I have a Quick Notes topic in Telegram. It is the nearest thing my personal system has to an input box: send a sentence from my phone and let the machinery put it somewhere useful. The first version was efficient in the way a paper shredder is efficient. It could turn a message into a calendar entry or task, but it did not understand that a thought, a reference, a question, and a commitment are different things. ...
Most notification systems do not have an information problem. They have a presentation problem. The email system had already done the hard work. In an earlier post, I described the scoring pipeline that separates mail needing an immediate alert from messages that can wait for the evening summary or a later review. More recently, I wrote about removing recurring junk at the source, rather than merely teaching the filter to tolerate it. ...
My garden CCTV system started with a simple loop: Frigate detects movement, a Python script sends a Telegram notification, and I can look at a snapshot or short clip from my phone. That was good enough for real-time alerts. It was not good enough for history. Telegram is a terrible archive browser. It is excellent at interrupting me when something happens, but bad at answering questions like: What happened in the last two hours? Did I miss a person detection yesterday? Which clips exist for this camera? Can I open the full event without digging through chat history? So the next small project was obvious: keep Telegram as the notification surface, but build a proper CCTV history portal on the Raspberry Pi itself. ...
In my previous post I connected a Raspberry Pi 5 to my AI assistant as a remote node. The natural next step: attach a camera and turn it into a proper garden security system — motion-activated, AI-powered, with notifications straight to Telegram. This post documents what I built: Frigate NVR running on the Pi 5, a Freenove 8MP camera module, automated clip retention, and a Python bot that sends snapshots to a private Telegram channel the moment something moves. ...
I’ve been running OpenClaw as my personal AI assistant for a few months now — mostly typing to it. Yesterday I added voice, and it changes the dynamic completely. The setup: 20 minutes, free tier The whole thing runs on ElevenLabs for text-to-speech. The free tier is genuinely enough — you get a generous monthly character allowance, plenty for daily conversational use. Setup steps: Create a free account at elevenlabs.io Grab your API key from the profile settings Add it to your OpenClaw config: "talk": { "provider": "elevenlabs", "providers": { "elevenlabs": { "apiKey": "YOUR_API_KEY_HERE" } } } That’s it. Restart the gateway and voice is live. ...
Most AI assistants start fresh each session. They read their instructions, follow them, then forget everything. Mine doesn’t. It maintains its own documentation, reviews it daily, and proposes improvements. The Core Idea My AI assistant (ClawdBot) wakes up each session by reading workspace files: AGENTS.md – its operating instructions SOUL.md – personality and voice USER.md – who I am, what I prefer TOOLS.md – local configuration (Telegram topic IDs, RSS feeds, routing rules) MEMORY.md – long-term memory memory/YYYY-MM-DD.md – daily logs These files evolve. When I say “remember this,” it updates them. When it learns something, it writes it down. ...