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The Secret to Getting 10x More Relevant Results in ChatGPT
In this video, I show you every way to customize ChatGPT as of October 2025. This includes personalization options for both the free and paid plans, so no matter how you use ChatGPT, this video will teach you how to set it up to get the best results!
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🔄 From One-Off Prompts to Habitual AI Use
Many people believe they are using AI because they have tried it. A prompt here, a draft there, an occasional experiment when time allows. But trying AI is not the same as integrating it. Real value does not come from one-off interactions. It comes from habits. AI delivers its greatest impact not when it is impressive, but when it is ordinary. When it becomes part of how we think, plan, and decide, rather than something we remember to use only when things get difficult. ------------- Context: Why AI Often Stays Occasional ------------- Most AI use begins with curiosity. We explore a tool, test a few prompts, and are often impressed by the results. But after that initial phase, usage becomes irregular. Days or weeks pass without opening the tool again. Each return feels like starting from scratch. This pattern is understandable. Without clear integration into existing routines, AI remains optional. It competes with habits that are already established and comfortable. When time is tight, optional tools are the first to be skipped. Organizations unintentionally reinforce this pattern by framing AI as an add-on. Something extra to try, rather than something embedded into how work already happens. As a result, AI remains novel, but not essential. The gap between potential and impact often lives right here. Not in what AI can do, but in how consistently we invite it into our workflows. ------------- Insight 1: One-Off Use Creates Familiarity Without Fluency ------------- Trying AI occasionally builds awareness, but it does not build intuition. Each interaction feels new. We forget what worked last time. We rephrase similar prompts repeatedly. Learning resets instead of compounding. Fluency requires repetition. The same way we become comfortable with any tool, language, or process, through use in similar contexts over time. Without that repetition, AI remains impressive but unreliable. This is why many people describe AI as inconsistent. In reality, their usage is inconsistent. Without patterns, there is no baseline to learn from.
🔄 From One-Off Prompts to Habitual AI Use
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3 things I do every weekend to set up my week
I’ve learned this the hard way. If you wait until Monday to get focused, you’re already behind. Here’s how I set up my week before it starts: 1. I choose ONE win that mattersNot a to-do list. Not busy work. One outcome that actually moves my life or business forward. That goes on the calendar first. 2. I remove friction ahead of time I look at my week and ask,“What’s going to trip me up?” Too many meetings, distractions, low-energy days. I fix it now so I’m not relying on willpower later. 3. I reset my environment Desk clear. Calendar clean. Priorities visible. When Monday hits, I don’t want to think... I want to execute. This isn’t about discipline. It’s about design. Winning weeks are built before they begin. What about you? What’s the ONE thing you do to set yourself up to win the week ahead? Drop it below 👇
How did you land your first client? (What exactly worked)
I’m trying to land my first client / first demo call and I want real mechanics, not theory. If you got your first client from cold outreach, can you break down exactly what you did? Channel: cold email, IG DM, LinkedIn, cold calls, walk-ins, referrals? Volume: how many touches/day and for how many days? What got the first “yes”: a short email, a Loom audit, a phone call, a calendar link, a free pilot? Follow-up cadence: how many follow-ups before you booked? Also: I’m not in the U.S. — did you call businesses directly to book demos? If yes, did they care about the number being international? I’m running a DBR / patient reactivation pilot (pay-per-show) for Med Spas. My goal is to book one demo call this week. Appreciate any real playbooks you used.
📰 AI News: Notion Quietly Tests Custom MCPs, Workers, And A Computer Use Agent
📝 TL;DR Notion is quietly testing a big upgrade to its AI Agents platform, including custom MCP tools, background Workers, and a Computer Use style agent that can control other apps. In plain terms, Notion is trying to turn your workspace into an automation hub, not just a note app. 🧠 Overview New leaks from Notion’s internal builds show the company expanding its agent platform well beyond simple chat inside a page. The experiments include support for custom MCPs, worker style automations, new external connectors, and an agent that can operate your computer or browser for you. If these features ship, Notion shifts from “AI that writes text” to “AI that runs workflows,” which is a big deal for solo operators and teams already living in Notion every day. 📜 The Announcement TestingCatalog spotted an unreleased Notion build labeled “Notion testing custom MCPs, Workers, and Computer Use agents,” along with copy that spells out the strategy, Notion is expanding its custom agent platform with new connectors, custom MCPs, and new AI tools, positioning itself as an automation hub. None of this is officially announced yet, so it is still experimental and may change, but it lines up with Notion’s recent push into AI first workspaces and custom agents that can work across your docs, tasks, and databases. ⚙️ How It Works • Custom MCPs - Notion appears to be adding support for custom Model Context Protocol tools so teams can expose internal APIs, databases, and services directly to their Notion agents. • Workers for background jobs - A new Workers concept suggests longer running or scheduled automations that can be triggered from Notion pages, databases, or events without you clicking a button each time. • Computer Use agent - The Computer Use style agent is designed to control apps that do not have clean APIs, for example by driving a browser or desktop UI so agents can complete tasks end to end.
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📰 AI News: Notion Quietly Tests Custom MCPs, Workers, And A Computer Use Agent
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