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Afternoon Tea is happening in 3 days
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Welcome to Clief Notes. Here's where to start.
1. Go check out 📚Navigating The Course to see how to get around and what's here. 2. Start with The Foundation. Concepts, folder architecture, prompting framework. Everything else builds on this. 3. Check in at the bottom of each lesson. Polls, discussion posts, other members working through the same stuff. Use them. 4. When you're ready to build real things join in on our Biweekly competitions and win some real cash. ⭐ Competitions Mega Thread 5. If you are wanting to dive into the masterminds, grab all the past templates, artifacts and resources. Upgrade and head into the The Vault for Premium and The Drawing Room (VIP) for VIP 6. Post your work. Ask questions. Help others when you can. What are you here to build?
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🤝 NEW: The Connection Hub is live
👋 Welcome to the Connection Hub - The Vault · Clief Notes So I was on the onboarding call this today, and one thing kept coming up that I couldn't stop thinking about: The biggest value of this new age isn't just the tools. It's the people. 👥 Specifically — people who understand AI the way THIS community teaches it. Not "prompt hacks" and not "10x your output" nonsense, but actually building systems, thinking in workflows, and treating AI like a real part of how you work. That's a rare group. And a lot of you told me the same thing: 💬 "I'd love to work with someone who gets this." 💬 "I want to break into [industry] but don't know anyone in it." 💬 "Who else here does what I do?" So instead of letting those connections happen by accident... I built a place for them. 👇 🗂️👋 Welcome to the Connection Hub - The Vault · Clief Notes It's a simple set of pages, split by industry. You find your corner, drop a quick intro about what you actually do and what you're looking for, and connect with people who speak your language.
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📢 Recordings of Tea Masterminds are live: The Second Brain
🧠 This round was about what a second brain actually is: a context layer you and your AI both read, not a notes app. The Afternoon Tea is the teaching. The High Tea is the room putting it to work on scale, memory, trust, and security. Here is what I want you to understand about these drops, because it is the whole point of being in here. While the videos are valuable and being able to sit and answer your questions is a big reason for them that's not the only value they hold. 📄 Every drop is a set of working files. Markdown built to be used and reused. Each one ends with the exact data to give your AI for your own situation. This round also ships a starter folder you can open, run the self-audit on, and walk away with the skeleton of your own second brain in a sitting. 🤖 I build them expecting you to feed them to your AI. That is the design. Hand a whole round to Claude in a few minutes, whether or not you made it live. The room's thinking is in the files, so you lose almost nothing by catching it later. 🔄 They adapt. A prompt pack is frozen. These are meant to be reshaped: update the context, swap in your own work, bend the templates to your process. And they grow on my side too, as we learn together in these calls. The call is dialogue. The package is that dialogue, crystallized into something you can run. Next round builds on this one. ☕ Afternoon Tea 6 →Afternoon Tea 6 (Second Brain Chat) 🫖 High Tea 10 → High Tea 10 (Second Brain Deep Dive) 🧭 How you should use these: 🔹 Show up live when you can. Your questions shape the next drop. 🔹 When you can't, rewatch, or drop the files into your AI and run the prompt at the bottom. 🔹 Open the starter folder and build your own version. Rename it to your work. It is yours to keep. 📚 A mastermind ends when the call ends. What you get here keeps working after: a structured version of your own thinking (and some of my own thinking!) that improves every round. In my opinion that is worth more than the hour in the room. (or three as some of you stick around in these calls to chat)
How do you know which memories your agents actually use — not just which ones you stored?
For anyone running a persistent memory layer that more than one agent reads from — as it grows, how do you know which entries actually get pulled into a run vs. which just sit there adding retrieval noise? Storing is easy and every run tempts you to write more, but a memory that never gets retrieved isn't context — it's surface area the next search has to wade through. I can measure what I wrote; what I haven't cracked is measuring what actually loaded and changed an output. So — do you track retrieval-per-entry and prune what never fires, or is it still by feel? And if you prune, what's your signal that a memory is dead weight and not just rarely-needed?
Context Shaping as a Missing Layer in Agent Workflows
I’ve been thinking about something adjacent to ICM that I’m calling Context Shaping. ICM makes a lot of sense to me as a way to make agent work visible: files, intermediate artifacts, editable surfaces, and a workflow the human can inspect or participate in. But I keep coming back to another layer that feels separate: Before the agent works, how is the context shaped? In real business workflows, the raw context is messy. It may live across email, calls, meeting notes, documents, spreadsheets, CRM records, support tickets, internal notes, and prior decisions. But I don’t think the answer is to just dump all of that into a giant context window or “business memory.” The harder problem seems to be shaping the right context for the specific workflow step. For example: What should be included? What should be excluded? What should be summarized? What should be redacted? What is only visible to certain roles? What previous decisions matter right now? What context is stale, misleading, or no longer safe to use? What does the agent need to know for this task, without giving it everything? From my point of view, this becomes especially important when agents are operating around real business workflows: handoffs, approvals, follow-up, estimates, customer conversations, internal tasks, project coordination, or anything where the wrong context can create bad decisions. So the distinction I’m playing with is: ICM gives the agent and human a visible workspace. Context Shaping prepares the context pack that enters that workspace. That context pack might include source references, summaries, constraints, permissions, open questions, excluded information, and a record of why certain context was selected. I’m curious if anyone here is thinking about this problem. Are you treating context as something the agent retrieves on its own, or as something that should be deliberately shaped before each workflow step?
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