My mind has been playing tricks on me, telling me that this community might not need my kind of content. Maybe because we are mainly builders and always building here. My information is not heavy on harnesses, labs and experiments (even though I build myself). It’s more leadership focused. I address leaders and how they should lead in this age. I’d love to share but I don’t want to share what we won’t need. So I’m asking. Would we like that?

Perhaps we're governing AI as if it were traditional automation. And that may be part of the problem. Traditional automation encourages a particular expectation: Input X → Rule Y → Output Z. We expect the process to behave as designed. AI, particularly ML-based and generative systems, might require a different mindset. We should assume that it will be wrong sometimes. Not as an exceptional event. As a property we need to design for. Suppose an AI system achieves 95% accuracy. Is that good? The answer isn't really in the 95%. It's in the 5%. - If 5% of automatically generated document tags are wrong, perhaps nobody particularly cares. - If 5% of employment, credit, medical or safety-related decisions are wrong, we have a very different problem. So perhaps one of the first questions in AI governance should be: - “Can this use case tolerate the AI being wrong?” That changes how we think about human oversight too. One response to imperfect AI is: - “The AI isn't 100% reliable, so we'll put a human in the loop.” But if a human has to validate every output, we may have simply created an expensive form of automation, and potentially a rubber-stamping exercise. Instead, perhaps we need to treat AI for what it is: ML, not deterministic automation. That means: → Define the expected performance before deployment. → Build evals around the actual use case. → Understand the failure modes, not just the average accuracy. → Define what kinds of errors are acceptable—and which are not. → Establish thresholds and escalation mechanisms. → Monitor performance after deployment. → Design the process assuming the model will sometimes fail. And then decide where human intervention actually creates value. The objective shouldn't necessarily be: - AI + human checking every output. It should be: - AI operating inside a system designed to tolerate, detect and manage its inevitable errors. This leads me to a principle I increasingly find useful:

Last month I was speaking with a friend who works for an engineering firm in Australia about ai, and all the cool things we can do with it these days, and he mentioned that he was trying to push to get a monthly newsletter out to their team to inform them of upcoming professional development courses and workshops. Of course it takes a lot of time to manually search the relevant websites, and put together a newsletter, etc. so no one has done it. I asked a few more questions about the tools they use, and then went and built out a small, structured ICM folder system, with the exact same blueprint that we have been learning in here and using for the competition building. I then made a loom video showing how it worked, and then emailed it to him along with the fully company branded email that it output. It was near the end of financial year at the time, so they were a bit busy, and he said he'd get back to me. Today, 1 month later, he came back and accepted my quote of $600, which includes 2 rounds of revision. To get the draft up and tested, it took me probably about 4 hours, and then there will be another few hrs in finalising it (with the revisions). In reality I probably undersold myself, but this is a side project at the moment (I run a cafe, not an ai consulting business...yet!), and I was excited to have the opportunity at a real client to test against. Let me be clear, I'm not selling a fancy Ai loaded website or app or anything... It is literally 5 folders, with a top level claude.md file, instructing claude co-work (or claude ai or code - or any other Ai tool that can follow structured instructions with a renaming of the claude.md file) on exactly what to do. This is exactly what Jake has been teaching here, and it will stand the test of time. As Anthropic updates their interface, and Open Ai starts to take over claude or another better tool comes along, this ICM folder system will continue to do its thing. It may need some tweaks along the way, but it's not going to need it's whole codebase updated or anything, because it's all plain language, english instructions.

👋 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.

It’s live. Starting today, everyone in Clief Notes has access to the new Clief Notes AI. The easiest way to use it? Don’t overthink it. Ask it the question you would normally ask me. “Where should I start?” “What should I focus on next?” “Where did you talk about [topic]?” It’ll use what’s already inside Clief Notes to help answer you and point you toward the right lesson or resource when there’s something worth going deeper on. The goal isn’t to give you another AI tool to play with. It’s to make everything already inside this community easier to actually use. If you want Access to it Comment "READY" and we'll send you access to it!