Apparently “I’ll clean up a few lessons” turned into rebuilding a whole module 😂 The classroom is now called AI Animations & Workflows, and Module 1 has seven new videos, eight connected lessons, and a clearer route from your first idea to a finished animation. I made this because I want you to be able to build a workflow you can keep using. Take an idea, give it a home in a folder, and have your AI help write the script, make the voice, plan the visuals, build the scene and export the video. The AI can do a lot of that work. Understanding what each stage produces helps you ask for useful changes and check whether the result actually explains your idea, right? We follow one small example through the lessons, then you use the same process for something of your own. The videos also use a new style: more visual explanations, app views, moving diagrams and examples that connect directly to what’s being said. Start with 1.1: Welcome and Your Route Through This Module, then work through: - 1.2 How This Video Was Made — see the whole process before setting things up. - 1.3 Get the Workspace Ready with Your AI — choose your starting route and prepare your project. - 1.4 Ask for a Script, Then Make the Voice — turn the idea into a spoken explanation. - 1.5 Turn the Voice into a Visual Plan — decide what someone should see as they listen. - 1.6 Let AI Build the Scene — build the pictures and review whether they help. - 1.7 Fix What You See, Then Export — make a specific correction and check the finished video. - 1.8 Make the Next Video with Your Own Idea — carry the useful tools and instructions into your own project. -

First post here, so be gentle, lol. I'm having a hard time wrapping my perception about what kind of data you can, or should put into yours for your AI memory. I've been messing around with computers and by extension data manipulation, since the 70s. I have a good understanding of how a relationship database runs. But we're not building that kind of ecosystem(?) are we? We can go bigger. Before I dug deeper, I always picture an LLM like Chatgpt, as having this huge massive brain, which held all of the Internet, and when I asked would wave it's virtual hands to say "Here it is". I know that's incorrect. I'm using AI as a research assistant and junior co-writer. I'm doing a non-fiction book what kind of skills you'll need to make money in the next 20 years. I'm doing a ton of digging for trends and possibilities and...all of you have a good idea of what that means, I'm sure. I went into this thinking it would be more like a Wiki compiled form all my research and conclusions but is that what I want? Seems like there so much more than just a glorified book list. I do want to have a folder style system, with the full transcripts, complete articles, or other important documentation that I need. That's doable too. But recently, I wanted to start at least collecting the base data. If I don't start doing that, I'm just digging my hole deeper. So I laid down a basic schema, and then asked GPT to pull me 5-6 highlights that it thought should go into the database. Once I get the workflow built, I pretty sure I'll try to automate it, so as I research, the AI formats and stores any highlighted data I come across. It pulled those six, then another three from our discussions on the first six, and we were in a side chat at the time, the main chat was on markdown files. We got 10 entries from that. So I had nineteen. I haven't done any more, but when I look at what I have, I get this weird vibe that the majority of them aren't on the book subject, but are more of how the LLM views the way I work? That's a poor description of it, I hope it works.

I am pulling records about the same people out of a few different systems into one folder, so an agent can actually work with them. The merging is not the hard part. The hard part is that the same person shows up three times, slightly differently, and every system is convinced it is the right one. Phone written four ways. Name spelled two ways. One system has the newest email, another has the newest address, and the one with the better data is not the same one twice in a row. Right now I pick a winner per field instead of per record, and I keep the losing values in the same file so nothing disappears quietly. It works. But the file keeps getting fatter, and I am not sure fat but traceable is the right trade for something an agent reads on every request. For anyone whose folder is fed by more than one system: do you settle the conflict once on the way in, or keep both versions and let whatever reads the file choose at the time? And what happens on the day one of those systems changes its mind about a person you had already settled?

Hey Clief Notes fam! 👋 I'm Joseph and I'm stoked to be here. 🙋 A little about me: A DevOps Engineer based in Munich. 🎯 My current goal: Improving my understanding of ICM and AI. 💪 What I'm currently building/working on: Various personal projects and consultations 🤔 My biggest struggle or question right now: Am I using ICM properly for my project? Let's get it! 🚀

I was thinking a lot about a post from @Carla Bosteder (Using AI without losing YOUR voice) from a few days ago and I came to a conclusion that I rely too heavily on AI to write for me. Yes, AI has some training on how I think and how I write. Yes, I dictate my thoughts to AI to generate the copy I want to write. But this is not the same. Somehow the soul of the communication is lost. I started noticing this more and more in this community. The tell-tell signs of AI generated text. It makes me stop reading and just feed the post to AI to summarize it for me. I was never a great writer. I managed to get As and Bs on composition papers in college. Some people have a gift and can write well, just like some people have a gift with art or music. For me it was always a process of writing, re-writing, editing. I do not have the time for that now, so what do I do if I want to preserve my soul in my work? I would love to join a community that focuses just on that. How to use AI as a tool when writing and not a text generator. Use the AI more like a secretary back in the age before office computers. Use the AI more like an editor that enhances and clarifies writing, and not like a soulless generator. There have to be methods and strategies from the past we can apply in the AI age. I am not the person to uncover those "ancient" methods, but I sure would like to learn from people that do. In the meantime I will dust off my copy of "The Elements of Style" by Strunk & White as I feel that writing style may be just perfect for the AI Era. P.S. No AI was used to generate this message.