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🔒 Q&A w/ Nate is happening in 7 hours
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🚀New Video: I Made Codex and Claude Code Build the Same App. One Clearly Won.
I gave Claude Code and Codex the exact same prompt to build a production-ready Typeform alternative, then compared the products, costs, speed, agent usage, and testing. Claude Code built the more usable app in a fraction of the time, while Codex went much deeper on architecture and reliability. This experiment made it much clearer where each tool fits in my workflow and why the way you prompt them matters.
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🏆 Weekly Wins Recap | August 8 – August 14
From $10K builds and monthly retainers to first discovery calls, first agents, and warm outreach turning into real opportunities - this week inside AIS+ showed that sometimes the best clients are closer than you think. 🚀 Standout Wins of the Week inside AIS+ 👉 @Mike Thomson signed his first monthly retainer with zero cold outreach - a local restaurant found him through Google and closed at $10K upfront + $3K/month. 👉 @Leon Seguin-denis officially launched his agency by signing his first client for €5.5K setup + €290/month recurring revenue. 👉 @Ameeth B. signed a $3.5K + MRR client and shipped a BI dashboard that automatically consolidates data from 7 Smartsheets every morning. 👉 @Dean Henry reached out warmly to just 2 people about AI automation and both agreed to let him build for their businesses. 👉 @Ryan S. Howard held his first discovery call with a large church ministry and uncovered 4 potential workflows, including one that could save a leader 6-10 hours every week. ⸻ 🎥 Super Win Spotlight | @Karen Widas Karen joined AIS+ expecting useful training. What surprised her most was the community. Someone inside AIS+ helped audit her website, which eventually gave her the confidence to rebuild the entire thing herself using Claude Code - and later build a custom solution for one of her customers. For someone who normally considers herself a “lurker,” she also found herself comfortably posting, asking questions, and helping others. Her biggest takeaway? The right community doesn’t just teach you. It gives you the confidence to build things you didn’t think you could build before. 🎥 Watch Karen’s story 👇 ✨ Sometimes the next opportunity doesn’t come from reaching more people - it comes from becoming more useful to the people already around you.
🏆 Weekly Wins Recap | August 8 – August 14
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What do you get if you upgrade to AIS+?
Some of you have never heard of the AIS+ community. Others have but the part that trips you up is the actual difference between the two. Either way, this post will give you clarity. This free group is a bundle of quick resources pulled from my YouTube videos, plus a massive open community that anyone can join. It's a great place to get your bearings and see what's possible. But it's open to everyone, it can be noisy and overwhelming, and there's no path through it. You can get help from other members, but I rarely answer questions here. AIS+ is the opposite: - A step by step roadmap with a clear order, so you're never guessing what to do next - A much smaller community of people who are seriously committed to building and selling AI agents - I answer questions every day and run a weekly Q&A call where you can get direct access to me For the course material: The roadmap takes you from zero to building and selling AI agents, and the whole thing is built on the latest tech like Claude Code and Codex. We update it constantly. The old n8n material has been archived. It's still there if you want it, but it's no longer the focus, because the way you build today has moved on and the courses moved with it. Here's the actual roadmap inside, in order, with when each piece opens up: 1. Start Here (opens the moment you join). Gets you oriented. How the community works, the path ahead, and how to get help when you need it. 2. Build Your Portfolio (opens the moment you join). Why a portfolio matters, beginner level tutorials, and what types of projects to focus on. You end up with real work you can show a client. 3. Claude Code (opens the moment you join). This is now its own dedicated course. Build faster, turn ideas into working automations, and go deep on the tool serious builders are using right now. This takes you from beginner to advanced, step-by-step. 4. Get Your First Clients (opens after 30 days). Getting your first clients is hard, because you don’t have any case studies yet. So, we analyzed all of the success stories from our members and found they get their initial clients with two different techniques: warm outreach and Upwork. So, we teach both techniques in detail with exactly what to say, exactly how to position yourself when you have no proof.
day 5 build
- Your live URL - https://gym-website-eta-seven.vercel.app/ - #AISChallenge - - One hack I used: I utilized a screenshot loop and Claude Code to save significant time while building. Since I didn't have a full screenshot of the before gym's original website, I used fragmented screenshots, and Claude Code helped me clean them up and integrate them into the new version I developed. - - I’m now planning to show this to the gym manager, whom I already know little bit because i go there. Does anyone have a good script or advice on how to start that conversation to see if they’d be interested in a website installation ? #AISChallenge
Should AI Remember Or Just Know Where to Look?
We keep making AI memory BIGGER, More EMBEDDINGS, More VECTOR databases, More COVERSATION history, More “LONG-TERM memory.” But here's a question I've been wrestling with: Does an agent actually need to remember everything? Or does it just need to know WHERE the answer LIVES, and when to retrieve it? Think about how we build reliable systems. You don't keep the entire database inside RAM. You don't copy the entire knowledge base into every process. You keep the right working state close, AND retrieve the rest when needed. Maybe AI memory should work the same way. 🧠 Working memory -> what the agent needs right now 🗄️Long-term memory -> durable facts, preferences, history 📚External knowledge -> information that can be retrieved on demand 🧹Archive -> useful context that shouldn't influence every decision The interesting architectural shift is this: Memory may become less about storage, AND more about retrieval policy. Because an agent that remembers 10,000 things but retrieves the wrong 10, isn't intelligent. It's just a very confident filing cabinet. And this gets even more interesting when memory becomes time-sensitive. A fact can be: ✅ relevant ⚠️ outdated 🔄 superseded ❓ uncertain 📦 archived 🚫 no longer applicable So perhaps every memory needs more than an embedding. It needs metadata, provenance, confidence, freshness, scope, and retrieval rules. Then the agent doesn't ask: “What do I remember?” It asks: “What do I need to know right now, and where is the most trustworthy place to get it?” 💡Maybe the next generation of AI won't have bigger memories. It will have better memory architecture. And perhaps the smartest agent isn't the one that remembers the most, BUT It's the one that knows what NOT to keep in its head. Curious: Would you rather have an AI that remembers everything, or one that can reliably find anything it needs when the moment arrives?
Should AI Remember Or Just Know Where to Look?
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