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🔒 Q&A w/ Nate is happening in 4 days
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🚀New Video: Turn Any Website Into LLM Ready Data INSTANTLY
In this tutorial, I show you how to turn any website into LLM-ready data in seconds using Firecrawl and Claude Code. We cover everything from scraping content and extracting branding information to mapping entire sites and pulling structured data. I walk through setting up the Firecrawl MCP server in Claude Code, then demonstrate real use cases including scraping 200 job listings from a remote job board and extracting branding details from landing pages. The best part is you don't need to think about configuration or which API endpoints to use. Just tell Claude Code what you want and it figures out the rest. FIRECRAWL DISCOUNT
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For beginners who don't know where to start
Most AI tutorials are made by developers, for developers. They skip steps. They throw around jargon. They assume you already know things you don't. You watch video after video and somehow end up more confused than when you started. That's not a you problem. That's a teaching problem. I made something that fixes it: -> For beginners who don't know where to start PS: If you’re already an AIS+ member, we will be rolling this out to you for free shortly. No need to buy it.
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🏆 Weekly Wins Recap | Jan 31 – Feb 6
This week inside AIS+ was packed with real traction. First clients landed, outreach fears broken, systems shipped, and builders stepping into confidence instead of overthinking. Here are a few standout wins inside AIS+ 👇 👉 @Ahmed Bin Faisal signed his first client via Upwork just one month after joining - full automation delivered and a very happy client. 👉 @Joe Scott scaled from £1K workflow builds to £30K AI agent projects by selling outcomes, not tools. 👉 @Deniz G built his own internal business app using n8n, Claude, and Supabase - CRM, inbox sync, lead scoring, and AI assistant all live. 👉 @Anthony Rako left his dev job, bet on himself, and landed a €2,380 real estate automation contract. 👉 @Nick Stadler cold-called 10 businesses and booked his first discovery call - outreach muscle officially activated. 🎥 Super Win Spotlight: @Gerard Vazquez | First Client Through Action Gerard joined AIS+ looking for clarity, real support, and a place to actually build.Instead of waiting, he reached out to people he already knew, booked multiple calls and closed his first consulting client at €1,500. With help from the community, he solved issues faster, delivered confidently, and proved to himself that action beats endless research. 🎥 Watch Gerard share his story 👇 Gerard’s journey shows that you don’t need everything figured out - you just need to start the conversation and keep moving. ✨ Want to see wins like this every single week? Join AI Automation Society Plus and turn learning into real outreach, real clients, and real momentum 🚀
🏆 Weekly Wins Recap | Jan 31 – Feb 6
A Question About Standards
In AI automation, it’s easy to build something that works. It’s harder to build something that’s truly reliable, clean, and scalable. Most workflows run. Few are built to last. As this space grows, I think the real separator won’t be who can build, but who builds with long-term standards in mind. Curious to hear your take: - When you build an automation, what defines “high quality” to you?
Google just handed us a Senior Engineer (Gemini 3 Deep Think Analysis)
Google DeepMind just released Gemini 3 Deep Think today, and the numbers are honestly a bit scary. We are looking at a Codeforces Elo of 3455 and gold medals across Math and Physics Olympiads. But here is the thing. If we just use this to generate code or write emails, we are missing the point. The benchmarks show this model is optimized for deep reasoning and rigor, not just fluent chat. Think of it this way. Most AI models are like enthusiastic junior writers who want to please you. This new model is built to be a grumpy senior reviewer who wants to find your mistakes. The best use case I have found so far isn't generating answers from scratch. It is reducing risk. 1. Give it your messy, unpolished ideas. 2. Ask it to find the logic flaws. 3. If it agrees with you too quickly, force it to argue the opposite side. It is designed to handle long-horizon reasoning under uncertainty. So instead of asking "Is this good?", ask "How does this fail?". That is where the real value is for us builders. I also wrote a breakdown of this on LinkedIn if you want to share this update with your network. Link is in the comments.
Google just handed us a Senior Engineer (Gemini 3 Deep Think Analysis)
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