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🔒 Q&A w/ Nate is happening in 7 days
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🚀New Video: How to Never Hit Your Claude Session Limit Again
If you're hitting session limits in Claude Code, this video breaks down exactly how tokens actually work and the habits that will stop you from burning through them. I cover context rot, manual compaction, the rewind feature, sub agents, markdown conversions, and a free token dashboard I built so you can see where your tokens are really going. By the end you'll know when to clear, when to chain sessions, and why the 1 million token window is insurance, not a goal to fill. Token Dashboard 10 GitHub Repos: https://x.com/DeRonin_/status/2045420155434320270?s=20
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🚀New Video: Claude Just Destroyed Every Video Editing Tool
Video editing just changed forever. What used to take motion graphics artists and editors hours of manual work can now be done in minutes with natural language, no code required. In this video, I'm breaking down two methods: Claude Design for spinning up custom motion graphics through conversation, and Claude Code connected with Hyperframes for a more advanced workflow with serious customization, so every output matches your brand's tone and style. I'll walk through real examples, use cases, and exactly how to set everything up. Plus, I'm giving away the free skills and GitHub repo I use in this video so you can skip the setup and start creating right away. GITHUB REPO
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🏆 Community Wins Recap | Apr 11 – Apr 17
From first AI roles and paying clients to live receptionist systems and enterprise training deals - this week inside AIS+ showed what happens when execution meets consistency. 🚀 Standout Wins of the Week inside AIS+ 👉 @Griffin Maklansky went from being laid off to landing a role as an AI Workflow Builder in just 1 month. 👉 Duy Nguyen moved from fear to action, built a full AI-operated business, and already landed 2 paying clients through word-of-mouth. 👉 @Narsis Amin built a fully working AI restaurant receptionist handling bookings, availability, and CRM logging end-to-end. 👉 Michael Wacht closed a deal to deliver AI training for 200 employees, stepping into enterprise-level impact. 👉 @Dion Wang received his first official testimonial, validating real client results and around 40 hours/month saved. 🎥 Super Win Spotlight | @Debbie DeMarco Bennett Debbie joined AIS+ at a moment when AI was starting to disrupt the business she had built for 13 years. Instead of staying scared, she decided to learn how to work with the technology. Since joining, she has: • Automated multiple parts of her business and freed up major time • Built her own admin dashboard and secure internal systems • Started DeMarco Bennett AI • Landed her first client and began rebuilding their business systems Her biggest shift? From thinking “I’m not technical enough” to realizing that with the right support, iteration, and community, she could absolutely build. Debbie’s journey is proof that you do not need a tech background - you need the willingness to learn, ask questions, and keep building. 🎥 Watch Debbie’s story 👇 ✨ Want to see wins like this every week? Step inside AI Automation Society Plus and start building assets that compound 🚀
🏆 Community Wins Recap | Apr 11 – Apr 17
Why I stopped letting LLMs do math (and built a deterministic pricing layer instead)
Hey everyone, Like a lot of you, I’ve been building AI agents for local businesses and contractors. But I kept hitting the exact same wall: Pricing Hallucinations. I set up strict pricing rules, tax rules, and margin floors in the system prompt. If the user asks a simple question, it works. But the absolute second a prospect starts negotiating—"Can we remove the premium filter?" or "Can I get an off-peak discount?"—the LLM starts guessing numbers. It calculates taxes on the wrong base price, ignores mandatory fees, and invents discounts. The realization: AI generates prices based on probabilities and patterns. Pricing requires deterministic math (1+1 always equals 2). Better prompt engineering cannot fix this. So, I built a solution: Quotix. It’s a deterministic pricing engine (rules-first node architecture) that handles the math, while the AI just handles the conversation. The AI is the salesman; the engine is the calculator. They never cross over. I just recorded a deep-dive video where I show the exact prompt failures, explain why the LLM breaks, and do a walkthrough of the node canvas I built to fix it. I am building this in public and would love the feedback of the builders in this group, since you guys are actually in the trenches deploying these systems for clients. 1. The Video Breakdown (The Problem & The Architecture):https://youtu.be/mX5NLB5xSg4?si=UK-GbezuM3pCm4el 2. The Live Demo (Please keep in mind work in progress): https://thegrowthmark.com:8090/engine/823d012fde358c02fc9a7fd464dd3f4a Would love to hear your thoughts and feedback!
😔 Please Help!!! I don't know how to organize my projects.
Last week I was adding things to a project in CC - VS Code. My /context is 80k from the start. I thought it would be a good idea to have all the skills, all the repositories, everything together, and when I wanted to do a project I could just say "Claude, I want to do X, Y, and Z." What's the best way to do this with everything we have? But I think it's better to have everything separate. How do you guys do it? Thank you in advanced.
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