Hey everyone 👋 I’m currently building a personal AI system around my university workflow and wanted to get some opinions from people who’ve done similar things. Right now, I’m setting up an Obsidian vault where I store all my uni-related data (assignments, files, notes, requirements, etc.). The goal is to later use something like Claude Cowork as a kind of “AI assistant” that can: - handle assignments - help with bigger projects - support exam prep Since I don’t have API/admin access to my university system (Moodle), I can’t automate data collection directly. So I’m focusing on building a good input pipeline instead. My current idea is: 1. use a Telegram bot as a quick input (send files, notes, voice, etc.) 2. process everything through n8n (detect type, transcribe, etc.) 3. then store it in Obsidian, where AI can later work with it Main question: Do you think it’s worth building this whole automation layer (Telegram + n8n + auto-classification), or would you keep it simpler and just upload things manually and let something like Claude Cowork handle organizing + structuring the data? Second question: Has anyone found practical ways to work around restricted Moodle APIs? In my case: - API access requires admin permissions - so I can’t use HTTP requests to fetch assignments or course data Are there any realistic alternatives here? (e.g. plugins, integrations, scraping approaches, etc. — nothing shady, just curious what’s possible) Would really appreciate any thoughts or experiences @Ryan Nolan, @Matt Payne 🙌

Need help integrating my n8n RAG agent with GoHighLevel live chat—want user messages to trigger my agent and send AI replies back. Anyone tried this setup?

My setup: OS: Windows Editor: Cursor IDE (with built-in terminal) Repo: A private GitHub repo I own Auth: I added an SSH key to my GitHub account Tool: I was using Claude Code on the web (the cloud-sandbox flavour of Claude Code, not the local CLI) What I'm trying to do: I asked Claude (in a Claude Code on the web session) to make some code changes for me. Claude did the work inside its cloud sandbox — it created a feature branch (let's call it fix/my-branch) and committed 4 file changes (commit hash 6af1c3f). I now want to: Get that commit onto my local clone of the repo. Push it to GitHub. Open a pull request. The complication: The Claude sandbox can't push to GitHub itself — it doesn't have my GitHub credentials. So Claude exported the change as a git format-patch output (a 559-line .patch block starting with From 6af1c3f3510915db259d531333f46adc8a9abf5c Mon Sep 17 00:00:00 2001) and told me to apply it locally with git am drift.patch. What I tried: On my local Windows machine in Cursor's terminal: cd <repo> git checkout main git checkout -b fix/my-branch git push -u origin fix/my-branch Output of the push: branch 'fix/my-branch' set up to track 'origin/fix/my-branch'. Everything up-to-date Then I went to GitHub to open the PR. GitHub shows: "There isn't anything to compare. main and fix/my-branch are identical. Showing 0 changed files with 0 additions and 0 deletions." Diagnosis (I think): The branch exists on GitHub but points at the same commit as main. I created a new empty branch, pushed it, but never actually applied the patch that contains commit 6af1c3f. So my local branch and the remote branch are both empty relative to main. I think what I need to do is: Save Claude's .patch output as a file on my local disk. Run git am drift.patch to land commit 6af1c3f on my current branch. git push again. But I'm new to git am and patch files, and I'm worried about: Line endings: I'm on Windows. The patch was generated on a Linux sandbox. If I paste it into Notepad or Cursor and save, will CRLF vs LF mess up git am?

Has anyone built an AI agent that utilizes tool calling with n8n? For example: An organization has different branches, and each branch has its own APIs for specific tasks (e.g., calculations, cashback). You use the n8n HTTP Request node and define rules so the AI knows exactly which function to call and also when to use the API response from one request to make another HTTP request and give answers to "questions". I built something like this with Python, LangChain, and Flask, but I'd love to see how people are doing it natively in n8n!

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