If l have been blinded side it’s not my intention But the value of community is key And conversations of sharing Finding your feet Help with teaching and understanding of complexities Setting up clones Experts at Hand Dean/ Tony and the many many more in our community Learning a new language connections in and out Makes every day a better one from the last YOU ALL ROCK

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Hey everyone, I saw so many people in different communities talking about receiving so many cold emails every day and how to make them stop. Here’s my honest opinion: cold email is actually a fantastic way to sell your offer. I use it myself, but I send customized, intentional messages… not the generic “Hey Mr. X, buy my offer.” That’s a deeper topic for another day. What I want to share today is how you can completely eliminate cold email clutter in your own inbox. With an AI agent like this, you can filter your Gmail (or any inbox), prioritize the right emails, and instantly clean out anything unwanted. It can auto-label, auto-reply, or mark irrelevant emails as read so you never have to deal with them manually again. If you have any questions about how this works, feel free to ask. I’m here to help.

Here's something we keep seeing: People say they want to "learn AI" but then get overwhelmed and give up. The problem isn't that AI is too complicated. The problem is they're approaching it like it's a subject to master rather than a tool to use. Let me explain the difference. "Learning AI" sounds like: Taking courses about how neural networks function Understanding the technical architecture of large language models Studying machine learning algorithms and training processes Becoming an expert in AI capabilities and limitations That's learning about AI. It's interesting if you're a researcher or developer. But it's completely unnecessary if you just want AI to help your business. Using AI effectively looks like: - Identifying a specific problem you have - Trying an AI tool to solve it - Seeing what works and what doesn't - Adjusting your approach - Repeating until you get results Notice the difference? One is theoretical. The other is practical and immediate. Here's the analogy: You don't need to understand how an engine works to drive a car. You don't need to know the chemistry of cooking to follow a recipe. You don't need to grasp the technology behind your smartphone to send a text. Same with AI. You don't need to know how it works to use it effectively. So what skill actually matters? Problem identification. Specifically, the ability to recognize which of your problems might have an AI solution. That's it. That's the skill that separates people getting massive value from AI and people who tried it once and gave up. What this looks like in practice: Let's say you're a coach and you spend 5 hours every week manually scheduling client calls, sending reminders, and rescheduling when conflicts come up. Someone who "learns AI" might research scheduling algorithms and calendar integration APIs and get lost in technical complexity. Someone who uses AI effectively thinks: "This is repetitive and time-consuming. I wonder if AI could help." They search for "AI scheduling assistant," find tools like Reclaim.ai or Motion, test one for a week, see it cuts their scheduling time to 30 minutes, and move on.