In September 2024 I started an AI automation agency. Nine months later I was doing $100K/month in recurring revenue. Then I sold my share to my partners. I took everything I learned: - The client acquisition system - The pricing - The delivery process … and I turned it into a step-by-step playbook for building a one-person AI agency. No code. No team. No guesswork. See exactly what's inside: -> I sold my AI agency. here's the playbook PS: If you are an AIS+ member, this is included in the Scale module. No need to purchase separately. - Nate

Huge congrats to @Antra Verma for being the first to cross the finish line 👏 To celebrate, we're hooking her up with a FREE AIS shirt, and her official completion certificate is attached below 🏆 Let's give her a massive round of applause in the comments, she set the bar! Can't wait to see more of you submit your projects and join the graduate club. 👉 Want to take on the challenge? Head to the Classroom section or jump in HERE 👕 And if you want to grab some AIS merch for yourself, check it out HERE Cheers everyone! - Nate

When you connect Playwright CLI to Claude Code, you can automate almost anything in a browser. This video walks through 3 use cases: having Claude Code QA a web app and fix its own bugs, scraping contact info from search results, and automating actions inside logged-in sessions like Skool. I also show how I'm chaining these scripts into scheduled tasks so an agent runs them on its own.

It was a Tuesday morning. I was scrolling through our monitoring dashboard—the usual routine, checking if anything had exploded overnight. Everything looked fine. Accuracy was at 94%, right where it should be. The model had been live for 6 months. Stable. Predictable. But something in my gut said, "Wait, this is too quiet." So I did something I don't usually do at 7 AM. I pulled the data deeper. I looked past the accuracy number. What I found: our model was making decisions with absolute confidence on cases where it had no business being confident. The data it was trained on came from 2024. It was now mid-2026. The world had changed, but the model hadn't noticed. For a fintech company using this, that translated to about £50K per week being misclassified. Silent losses. You'd never see it in the accuracy metric. Here's what kills me about this: That company could have gone 2–3 more months without knowing. Accuracy would stay at 94%. Everything looks good. And by the time they figure it out? They've lost £400K. Maybe more. We caught it in week 3 because we built something different. We weren't just watching accuracy. We were watching uncertainty. The model's confidence was dropping while accuracy stayed flat. That's the mismatch nobody talks about. That's the signal. Here's what we learned—three principles that actually work: 1. Uncertainty matters more than accuracy. Your model can have 97% accuracy and be completely unreliable for decision-making. These are different questions. Most tools only measure one. 2. Disagreement is data. We ran an ensemble of models. When they disagreed on predictions—especially when they disagreed while the primary model expressed high confidence—that's where the real problems hide. 12% ensemble disagreement for us meant an 87% probability of actual drift in the data. 3. Calibration is non-negotiable. Don't use someone else's thresholds. Calibrate your system to YOUR data, YOUR tolerance for error, and YOUR business risk. This is what separates companies that just have AI from companies that trust their AI.

Been having a few conversations lately and noticed something… A lot of people aren’t really stuck because they lack ideas it’s usually something small in the process that slows everything down. Could be: • Not getting clients • Low conversions • Not knowing what to improve next • Or just things not “clicking” yet So I’m curious What’s the biggest issue you’re facing in your business right now?? No pitch here, just want to understand what people are dealing with.