Very interesting worth checking out... https://workspace.google.com/blog/product-announcements/introducing-google-workspace-studio-agents-for-everyday-work

We keep hearing it. "AI will enhance jobs, not replace them." It's the same reassuring mantra repeated by CEOs, consultants, and optimists everywhere. But I've spent the past three years building AI applications in voice and chat as a Chief AI Officer. I've watched the technology evolve from impressive to devastating. And I need to tell you something nobody wants to hear: They're lying to you. Or worse, they actually believe it. The "AI will enhance not replace" narrative is exactly like saying automobiles would enhance horses, not replace them. Sure, technically true in the narrowest sense, some horses still exist. But we didn't need 20 million horses in 1900 to become 20 million "enhanced" horses in 1950. We needed about 3 million. The other 17 million? Gone. Except this time, you're the horse. The Numbers Don't Lie, They Scream October 2025 just became the worst month for job cuts in over 20 years. Companies announced 153,074 layoffs, almost triple the same month last year. This isn't a blip. This isn't a correction. This is the beginning. By July 2025, over 130,000 tech workers had already lost their jobs. The year isn't even over and we've seen more than 806,000 total job cuts announced, the highest figure since 2020. But here's what should terrify you: these aren't struggling companies. Microsoft posted $70.1 billion in revenue (up 13%) while cutting 15,000 jobs. Cisco reported a 5% revenue increase and then laid off hundreds. Intel is eliminating 15% of its entire global workforce, not because they're failing, but because they're "optimizing." The pattern is clear: profit is up, humans are out. What's Really Happening Behind the Press Releases Let me give you the translation guide for corporate-speak: When Amazon CEO Andy Jassy says AI will lead to a "reduction in corporate workforce," he's not talking about restructuring. He's talking about 14,000 middle managers being shown the door. When Microsoft mentions GitHub Copilot writing 30% of new code, they're explaining why they don't need thousands of engineers anymore.

Someone just asked about AI accuracy, and I realized this is something we all need to talk about. Because here's the thing: AI is incredibly powerful, but it's not perfect. And knowing how to work with that? That's the real skill. Let me share what I've learned about getting more accurate and reliable results from AI. The Truth About AI ChatGPT and other AI tools can absolutely give you wrong information sometimes. They can be confidently incorrect. They can make stuff up. This isn't a flaw you need to work around forever (probably), but it's reality right now. The good news? Once you know this, you can use some simple strategies to get way better results. Here's What Actually Works Make it show its work. Add phrases like "explain your reasoning" or "walk me through your thinking" to your prompts. When AI has to justify its answers, it tends to be more careful and accurate. It's like asking a student to show their math work. Get specific with your prompts. Vague questions get vague (and sometimes wrong) answers. Instead of "tell me about SEO," try "give me three SEO strategies for blog posts in 2025, with specific examples." The more detail you provide, the better the output. Double-check important stuff. If you're using AI for facts, dates, statistics, or anything critical, verify it. I always do a quick Google search for anything that matters. Takes 30 seconds. Saves potential headaches. Challenge it when something feels off. Just say "are you sure about that?" or "can you reconsider that answer?" You'd be surprised how often it'll correct itself and give you something better. Ask for confidence levels. This one's been huge for me. Add "rate your confidence in this answer from 1-10 and explain why" to your prompts. When it gives itself a 5 or 6, you know to dig deeper or verify. Turn on Deep Research. Most LLMs now have a deep research mode (ChatGPT, Claude, Gemini, DeepSeek, Perplexity). This feature actually goes out and finds real sources, validates information, and gives you thought-through links and content. It takes a bit longer, but the accuracy jumps way up. Game changer for anything factual.

I've seen two questions in the community lately that I bet a lot of you are thinking about too. "Can someone share an AI tool to increase sales and improve customer follow-up?" "I need help managing social media for my business but don't know where to start." Both of these questions are really asking the same thing: How do I get more leads and actually convert them without drowning in complexity? Here's what I realized. People keep asking for THE tool. THE platform. THE solution. But the real problem isn't finding one magic tool. It's not having a strategy that fits YOUR specific business. And that's exactly what AI can do better than any single tool ever could. Instead of hunting for the perfect lead gen software or social media scheduler, you can have AI become your personal lead generation strategist. It can analyze your business, build a custom system, research the best tools for YOUR situation, create content strategies, design follow-up sequences, and give you a step-by-step action plan. All from one conversation. I'm talking about ChatGPT with web search enabled (Claude works great too). Not some expensive software. Not a complicated funnel builder you'll never figure out. Just an AI that can think through your entire lead gen strategy with you and then help you execute it. So I built a prompt that turns any AI with web search into your lead generation expert. And I'm not exaggerating when I say this thing is comprehensive. What This Prompt Does: It starts by understanding YOUR business (what you sell, who you serve, where you are now). It builds a complete lead generation strategy customized for you. It researches and recommends the actual best tools for your budget and needs. It creates social media content strategies that attract your ideal customers. It designs customer follow-up systems that actually convert. It shows you how to track what's working and what's not. It gives you a prioritized action plan so you know exactly what to do first.

Okay, so you just joined this community and you're looking at Skool thinking... what now? How does this actually work? And how do some people seem to level up so fast? Here's the thing: Skool is different from other platforms. It's not about who posts the most or who has the flashiest content. It's about who actually helps people by getting likes. And that's honestly refreshing. Let me break down what I've learned (because I'm still figuring this out too, but these things have made a huge difference). How Skool Actually Works You've got levels. You see that number next to your name? That goes up when you contribute value to the community and people like what you do. Every time you post something helpful, answer a question, or engage meaningfully, you earn points when people like it. More points = higher level = more visibility in the community. But here's what really matters: the points are just a reflection of how much you're helping others. That's it. The system rewards generosity. The Leveling Up Secret (It's Not What You Think) I see people trying to "hack" their way up with tons of posts or constant comments. It doesn't work. You know what does? Show up to give, not to get. Answer questions from beginners even if they seem basic. Share what's working for you. Celebrate other people's wins. Drop a helpful resource when someone's stuck. Be the person you needed when you were starting out. Seriously, the people who rise fastest are the ones who forget about levels entirely and just focus on being genuinely helpful. What Great Content Looks Like Here You don't need to write novels or create complicated tutorials. Some of the best posts I've seen are simple: A quick win someone can try today. A tool that saved you hours (with how to use it). A prompt that actually works (copy and paste ready). A mistake you made and what you learned. An answer to a question you see asked repeatedly. Make it practical. Make it actionable. Make it beginner-friendly. That's the formula.