Found a piece of my own client work this week that had been sitting stalled for thirteen days. Fully drafted. Ready to go. It was stuck because one handoff step never happened, and nothing caught it until I stumbled on it by accident. Around the same time, I'd been asking clients a blunt question: what are you actually paying me for? AI can build the website, write the ads, draft the campaign now. Three separate conversations, no coaching between them, same answer: assurance. They're not marketers. They don't know what's happening day to day. They want to know someone trustworthy is watching it. So the plan was to automate proof. AI reads the data, drops five plain bullets into the agenda instead of a generic monthly PDF. Here's what we did. Here's why. Then I looked at why nobody caught the stalled one. I never had a name for "stuck because someone outside the loop hasn't gotten back to me" as its own thing, separate from normal waiting. Both just read as "waiting." If you can't tell the two apart, nothing will flag the difference until you trip over it by accident. If the product is "I'll make sure it's handled right," the proof of that can't be an AI summary nobody double-checks. An unchecked summary just hides the same invisible-work problem one layer deeper. When part of your process depends on a real person outside your system getting back to you, how do you tell "still waiting, that's normal" from "quietly stuck," before you stumble into it by accident? Who's actually watching for that, if you're honest? I had been disciplined about not building a UI for my ICM because I thought it was a waste of time. But now I feel like I need a dashboard for KPIs and statuses so I know what's actually going on under the hood. Anyone else running into this? And by ICM I mean my Operating System or Second Brain.

https://youtu.be/9dYcwOkpCE8?si=xR-v5G1P27L7KPIU Fun - dropped yesterday. Went from specific inflexible agents to using files and folders.

I have something that sorts my incoming work before I see it, and a while back I let it start learning from what I did afterwards. Replied, acted on, ignored, deleted. It adjusts what it puts in front of me next time. It works, roughly. But I keep hitting the same wall: I am a bad teacher and I have no way to tell it so. A week where I am underwater looks exactly like a week where nothing mattered. A Sunday cleanup where I clear a pile of things in four minutes teaches it that the whole pile was unimportant, when really I was just tired of looking at it. And the things I avoid because they make me uncomfortable are often the ones I should have opened first, so it learns to hide precisely the wrong stuff. I have patched the obvious cases. Anything cleared in a big batch counts for less. Age is taken into account before an ignore counts as a judgement. But those are guesses about my own behaviour, and I have no way to check whether the guesses are any good. What I keep landing on is that the signal is cheap and abundant and mostly meaningless, and the signal I actually want, did this turn out to matter, arrives weeks later if at all, and never in a form anything can read. So: anyone here letting a system learn from your behaviour rather than from your instructions? How do you stop it learning your bad weeks? Or have you tried it, decided it was not worth it, and gone back to writing the rules yourself?

Made an MCP that connects EdubaWare to your favorite models !

EDIT: WE HAD OVER 100 PEOPLE SIGN UP IN TEN MINUTES....GOING TO BE ROLLING OUT ACCESS ON SLOWER BASIS NOW SO I DONT RUIN MY BANK ACCOUNT WITH TOKEN SPEND FOR YALL (im covering ai costs for everyone) but keep applying we are keeping track and will be letting more people in and reaching out about getting you all access one by one especially VIP. Our Platform is here, the thing a lot of you have been asking for and I have been teasing Take your ICM folders and second brains, put them in the cloud, and work on them together in real time. You upload your folders and files. One strong model with a good harness reads the map and becomes the agent you need. No new agents to build, no zip files to pass around. Each workspace runs in its own container. It renders your markdown, edits your files, installs packages, runs Python and Playwright, and multiple people can work in the same space at once. No Mac Mini needed to keep your data separate either. We're opening it to VIP and alpha testers first, and I'm covering the AI cost while we test so cant do a full role out yet. Free AI use which is great for those users, not great for my bank account haha. ✍️ Sign up for access: https://docs.google.com/forms/d/e/1FAIpQLSdSnToxclxt8EgoB2GizrEvHP7gzOedVcRXdCkpi1SZwR8ZfA/viewform 🔗 Questions, or want to work heavier with this? Email [email protected]