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Clief Notes

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47 contributions to Clief Notes
Building out my first real ICM use case for someone else - starting close to home.
My mum works in corporate America and is stretched thin. Spreadsheet analysis she has to run manually, a constant pile of emails to draft, life admin on top. She also maps out her processes with mind maps and flowcharts already - the raw material for a second brain is there. The use cases are obvious. She just needs the cognitive load cut. The plan is to wrap her an ICM system she can actually use - one interface on her Claude Enterprise subscription, so she doesn't have to think about what's underneath. I'm 18, built this for myself, and I'm starting to look at consulting for local businesses. This is the first test of translating what I know into something that works for someone else. The scoping process I'll sit with Claude and design the approach. What I'm after is the specific stuff: what would you actually tell someone [me] doing this for the first time with a non-technical user who's already process-minded?
1 like • 3h
@Joseph Dodds Great idea, hadn't thought of checking the competition thread - thanks Joseph 🤝
0 likes • 2h
@Scott Smith Thanks, Scott. Hopefully 🤝
Sneak Peak: my ICM based content creation assistant 📁
Deep dive will be coming in the next couple weeks after I get back from my vacation next week. Be on the lookout for that. Til then here’s a sneak peak at how I’m building blog posts, shorts, and other content and how I’m also building up to launching long form content as well. Subscribe if you like my content! Let the algorithm know it’s worth watching 😁
1 like • 13h
This is exactly what AI should be doing - not just processing tasks but actually knowing you well enough to draft for you. Running something similar - a personal agent that reads across everything and surfaces what matters. The part that compounds is the context: the more it stores, the better it gets at connecting similar instances, and the advice starts bending closer to how I actually think and what I actually need. The other thing this shows is how important the process of building is beyond the output. The system thinking you develop just from planning something like this - working out how to structure context, what to feed it, how to close the loop - that carries into everything else you build. Worth doing even if the tool never gets finished.
0 likes • 4h
@Don Roy 100% agree, Don. So many people get caught up in the systems and different words and thinking but just strip it back to the basics and think about actual use cases. It's something Jake said that really struck me: stop trying to implement the business into your AI stuff. You should try to implement AI into your business stuff. The foundation should always be the actual thing that is important to you. AI is just what can reduce friction. AI is the tool and the layer on top not the substrate
Your ICM works. So why is it getting expensive to run?
Quick recap, because this is "part 3" following @Bas Rosario 'cake' post and my first follow up. Thank you @Brendan Tucek. Your post is what got me thinking about this 3rd part. Bas taught us to break the cake into ordered steps, one instruction per folder. My follow up post zoomed in on the step that checks the cake — the toothpick, the gate. This one is about the part nobody warns you about until it shows up on the bill: cost. Here's the symptom. Someone in here recently posted a folder system that genuinely works, doing real work in their business, and then admitted the part most people don't: it burns a lot of tokens just figuring out where to look. 🪙 If you've built anything past a toy, you've felt this. The structure is fine. It's getting slow and expensive anyway. 💸 Here's where it comes from. In most ICM setups there's one file the AI reads before every single task. The map. The "you are here" file. Every word in it gets paid for on every interaction, whether the task needed it or not. And that file has a way of growing. You add a rule, then a note, then the whole folder tree, then some history, and one day your always-open page is a 3,000-word document. Now the model re-reads a small book before it cracks the first egg. Every time. 🥚 The fix is the oldest trick in any real kitchen: 'mise en place'. 🧑‍🍳 You don'tdrag the whole pantry onto the counter to make one cake. You bring out what this step needs, and everything else stays in the cupboard until it's called. For your folders, that means the always-loaded file is an index, not the recipe. It points. "Buyers live here. Follow-ups here. Voice guide here." 📇 One glance, then jump. The actual detail lives down in the step folder that only opens when the AI is standing in it. Whoever needs the frosting technique walks to the frosting folder. They don't carry the frosting instructions around all day in case it comes up. So the through-line of all three posts is one discipline pointed at three different things.
