Most people assume AI has a huge storage memory that keeps everything you tell it… But the reality is very different 👇 AI doesn’t “store” information like a phone or a database. It works through a temporary context window. Meaning: It only understands what is present in the current conversation Once the session ends, it doesn’t automatically retain all details Long-term memory only exists if an external system is built around it 📌 So AI is not a “storage system” It is a moment-to-moment reasoning system The key difference: Storage = permanent retention Context = temporary understanding based on what’s currently available 💡 This is why real AI systems don’t rely on AI alone— they combine external memory + rules + continuous context management Question for the community: Have you been treating AI as a “memory system” or a “context system”? 🤔 #AI Email Agent (9/20/24) @Nate Herk

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I always assumed tools like Claude Cowork were the next step. But after talking with a few builders here, I realized a lot of experienced people are building their own AI workspaces instead. One setup that caught my attention was using Claude Code with an Obsidian vault and local scripts to organize knowledge and automate development workflows. I'm still learning Cowork and rebuilding examples while making videos about what I learn. But now I'm curious to explore this side too. Feels like the real skill isn't learning one AI tool. It's learning how to connect them together. Has anyone else built around Obsidian or a similar knowledge system?

Everyone's talking about loop engineering. Here's what it actually is. It's not the ReAct loop your agent already runs (reason, act, observe, repeat). That ships built in. You don't engineer that. Loop engineering is everything wrapped around the agent: what kicks it off, what feeds it work, what checks the output, what decides to run again or stop. The agent owns the inner loop. You design the outer one. Core idea: the prompt is no longer the unit of work, the loop is. Give it a goal and a success condition, and it keeps taking turns until that condition holds. Codex and Claude Code already ship this natively as /goal. It also sidesteps context rot. Instead of one long session piling up dead ends, each iteration starts fresh, reads state, does one unit of work, exits. The catch is tokens. Loops burn them on every retry and re-read, so cap it before trusting it to run overnight. Is anyone here already building with loops instead of turn by turn prompting?

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