Most people overcomplicate Instagram automation… and that’s exactly why they don’t stay consistent. The truth is, you don’t need 10 tools or some crazy setup. You only need 3 things: 1. Content that’s easy to produce (AI can help you with this) 2. A simple scheduler so you’re not posting manually every day 3. A way to respond faster (DM/comment automation but keep it human) That’s it. Automation isn’t about removing yourself…It’s about removing friction so you can actually show up consistently. The people winning right now aren’t fully automated they’re just smart with their time. If you had to pick one thing slowing you down right now… Is it content, posting, or engagement?

TL;DR: open-source desktop dictation app that sits next to every AI chat window you have open. Local Whisper for speech-to-text. Wake-word listening so you don't even click. Optional AI parse via Ollama, OpenAI, or Anthropic. MIT, free, no telemetry. 🔗 GitHub: https://github.com/Agenius-AI-Labs/agenius-note 🔗 PyPI: pip install agenius-note 🔗 Walkthrough video: https://youtu.be/OAcrm0wZd6Y The problem it solves I usually have three Claude windows, a VS Code Claude session, ChatGPT, and a local Ollama open at the same time. Every prompt I type is a context-switch tax. The Whisper-based dictation built into macOS / Windows works but lives in the OS chrome, not next to my chats. Claude Desktop has voice but it's tied to Claude. I wanted one mic for everything. What it does 🎙 Push-to-talk dictation, or hands-free wake word (default "hey jarvis", train your own .onnx in the openWakeWord Colab notebook) 🧠 Pipes the transcript to your LLM of choice for a structured note/task parse. Or skip the LLM and just take raw transcripts ✅ Quick todos pane on the right ("hey jarvis, remind me to walk the dogs in an hour" routes straight in) 📋 Quick Note brain-dump panel. Talk a thought through, hit Copy, paste into your next prompt. Nothing stored 🔐 API keys live in OS keyring (Keychain / Credential Manager / Secret Service). No plaintext on disk Stack PySide6, faster-whisper (CUDA float16 with CPU fallback), openWakeWord, SQLite, Ollama / OpenAI / Anthropic. ~5K LOC. MIT license. It runs everywhere Windows, macOS, Linux. Pre-built bundles on the GitHub Releases page (SmartScreen and Gatekeeper will yell on first launch, we're not code-signed yet). Or pip install agenius-note if you have Python 3.10+. What I'd love feedback on - What wake word would you train (mine is going to be "hey biggie" once I get around to it) - Which LLM backend feels best for your workflow - What's missing (next on my list: a chat panel inside Quick Note so I can ask the AI things without leaving the app)