Your annual goal is probably losing to your to-do list. One of the simplest questions we worked through in the last AI Systems Lab was: What has to be true by Friday for you to still be on track for this month's income goal? Most planning systems start by asking, “What do I need to get done?” That’s how you end up with a longer list instead of a better week. A better sequence is: 1. Start with your monthly target. 2. Ask AI whether you’re actually on pace. 3. Have it identify the 1–3 priorities that will keep you on track. 4. Ask what should be deprioritized so those priorities have a real chance of getting done. 5. Use your AI assistant to help execute the plan. That’s where AI gets a lot more useful. Instead of giving you more things to do, it helps you decide what actually matters this week and helps execute. Next Friday, September 18th, we’re taking that same idea into a different part of your life: money. The next AI Systems Lab session is The Wealth Code | Build the Rules That Turn Income Into Wealth. Over the last 15 months, my net worth is up almost 13% and my cash flow has nearly doubled. AI has become a big part of how I pressure-test financial decisions & investments. On Friday, I’m giving you the exact financial playbook I use with AI. We’re going to define what financial freedom actually means to you, create the rules for how you want your money to behave, and use AI to pressure-test the decisions that follow. AI Systems Lab runs every other Friday and is included with Premium at $97/month. I’m opening a few guest seats to this upcoming session, if you’ve been curious about the Lab, this is a good one to sit in on. 𝗖𝗼𝗺𝗺𝗲𝗻𝘁 “𝗪𝗘𝗔𝗟𝗧𝗛” 𝗯𝗲𝗹𝗼𝘄 𝗮𝗻𝗱 𝗜’𝗹𝗹 𝗗𝗠 𝘆𝗼𝘂 𝗮 𝗴𝘂𝗲𝘀𝘁 𝗽𝗮𝘀𝘀. Already in the mastermind? You can watch the full replay from last week here ↓ Clarity x Execution = Freedom | AI Systems Lab Replay

Going down the rabbit hole! :).

Watch the video, then drop 1–2 things in the comments that you've had GPT do in the last week or so that would've blown your mind 3 years ago. I'll drop mine below

Most agents start with the wrong question: "Which AI tool should I use?" The better question is: "What team do I need around me?" True leverage isn't found in a single chatbot. It’s in building a small team of AI specialists equipped with your specific context, a set of skills, connected tools, and standards. If you want to start building your AI Team, here's a few roles I recommend adding to the lineup: - Chief of Staff: Routes work to team members and keeps context across your different businesses. - Lead Follow-Up Specialist: Prioritizes opportunities and drafts replies in your clients DISC language. - Marketing Assistant: Turns listings and expertise into campaigns and assets. - Client Care Coordinator: Elevates your client experience to earn repeat and referral business. - Operations Manager: Reviews SOPs, recurring work, and bottlenecks. Ten years ago, building this team required multiple hires and six figures in payroll. Today, $100/month in AI software unlocks these exact capabilities which is absolutely wild to think about. Here's my recommendation, forget about Claude vs ChatGPT comparison for a minute. Sketch the 3 to 5 specialists your business needs most, then decide what each one needs to know, do, and access. If you've built a CustomGPT, Agent, GrokBot, Hermes Agent, OpenClaw Agent etc. drop in the chat how it's been a game changer for you compared to the old way of using AI ↓

Most people are using AI one task at a time. - Write this email. - Summarize this meeting. - Analyze these leads. - Give me five ideas. Useful, but you are still managing every step. The bigger leverage comes from delegating the outcome. Instead of: Help me improve this email draft Try: Review my priority inbox using superhuman mail, draft replies to the top 5 emails needing my response and archive any notifications/spam emails that don't need my attention. Flag any decisions that require my judgment. A strong AI delegation usually gives it four things: - Outcome: What should be true when the work is finished? - Context: What does it need to understand about the business or situation? - Boundaries: What can it decide, and what requires you? - Definition of done: What should it return when the job is complete? If your workflow still looks like: You decide → AI completes one step → you inspect → AI completes another step you have accelerated the task. You have not really delegated the outcome. Implementation: Take one recurring workflow this week and give AI instruction around the finished result you want instead of micromanaging every task.