🔍 Three things to notice. 👇 1️⃣ Numbered folders set the execution order, so 01- always runs before 02-. 2️⃣ Each stage carries its own CONTEXT.MD, references/, and output/. 3️⃣ The handoff between stages is dead simple. Stage 1's output/ is what stage 2 reads as input. ================== 📂 The folder structure workspace/ -------------------------------------------# the whole operation CLAUDE.md ------------------------------------------# L0: orientation, "where am I?" (always loaded) CONTEXT.md --------------------------------------- # L1: the map, "where do I go next?" stages/ ------------------------------------------------ # all the steps in order 01-research/ ---------------------------------------- # step 1: gather the source material CONTEXT.md ---------------------------------------# today's job description references/ ------------------------------------------# rules for this step output/ -------------------------------------------------# what this step produced 02-script/ -------------------------------------------- # step 2: turn research into a draft CONTEXT.md -------------------------------------- # today's job description references/ ----------------------------------------- # voice rules, examples output/ ----------------------------------------------- # the draft lives here 03-production/ ------------------------------------# step 3: ship the final artifact CONTEXT.md ------------------------------------- # today's job description references/ -----------------------------------------# design system, build conventions output/ ----------------------------------------------- # the finished product _config/ -----------------------------------------------# L3: brand, voice, design (configured during setup) shared/ ----------------------------------------------- # L3: assets every stage might use skills/ -------------------------------------------------- # L3: bundled skills the agent can call setup/ --------------------------------------------------# first-time configuration

Is anyone else building local memory systems and how would you know if your AI's memory system silently broke? My Local Memory system failed for three sessions before I noticed. Not loudly. No errors, no warnings. Claude still responded. Queries still returned results. Everything looked fine. What actually happened: the retrieval index I'd built (the thing Claude uses to remember what I know, what I've decided, what's in progress) had a corrupted cache file. JSON had gone invalid. Every query was silently returning degraded results. The model was answering from partial context and I had no idea. I found out because an answer felt slightly off. I went digging. The cache had been broken for days. That's the failure mode nobody talks about when you build on top of AI: the silent ones. I posted about the five-layer memory system back in May (here): CORTEX for structured state, PALACE for long-term memory, CORPUS for document retrieval, GRAPH for codebase navigation, INGEST for pipelines. That system is what broke. I'd built the memory layers but nothing watching the memory layers. A building with no facilities manager. Everything looked like it was running until the one piece holding it together quietly failed. The fix wasn't complicated. But it needed a different way of thinking about the setup. Buildings have a facilities manager. Someone who shows up before anyone else, checks that the systems are running, flags anything wrong, and routes incoming deliveries to the right desk, so the people doing the actual work never have to think about whether the infrastructure is functioning. That's what I built. Not a new AI. A facilities manager for the AI system I already had. The FM runs locally, at session start, every time. It's a small local model, Qwen3 running via Ollama, dispatched through a shell script. Costs nothing to run. Takes about 4 seconds. At every session start it checks six things: index file integrity, last sync completion, sync staleness, session log continuity, knowledge graph status, vector database currency.

Tell us three things: 1. What you do (job, industry, student, career-changer, whatever) 2. What brought you to Clief Notes 3. One thing you're trying to figure out right now related to computing or AI I'll respond to every single one. And read each other's intros too because the person who's stuck on the same problem as you might already be in this thread. I'll go first I am Jake, I have been working in tech for 15 Years, building with Generative AI for 3 Years straight now! Excited to teach and learn! That's it. Simple, scannable, gives you data on who's joining and what they need, and keeps the feed clear for content that retains people past week one.

We talk about folders all day, but the folders are FOR something. I want to know what... 🎖️Bonus points: comment with the single most painful manual process in your industry. The best comp entries come from exactly those answers.

We're not experts in every field and sometimes you just don't know what you don't know. I've been working on a project for a business idea and based on a lot of hate I've seen in social media directed towards vibe coders I've taken note of things I might miss in my development. However, by following ICM I've noticed how easy it has been for me to develop my app and then pause and ask claude to help me design what I call a new persona to work on a very specific task. Latest example of this was me telling claude that I am worried someone might find vulnerabilities or back doors in my app and exploit those to get access to my API or supabase or whatever. By describing my concerns and what type of solution I was looking for Claude came up with a Claude.md and Context.md files for a pentest persona. Put those in a folder in my project and now whenever I want to do any type of test like that I just ask for it to do it!. I've done this and now I have, business owners, software auditors, legal advisors, pentester, VC Investors, Branding specialists and some others in my workflow. It just comes to show how incredibly flexible and repeatable this methodology is.