I was invited to sit on a panel this morning: "AI in Action: The Mindset Behind the Moves," at Auxiom's Community Appreciation Event, attended by 120 business leaders in Detroit Metro. Grateful to Founder and CEO Matt Loria for the invite. Auxiom is a local IT and cybersecurity company. Before the panel, Ashok Sivanand (Nous) ran the room through a workflow-redesign workshop. He opened with a stat from McKinsey: 80% of companies doing generative AI work saw no change in profitability. He paired it with another: only 1 in 5 companies had actually redesigned a workflow before pointing AI at it. Same 1 in 5, both times. He called it a coincidence. This is similar data I referenced in David's Corner, The Tool is 10 Percent. His worksheet was amazing though: name the constraint, name the workflow, name your customer, find the leak, pick one fix, run a 30-day experiment with a guardrail and a report-back date. His line on the handout: diagnose before you prescribe. All 120 execs walked out of that room with a real next step; that's rare for many speakers. On the panel, I got to talk about an idea I've been writing about here: AI does two different jobs. It's good at mining your own record for what's already true, and it's good at amplifying whatever you give it. Skip straight to amplifying, and the output sounds like everyone else's. Someone asked what my own transition looked like, going from a 12-person team to running alongside 20-plus specialists. Two years chasing tools before I found ICM. Two weeks after that, I converted all my unstructured data into structured markdown and built my routing map and orchestrator, Duke. After, a CIO on the panel asked me how I was able to orchestrate across 50k markdown files. I said, "Simple: a map, and dropped Jake Van Clief and ICM as the solution." The closing session was Aaron Salko and Kelly Johnson on human performance. A line I wrote down: "Technology creates capability; human performance determines the outcome". If you've got performance gaps today, AI doesn't fix them. It multiplies them across more people.

I think I have 30-40 hours left of Fable access. My usage has just ticked over to 56% used. I had enough of a build queue that I decided to upgrade my plan just for this month and the Fable-in-subscription window and honestly, it's already been worth it. How those tokens have been spent: - 5% used to complete a system recarve and hardening pass - 35% used to orchestrate a full substrate port (from NotePlan to Notion) *and* a full branch that is future compatible with that state ready to switch to on Friday assuming this week on Notion goes as planned (oh and a full school comms rewrite to go with my brand new gmail set up exclusively for my system to access). I didn't have to build a thing in Notion - Sonnet dispatches did the lot. - 5% used to build the work order stage of my construction crew - 11% used to build the orchestration, build oversight and dispatch stage of my construction crew (and a massive shout out to @Ari Evergreen - I forked Pushing Dispatch_ and that helped me keep this to 11% of Fable orchestrating, otherwise it would have been more) Every stage of the construction crew has been pushed through a live run of the step before it in the chain to produce the document that guided the build. For the work order stage, that meant a PRD from the first stage and a build spec produced by the second stage. For this orchestration, it meant that I had fully sliced work orders, mapped to my schema, clustered to work packets that made sense. 8 stages; that were able to run in an orchestration-style mode (on Fable, I would not have let Opus go like that to be honest) and I came back to high quality work, measured to my own rules and standards and only a few small tweaks that didn't require substantial rework before committing. Honestly, the fact that something of this scale could be overseen with only 11% usage feels like a real testament to the whole chain here. I mean... this is really something. That means I still have 44% of my Fable tokens to go and only 30-40 hours to spend it in... and now we see how much of it I can use before I lose it... Wish me luck.