0 likes • 8h
@Carmen Aviles I'll post it later today, the full work through live demo, etc., and I appreciate the support!
1 like • 4h
@Gabriel Azoulay I really appreciate it Gabriel! And I think you said it right. It's the bedrock thinking, and it's not about the system that anybody creates. It's about the thinking that develops that system. It's all about separating from all of the ICM and technical jargon and thinking from a business and life perspective. How do you do what's called "cross-pollination," which means taking this and putting it in a different context that makes sense. That's where the logbook comes in. If something isn't quite working well and things are out of order, then you introduce a mechanism where you log a lot and you have the data there to go back on. The prompt performance isn't grading the prompts themselves and you can build it however you want. The idea is that it just measures whether the prompts happened, the input, and the output, and it's something to look back on. You can create a mechanism where during the touchdown phase you can have Claude note down any additional context that was required and log any data or points that were prompt-related. You can then review the prompt performance.md and make any edits to the initial instructions given to a worker bee. There may be a slight misunderstanding because the worker bee doesn't run the prompt. The worker bee gives the prompt and the Claude code performs it. They're doing two separate things, so they can't just grade nicely if that makes sense
Fast isn’t always the goal
Ok. I’m @David Vogel ’s one hit wonder. I’m beavis to his butthead. I had a post that went crazy in here about two months ago: I got a verbal agreement to start an ai transformation. ‘Good news!” Well in the meantime the CFO switched, new employees entered to scene…the allocation of resources became stricter. People went on vacations. I learned a greater depth to how this company needs to pass fees through to entities. It got complicated. Slower. More …who knows…maybe? Well…I signed the agreement with them today. 6mos. Same project I pitched for 3mos but at a slower financial drip for company. A few caveats that weren’t AI related that I’m happy to get as designer… All based around -what does the company I bill…bill this to and measure it against? General AI world communicates and pitches more like, “GAH’ I built a spaceplane and went to andromeda today and yesterday I was just making nachos! “ I’m being extreme to make a point. But, the insight is that decisions and agreements take mutual comprehension and clarity of vision AND performances from many different parties with different perspectives. Yes ‘outcomes’, but it’s a gamble. ‘Potential outcomes’ You have to de-risk your bet—-while you keep studying the table. AI news and marketing mostly is whizbang fomo nonsense. The work and success is in mutual agreements and buy-in. AI is just a tool. The work is finding problems and spending the time with all the parties to create buy-in on solutions. Is a camel a horse by group-design? Yes—- but if everyone wants to live maybe it’s the better animal. Anywho. Get buy in. Listen. Adjust. Listen. Adjust. Listen. Adjust.
1 like • 10h
@Mira Bradshaw yeah I love that analogy about just taking away the matches before and then you don't have to worry about putting out the fires. I could imagine that's a lot more prevalent with team workflows as well. Everything I'm doing is currently solo but I could imagine having multiple people work on this. I'm going to do a post on my full system soon, but I find that having a concrete loop and having every Claude Code job write touch downs is really beneficial for keeping everything in check. I'd be interested in hearing the actual ways that you "take away the matches"?
1 like • 10h
@Mira Bradshaw great, thanks - much appreciated - I'll take a look at those :)
Open Model Beats Opus 4.7 - Runs on your laptop
Ornith-1.0: the open-source coding LLM that matches Claude Opus 4.7 — and runs on your laptop. This open-weights agentic-coding model hits 77.5 on Terminal-Bench and 82.4 on SWE-bench Verified, beating Claude Opus on both, then ships a 9B size you can `ollama run` locally. MIT licensed, four sizes, and it taught itself the harness.
0 likes • 11h
Incredibly interesting, gonna be looking at getting this set up and running locally for my own workflows
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Alex Brown
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@alex-brown-3474
17 y/o - My YouTube Channel: @alexbrown_ [5 million long form views in 2025] - Involved in multiple entrepreneurial ventures - Student of The Universe

Active 27m ago
Joined Apr 3, 2026
UK
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