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2d •
🚀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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3d •
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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1h •
🏆 Weekly Wins Recap | Feb 7 – Feb 13
Big contracts, First clients, Real cost savings.This week inside AIS+ was about execution over excuses. Here are a few standout wins inside AIS+ 👇 👉 @Glenn Marcus closed a $60K Agentic Engineering contract in 72 hours after launching his new agency site. 👉 Ai Stromae built an automation saving a client €30K per year - €1K paid upfront with referrals coming. 👉 @Mike Thomson landed his first real paying client through persistence and smart follow-ups. 👉 @Jeremy Aune closed his first AI voice assistant client - with expansion already in discussion. 👉 @Meir Heimowitz cut $1,400/month in business costs using Claude Code automations. 🎥 Super Win Spotlight: @Glenn Marcus | $60K in 3 Days Glenn launched his new agency site on Thursday. A friend forwarded it to a CEO. By Tuesday, a $60,000 contract was signed. But this didn’t happen overnight. Through AIS+, Glenn sharpened his thinking around real use cases, agentic systems, and applying AI to actual business problems - not just tools. That clarity gave him the confidence to pivot his consulting company into an Agentic Engineering firm. The result? Right message. Right positioning. Right timing. $60K in 72 hours. His story is proof that when preparation meets opportunity, things move fast. If you’re AI-curious or already building, this is what momentum looks like. 🎥 Watch Glenn share his story 👇 ✨ 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 🚀
5d •
Built an AI Email Agent with n8n 🚀
I just built an AI email agent that writes customized emails and sends them to customers whenever a new product arrives. The project is made up of three workflows: 1) Customer Data Workflow This workflow stores customers’ names and email addresses in a database. I used Pinecone Vector Store to store the customer data. 2) Email Sending Workflow This workflow connects Gmail and gives it permission to send emails automatically. 3) AI Agent WorkflowThis workflow builds the AI agent and connects it to both the database and the email workflow using a webhook.When I message the agent to send an email (to one person or all customers), it: - Pulls names and email addresses from the database - Generates a personalized email - Sends it automatically through Gmail This is very useful for e-commerce, especially for notifying customers about new product arrivals or promotions. Big milestone in my AI automation journey — more to come 💪🔥
3d •
Automation failure reasons
Automation Doesn’t Fail Because of Tools It Fails Because of These Things Most broken automations weren’t built wrong technically. They were built wrong conceptually. Here’s what actually matters. 1. Ownership must be clear Every automation needs an owner. Not “the system”. Not “the tool”. A real person who is responsible when it: misfires sends the wrong message misses a lead If no one owns the automation, no one improves it. 2. Timing is more important than speed Fast automation is useless if it’s badly timed. Following up too early feels pushy. Following up too late feels careless. Good automation respects: business hours response gaps user behavior Timing creates trust. Speed does not. 3. Exceptions are the real workload Automation handles the average case easily. The value is in handling: incomplete data unexpected replies edge cases If your system breaks on exceptions, you haven’t automated — you’ve postponed work. 4. Feedback loops are essential Automation without feedback never improves. Your system should learn from: replies failures manual corrections Even simple feedback (tags, notes, outcomes) can dramatically improve future decisions. :--> Questions:+ 1. More points to add ? 2. More points to improve? 3. Which point is mostly happens?
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