Most useful answers in a community disappear into the feed. Someone solves a hard problem today. A month later, the same question returns because the answer was never turned into something durable. The community keeps paying the cost of rediscovery. That is why I built LLM Wiki: a simple shared memory for AI agents. Instead of saving every conversation, it keeps the knowledge worth reusing: 1. Save a useful article, transcript, note, or exported community thread. 2. Let the agent compile it into linked Markdown pages. 3. Ask a question later and retrieve the right section with evidence. 4. File useful conclusions back so the next answer starts from what the community already learned. This is useful for recurring questions, research libraries, customer conversations, project decisions, and any topic a group explores over time. LLM Wiki v2 improves how that memory is searched: - exact section search finds names, flags, and phrases - optional semantic search finds paraphrased ideas - reciprocal rank fusion combines both result lists - citations and source metadata show where an answer came from Cerebras recently published a detailed article about its internal knowledge base. Employees ask it more than 15,000 questions a day, according to the team. Their system is enterprise-scale, but the need is universal: information is scattered, and good answers should not have to be rebuilt every time. No embedding service is required. The default is local, Markdown-first, and dependency-free. The clever parts are optional; the knowledge stays readable. Open-source project: https://github.com/praneybehl/llm-wiki-plugin Cerebras article: https://www.cerebras.ai/blog/how-we-built-our-knowledge-base What valuable answer in this community keeps getting rediscovered?

Looking for the course i bought a while ago. as i need to revisiit to fix somethings on that. how can i access that course and go back through it?

Not sure if this is the right place to be posting this, so please move if it needs to be. Frame looks to be forcing th V4 update on everyone, but I know there were issues with the KEDB Extreme last year moving it from v3 to v4. What's the best course of action to take at the moment with it? Any help would be appreciated (Screenshot of email attached) Thank You :)

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The NCA-toolkit node in my n8n automation stopped working recently The Job logs are saying I'm missing these variables: - GCP_JOB_PATH - GCP_JOB_PAYLOAD I'm assuming this is related to the recent update of the NCA Toolkit repo, since cloud run is pulling the latest image I'm no expert so doing my best to connect the dots... anyone have some insight on this? Thank you UPDATE: I forked the repo and then connected it to my service, then built and deployed. My source is now a 'repository', rather than a 'container'. I then recreated my Job in us-central1... seems there's some hard code in the nca image that looks for a Job there and I couldn't override it with variables After those 2 changes it worked