Quick question that might sting a little: what's the one task you know AI could handle, but you keep doing the old way anyway? We've all got one. The weekly report you rebuild from scratch every Monday. The inbox that eats your first hour. The spreadsheet cleanup you dread. You've thought "I should automate that" a dozen times — and then just… did it manually again. Here's the thing I've noticed after working with a lot of you: the gap between people who use AI and people who talk about using AI usually isn't skill. It's a single, uncomfortable first attempt. The messy prompt. The output that's 70% right and needs a nudge. That first try feels like failure, so we retreat to what's familiar. But that 70% draft you almost threw away? That's not failure — that's a starting line most people never reach. The people getting real leverage from AI aren't smarter than you. They just refused to let "not perfect on the first try" stop them. So this week, I want you to pick that one avoided task and give it a real shot. Not a perfect prompt. Not a polished workflow. Just one honest attempt. Then tell us what happened — the win, the fail, the weird result. That's exactly the stuff this community learns fastest from. Progress beats perfection every single time. Your turn. Call to Action: What's the one task you've been meaning to hand off to AI but keep putting off — drop it below and let's crack it together 👇

We've all been there: you leave a 90-minute strategy call with three pages of scattered bullet points, half-legible scribbles, and a growing dread about follow-ups. Here's how to fix that in under 5 minutes with AI: Step 1: Record your meeting. Otter.ai, Fathom, or even your phone's voice memo app all work fine. Step 2: Paste the transcript into Claude or ChatGPT. Step 3: Use this prompt — "Summarize this meeting into: key decisions made, action items with owners and deadlines, and open questions that need follow-up." That's it. You get a clean, shareable summary in seconds — ready to paste into Slack, email to your team, or drop into Notion. The real win isn't just the time saved. It's that you actually participate in the meeting instead of frantically typing notes. You show up more present, your team gets clearer direction, and nothing falls through the cracks. I've seen people save 2–3 hours per week from this one habit alone. And once you start, you won't go back to doing it the old way. If you're running client calls, team standups, or strategy sessions — this is the lowest-effort, highest-return AI habit you can build right now. Call to Action: What's one meeting you wish you'd had AI notes for — and what slipped through the cracks? Drop it below 👇

Most people use AI like a search engine — they type a vague question and hope for the best. That's leaving 80% of the value on the table. Here's the habit that changes everything: give AI a role before you give it a task. Instead of: "Write me an email to my client about the project delay." Try: "You're a senior account manager known for maintaining strong client relationships during difficult conversations. Write an email to my client explaining a 2-week project delay, keeping the tone professional but warm." That one shift — adding context and a role — dramatically changes the output quality. AI models are trained to pick up on framing. When you define who they should "be," they draw on a much more specific slice of their training. This works across every use case: - "You're a financial analyst…" - "You're a high school teacher explaining this to a 15-year-old…" - "You're a skeptical investor stress-testing this business plan…" The more specific the role, the more useful the response. It takes 10 extra seconds and makes a night-and-day difference. Call to Action: Try it right now — what's a task you've been prompting poorly? Share the before/after below 👇

We had an amazing chat today about the various use-cases for Google's revolutionary NotebookLM as well as discuss the leveraging of AI to learn faster and become more creative. To watch the recording click here! Challenge #3 - Create a NotebookLM niched for your specific problem (not necessarily your solution). Include 15+ sources and generate 3+ artifacts. Be ready to share at the next UST Meeting (July 9th)