a major part of this. Voice quality, timing, persistence, and context handling are finally good enough to make outbound voice work and they’re improving fast. But this only worked because the system was already proven. • The sales script converted with humans • The offer was validated • The qualification logic was clear AI didn’t guess. It didn’t fix a broken funnel. It didn’t magically improve conversion. It removed the human bottleneck and scaled a process that already worked. Human setters stopped doing soul-crushing volume dialing. They only followed up with people who had already shown intent. AI handled repetition. Humans handled the conversations that mattered. Why I tested this myself first: A lot of AI agencies can show outbound voice demos. Very few can show revenue from it. That’s why I tested this inside my own operation first, where I already had years of sales experience and a proven process to plug AI into. I recorded: • the full metrics breakdown • the actual call recording that led to a close If anyone wants to see how it actually worked end-to-end: 👉 https://beavermind.ai/ If you have a high-ticket sales team, or you know someone who does, and want to sanity-check whether this approach fits their setup, feel free to comment here or DM me. Happy to answer questions.

Most creators think “AI marketing” means prompts and templates. This case study shows the real play. AI did the heavy lifting on analysis. We made the judgment calls that drive revenue. Result: $85,532 from a single webinar cycle. For context, we promoted a trading add-on that acts like a map for decisions. AI mined the replay and live chat, pulled the lines that hit a nerve, clustered questions, and gave us the clean angles. We wrote the final 10 percent and shipped fast. What you’ll find inside the resource: - The 5-module email engine that works in any niche - The 30-minute replay mining checklist with a copy-ready prompt - A simple segmentation plan that you will actually use - Subject line rules that raise clicks, not just opens - Objection emails and a clean 3-email close - Benchmarks so you know if you are on track Why this works: AI extracts patterns from long content in minutes. Humans add tone, proof, and pressure control. That mix turns a replay into a revenue asset without a big team. Grab the playbook here: https://docs.google.com/document/d/17-s_9PvMMEd_ErW0_Z-Ibj3nqyWcFBWLmVoElH4GDkk/edit?tab=t.0 P.S. Let me know in the comments if you want to watch the replay of the webinar, and I'll send to you via DM. To your success, Ruben

If you’re running a coaching or consulting business and feel like your sales team could be closing more, this one will hit home. I used to spend hours each week reviewing sales calls manually — giving feedback, checking script adherence, coaching reps… it worked, but it wasn’t scalable. So I built an AI Sales Manager that automates all of that. Now every call is recorded, analyzed, and scored automatically — freeing up time, improving consistency, and boosting performance across the team. This system took our close rate from 19% to 42% without hiring anyone new. 🎯 In this video, you’ll learn: - Why most teams struggle with inconsistent coaching (and how to fix it) - How to automate call reviews using GoHighLevel + GPT - The exact workflow connecting Sybill.ai → Zapier → GoHighLevel → Slack - How AI identifies weak spots in your reps’ performance instantly - How to make your team’s close rate predictable and scalable 📹 Watch the full video here: 👉 https://www.youtube.com/watch?v=OXIF45DNZQU 📘 Get the free resource (framework + plug-and-play prompt): 👉 https://docs.google.com/document/d/1HIc0d-W4xfM5Z-8TLFnJN5SVsh5eEHjmESgwIes3Lxc/edit?tab=t.0#heading=h.2ujdwohz0wtp