(and a small change to how we run these) Hello everyone!! 👋 First, the honest bit. This one is landing later than Monday, and on purpose. Two things got us here. One, a lot more of you are submitting now. If I am going to really sit with every entry and give it a proper look, a weekend is not enough. This round I went through all of them, watched the videos, opened the repos, the full pass. That takes time and I would rather do it right than rush it. Two, I could feel a few of you running hot. Weekly is a sprint, and burnout was starting to creep in for some. So we are moving to bi-weekly. More room to build, more room to breathe, and the time for me to actually review the work the way it deserves. 🎥 Quick word on the videos. They were a step up this round. Some of the animated walkthroughs and live demos were a genuine pleasure to watch, and yes, I weigh them. A clean demo that shows the thing actually working makes a real difference. However I don't want that to ALWAYS be a requirement. Also you will notice the Heavy hitters that you usually see up here are not currently, some posted late and I decided to let the new entries and first timers also have a chance as well! But certainly, check the original post as every submission has something for you to learn from : 💰 Competition 7 ➖➖➖ 🛠️ A FEW THAT STOOD OUT (in no order, and if you didn't make it, it doesn't mean yours wasn't great) The Pipeline Operator — @Jayden Forshee Runs a whole sales pipeline. Paste a lead and it grades it, writes the outreach, and moves the card itself. The live board where you watch cards move on their own, sat right next to a normal chatbot, was one of the clearest ways anyone has shown what an operator actually is. https://github.com/griffainai/studio-pipeline-operator Board: https://pipeline-operator.vercel.app/board

Personally. No I don't think they did, I think the researchers are discovering what I did already ! And I'm happy they are. I would love if you all could comment, share or tag Google in this though as I would love to work with them ! Video below. https://cloud.google.com/blog/products/data-analytics/how-the-open-knowledge-format-can-improve-data-sharing

This will tell you a lot about the future and the way I think, give it a read if you have time. https://jakevanclief.substack.com/p/the-machine-is-smart

This post is not for the ICM pro, there will be no talk of gates, scripts, or orchestration! This is for the person just starting out! @Karli Rosario Yes, I mean you! (And anyone else who may just be starting out with ICM) Seriously, I'm glad you found ICM. Let me give you the simplest version of it I know. ICM is a system of structured folders. Yes, the same folders you have been using on a computer for most of your life. The ones you stored photos in, & pirated music from Napster and LimeWire. That's it. I will take you through the process below. When working with AI, a lot of people are doing this 👇 You take a long prompt, feed the entire thing to AI at the beginning of your interaction, and spend time going back and forth with AI trying to get the outcome you want. (I'm not coming for you Karli, you are exceptionally good at this, but ICM will make your outcomes exceptionally better!) What is different about AI and prompting with ICM 👇 You take that same really long prompt and instead of giving it to the AI all at once in the beginning, you break it into steps, and each step gets its own folder, each folder gets its own piece of your large prompt, just 1 step from it, and you ordered the folders by when the steps happen in the workflow. You got it? Good 😊 ❤️‍🔥 -------------------Still a bit unclear, let's bake a cake. 💡 Here's an analogy I have success with (I picked this up way back in my VB programming days): Imagine teaching AI to bake a birthday cake. 🎂 The way most people do it: 👇 One giant prompt. "Bake a cake, here's the recipe, the frosting technique, the decorating style, the candle placement..." Then they hit enter and wait. The AI is juggling 40 instructions at once, and by step 30 it's forgotten step 3. The ICM way: 👇 Break the prompt/workflow into steps. Each step gets a folder. The first folder is your first step. Then you point the AI at the first step, and the first step is 00-birthday-cake: (Point the AI just means giving access to the folders to the AI, through uploading or direct local access, don't worry about that now, let's keep building our cake.)

Fable made me start using Codex. Well, actually Claude, Codex, Kimi and MiniMax M3 together. Not because Fable is weak. Because it is the first model strong enough to run the others properly. The shift: stop asking which model is best. Start matrixing every model to the task it performs best at. - Claude (Fable): the seat. Orchestration, judgement, context. - Codex: the coding powerhouse. - Kimi: long-video understanding. - MiniMax M3: the looping build system. For the first time the multi-model workflow is truly effortless. Local models included. It all just works. The model at the top is not doing the work. It is routing it. All of it, loops included, lands in an ARI-OS update. The intelligence is the routing, not any single model. Read the deep-dive: https://aris-space.com/documents/workflows/fable-made-me-start-using-codex [[EDIT]] I wanted to just clarify what I said of in this post by saying that the infrastructure I've built with Fable and the way that it can solve problems when you give it a tight brief and the thoroughness of the model allowed me to create a seamless system. But ultimately, every step of this has been tiered with the model we had. //A<3