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I track my recovery daily—mood, energy, focus, activities, medications, and reflections—but typing everything out never lasted more than a few days. So I built a voice-first pipeline: I talk, and it automatically becomes a clean, organized Google Sheet. Step-by-step: 1. I built a free iPhone Shortcut that records my voice when I say, “Hey Siri, Log,” and sends it to the Gemini endpoint. 2. Gemini transcribes the audio and extracts structured details, including wake time; mood, energy, and focus scores; activities with categories and durations; medications; and reflections. 3. Everything is automatically organized in the appropriate place in a Google Sheet: a daily summary, activity log, metrics log, medications log, and clean, human-readable digest for each day. 4. I can say “yesterday” or “on Monday” to log something I forgot, and it files the entry under the correct date. 5. I connected the completed sheet to a separate AI chat scoped specifically to reflection, so I can ask questions such as how my exercise correlates with my mood or how my energy trends over the month. The best part is that the entire workflow runs on free tiers—Google Sheets, Apps Script, iPhone Shortcuts, and Gemini’s free API tier—so there’s zero cost to build or run it. The result is a daily tracker that takes seconds to update from anywhere, requires no typing, and turns my entries into a dataset I can actually learn from—all without writing a traditional app.

I changed my iPhone’s Action Button from mute/unmute to a menu of shortcuts. When I press it, I can select a shortcut I created called “Expense AI.” Expense AI records my voice, appends the transcript to a prompt, and sends it to ChatGPT. ChatGPT returns a JSON object containing the time, amount, expense description, payment method, and category. The data is then saved to a live Google Sheet. Step-by-step: 1. I changed the iPhone Action Button to display a menu of shortcuts instead of controlling mute/unmute. 2. I selected the “Expense AI” shortcut from that menu. 3. Expense AI recorded my voice and appended the transcript to a prompt. 4. It sent the prompt to ChatGPT, which returned JSON with the time, amount, expense description, payment method, and category. 5. The resulting data was saved to my live Google Sheet.