So I'm sure you guys have heard the term "AI slop", and everyone sorta defines it differently. Maybe you think it's those TikToks of AI-generated fruits going on dates. Maybe it's infographics with misspelled words. Maybe it's something else entirely. But I want to talk about it in the context of communication. Internal, external, content you put out into the world. I write my LinkedIn posts with AI. My agent knows my business, how I write, how I speak. That's just how I work now. And there's nothing wrong with that. I think everyone should be using AI to write if it makes them more efficient. But this isn't a binary yes or no. It's a spectrum. Sometimes AI can draft and send automatically. Most of the time, I want it to just draft. Then I review. If someone sends me an email with em dashes everywhere, I don't actually care at all that they used AI. The fact that I can clearly tell it's AI-generated isn't the problem. What I do start asking is: → Did they proofread this? → Is this completely accurate? And subconsciously, I might start losing trust. Not just in the email but in the person who sent it. Our job here has changed from writer to reviewer. This quote has really stuck with me: "You can outsource your thinking, but you can never outsource your understanding." When your name is attached to the content, you take credit if it lands, as you should. But that also means you need to take accountability if it's incorrect. Taste and reviewing are becoming more important than ever. AI is super intelligent and powerful, but I don't want to see a world where we trust AI so much, that we stop reviewing things, and then the human on the other end of the content starts losing trust in us. That's why even though I write with AI, and people know that, I still try my best to disguise it and make it sound as "Nate" as possible. Check out the LinkedIn post I just wrote about this HERE

My name is Michael, and I’m here to better understand the wave of new technologies reshaping our world. I’m especially interested in learning how to thoughtfully integrate these innovations into my everyday life and routines.

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 💪🔥

Built a 47-node workflow masterpiece. Client called it "too complicated" and went back to manual. I'm sharing this embarrassment because I see others making the same mistake. THE CLIENT REQUEST: "We need to extract key terms from contracts" WHAT MY EGO BUILT: A 47-node n8n workflow with: - AI classification (12 contract types) - Language detection (supported 8 languages) - Parallel processing queues - Smart routing based on contract complexity - Error recovery with 3 retry strategies - Redis caching for "performance" - Beautiful Grafana dashboard - Webhook notifications for everything - 15 different extraction templates - Machine learning confidence scores Time invested: 2 weeks My pride level: 11/10 Client training needed: 3 hours Documentation: 47 pages FIRST WEEK RESULTS: - Documents processed: 12 - Errors: 7 - Client confusion: Maximum - Support tickets from client: 23 Their feedback: "This is more work than doing it manually." WHAT THEY ACTUALLY NEEDED: 3 nodes: 1. Watch Dropbox folder 2. Extract: Party names, dates, amounts 3. Add row to Google Sheets Rebuilt in 30 minutes. SINCE THE REBUILD (4 months): - Documents processed: 5,247 - Errors: 3 - Client questions: 0 - They've referred 2 other law firms The ego check: My complex solution was about impressing myself. Their simple need was about getting home by 6 PM. My new rule: If I can't explain the workflow in one sentence, it's too complex. Current revenue from "boring" 3-5 node workflows: $12K/month Revenue from complex "impressive" builds: $0 What's the most overengineered disaster you've built? Let's share our therapy session 😅

💡 Making Money with AI Isn’t About the Tools – It’s About the Leverage Most people focus on which AI tool to use. The real question is: how can AI multiply your results in ways that humans alone can’t? Here’s the framework I use when advising clients:1️⃣ Automation – Eliminate repetitive tasks to reduce costs.2️⃣ Acceleration – Speed up workflows to produce more, faster.3️⃣ Augmentation – Enhance human creativity and decision-making with AI insights.4️⃣ Aggregation – Use AI to sift through massive amounts of data and find opportunities others miss. 💰 The businesses making the most money with AI aren’t “using AI” for the sake of it. They’re restructuring their business models around leverage. 👉 The opportunity isn’t to do what you’ve always done, but a little faster. The opportunity is to do what was previously impossible without AI. The question I leave my clients with:➡️ Where can AI create leverage in your business that your competitors haven’t even thought of yet?