This was the first community I joined, and my first real go at AI beyond just talking to a chat window. I found it pretty much by chance, lurked for a few months, and High Tea 6 was my first call. I didn't realise at the time how much that would shape things. The picture I got here was a healthy one. Build the thing, watch how it actually behaves, be honest about the bits that don't work. I've spoken to enough people since who came in through paid courses to know that isn't the norm. Nobody here sold me a shortcut, and I got pretty lucky landing here first rather than somewhere else. Something happened recently that made me take a step back. I met someone at an open networking event who runs corporate training and is writing a textbook alongside it. What she needs is her course turned into per-module walkthrough videos - her own slides on screen, voiceover over the top, one video per module. I built it as ICM, because that's just how I build now. Numbered stage folders, one agent reading the right files at the right moment, markdown carrying the context, and local scripts doing all the mechanical work that never needed a model in the first place. Her voice cloned from a module she'd already recorded, the deck walked and exported as frames, one script and one audio file per slide. The durations of those audio files become the cue sheet that stitches the whole thing together, so there's no separate timing step to get wrong. One module's through it end to end. 21 slides, 21 scripts, 21 audio files, one finished MP4. And there's around ten hours of modules to put through the same pipeline. As an 18-year-old that's a really good opportunity, and it's going to generate me some serious income. I wouldn't have built any of it without what I picked up in here first, so thank you to everyone who's answered a question of mine along the way. Nothing's finished yet. I've still got a lot to come and plenty I haven't cracked. It just felt worth stopping on rather than quietly getting on with the next thing.

As some of you know I have been working on a few modules for the classroom WELCOME TO THE WISE ARCHITECTS CORNER - THE LEGENDS · Clief Notes For a while now the sign on the door read 👷 Coming Soon 🚧 The First Rung Is Now Open Welcome. This is where we will demonstrate how AI works, where we build human-AI systems that last, and where the person at the keyboard stays the author of the whole thing. You do not need a technical background for any of it. You bring the curiosity, I bring the blueprints, and we build the understanding together. 🪜 Here is the climb This whole corner is one ladder, five rungs, and each rung raises what you can do with the machine: (1) Prompt engineering, talking to the model (2) Context engineering, giving it what it needs (3) Memory engineering, making it remember (4) Loop engineering, making it check its own work and then repeat (5) Graph engineering, running a whole system of them, with you in the chair You walk in asking "how do I even talk to this thing?" and you walk out running a system of them. That is the journey, and the top of this ladder is a system of machines, the bottom is one sentence, and the bottom is open today. 📚 What is open today The whole first rung, Prompt Engineering, all six posts: the Series 1 Overview, three classes, the payoff with its quick card, and my perspective on the rung everybody says is dead. 📆 A few things before you start One series a week. Rung two lands next week, rung three the week after, and this corner is going to grow fast, five weeks to the top. Follow these modules in order. You will find that each rung stands on the one below it, the second assumes you took the first, the third assumes you took the second, and the path only works if YOU climb from the bottom. Start at the map. The Start Here post shows you how every series in this corner runs and points you to the first door, the Series 1 Overview. Do not skip it (I know, you want the techniques, they are one door further and they are not going anywhere, the map is a short read, and it saves you a whole series of wondering where you are).

A founder asked me a question this week that I couldn't answer on the spot: do other businesses have a system like this? So I went and looked. Short version: outside this room, I can't find them. Everyone here runs some version of it already, a folder of markdown that Claude reads and maintains, and I'd stopped noticing how unusual that is. I'd like the room to tell me where the others are hiding, or whether we're further ahead than we think. The system in question is the one I've been installing at a three-person shop since August. The part that's now real: a knowledge base in a git repo that their own Claude reads before it does any work, a file register that watches their Drive and logs every arrival and every move, and a pitch engine that runs a brief through four human approval gates with the gaps written on the slide. Every filing carries who approved it or which rule filed it. Every page carries where it came from. When something ends up in the wrong place, the record says whether a person put it there or our rule did. None of the pieces are exotic. Markdown, git, a spreadsheet, an Apps Script, skills. What's different is that the knowledge is compiled and maintained, not retrieved. The agent doesn't search a pile of PDFs every time. It reads pages it helped write, with the provenance on them, and the rules for what it may and may not do live in the same repo. Here's what I found when I went looking for who else does this. The big holding companies in that industry have "operating systems" now. Real ones, sold to clients as the reason to hire the group. That's a data platform with agents on it, top down, owned by the group. Not a thing three people could own. Everyone in the middle has AI on top of files. The numbers from this year's surveys: about two thirds of agencies run brief generation in production, a third draft client reports with it, and the single biggest problem the independents report is getting AI into their actual workflows. Every "AI knowledge base" guide I read describes the same thing. Search over the shared drive. A memory server. Chat with your documents. Useful. Also not a record of anything.