Lost an SSH session? Power outage? Agent context gone? Magpie Search can search conversation history, identify the exact dropped session, and recover what background tasks were still running. https://github.com/xfloukiex-lab/magpie-search

Am I the only person struggling how I should get started after creating my folder structure?

1. Watch the intro video and introduce yourself in the intro post here 2. Start with The Foundation (free course). Concepts, folder architecture, prompting framework. Everything else builds on this. 3. Check in at the bottom of each lesson. Polls, discussion posts, other members working through the same stuff. Use them. 4. When you're ready to build real things, move to Implementation Playbooks (Level 2). When you're ready to build your own tools, Building Your Stack (Level 3). 5. Post your work. Ask questions. Help others when you can. What are you here to build?

Ever had your computer reboot on you, or a power outage hit mid-session? Every thread your agent/llm was holding... gone, Now you have the tool to get it back. Well you can thank me later while you dive in your next vibe coded project without worry. Never forget what your agent/llm lost again. I introduce Magpie-search, Magpie indexes everything your AI has ever worked through, locally, so a crash is a hiccup instead of amnesia. And that's not it, the amount of tokens is saves on a deep websearch is insane!. What Magpie-search is A normal search engine looks in one place. Magpie takes one question and fans it across everything that matters at once — the AI's entire conversation history, the files on the machine, a structured knowledge graph, a vector store, the live web, even YouTube — and pulls the answer back from wherever it actually lives. Six sources, one call. And I would like to say thank you! jake van clief this wouldn't have been possible without the knowledge you provided. Yall go check out the repo for more information https://github.com/xfloukiex-lab/magpie-search

Search finds. It never reads. Every "AI that knows your stuff" runs the same trick: embed the material, grab the paragraph nearest your question, bluff the rest. For easy questions the bluff holds. For the ones that matter, it doesn't. So I'm building the missing layer. Call it a reading swarm. Instead of paying one expensive model to read a whole mountain, I cut the corpus into slices and send a swarm of cheap workers, one per slice. Each reads its slice properly and hands back a single finding. A deterministic harness merges them into one verdict. The expensive model only steps in if I ask it to sharpen the final call. Not shipped yet. Still smoke-testing the edges, and I read every verdict myself. But the law already holds: finding isn't comprehending, and comprehension doesn't need a bigger brain. It needs more cheap eyes, one slice each. What's the biggest pile of material you wish your AI actually read, not skimmed? //A<3