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I quickly capture my thoughts in Apple Notes, which serves as my mobile inbox. A scheduled Claude Cowork skill reads those notes through the desktop connector on my MacBook and processes them into my calendar and Obsidian. I organize notes using either the “Forever Notes” method (https://www.myforevernotes.com/docs/journal) or a simple YYYYMMDD daily-note format. Time-log notes record a start time, end time, and description, then save that information to the calendar app. The calendar holds the raw data, which I can extract into a separate Excel sheet if necessary. Planned schedules are checked against existing calendar entries. If an entry is already present, it is highlighted; if it is missing, it is added. This saves me the time and effort of opening a link or editing multiple fields in the calendar app. Random thoughts are filed into my second brain in Obsidian. They are processed with templates, moved to specific folders, or intentionally tagged. Apple Notes, Obsidian, Apple Calendar, and Google Apps are free. The only subscription I need is a Claude account to use Claude Cowork. Step-by-step: 1. I capture thoughts and other information in Apple Notes on my mobile device. 2. A scheduled Claude Cowork skill reads the notes through the desktop connector on my MacBook. 3. I organize the notes using the “Forever Notes” method or a YYYYMMDD daily-note format. 4. I process time-log notes containing a start time, end time, and description, then save them to the calendar app. 5. I check planned schedules against existing calendar entries, highlighting entries that are already present and adding those that are missing. 6. I extract the calendar’s raw data into a separate Excel sheet if necessary. 7. I process random thoughts in Obsidian with templates, move them to specific folders, or intentionally tag them.

I've basically had the exact same haircut since high school, so this year I finally decided to experiment a bit with Nano Banana 2 and see what a different look might feel like. I uploaded my own portraits and started merging them with different models' hairstyles. After 10+ rounds of virtual makeovers, I found out that the hairstyle that suited me best was… my current one. Step-by-step: 1. I uploaded my own portrait photos to Nano Banana 2. 2. I gathered examples of different hairstyles I wanted to test. 3. I asked the model to merge each hairstyle with my portraits while keeping my identity recognizable. 4. I repeated the process for more than ten virtual makeovers. 5. I compared the results side by side and learned that my current haircut still suited me best.

I asked Claude to help me build a weekly and monthly habit tracker as an artifact. I prompted it to conduct a Q&A with me so it could understand everything I wanted to include. I also asked Claude to add an insights tab and provide tips for improving my own compliance. Step-by-step: 1. I asked Claude to build a weekly and monthly habit tracker as an artifact. 2. I prompted Claude to conduct a Q&A with me about the features and details I wanted included. 3. I asked Claude to add an insights tab. 4. I asked Claude to provide tips for improving my compliance with the habits.

I am 65 and recently retired, and I have been asking AI for advice to keep my plants alive. It tells me whether they need more or less water, more or less light, or soil amendments such as perlite or coconut.

I used the OpenAI Codex app to develop an idea I had while talking with my wife about power companies raising their prices during periods of high demand. We recently paid up to 90¢ per kW/h, which is insane, but when the kids hear “90¢,” they think it’s nothing. They don’t understand power pricing—or even what a kilowatt-hour is. https://kilowhat.jiovanie.com/ In about 15 minutes, I had a fully working web app that approximates how much power devices in your home use and how those costs add up over a month. You can see the cost of a single device or set up all the devices in your home, specify how long each one runs per day, and build a full monthly tally of power usage. The app also shows how a “small” 20¢ increase in the price per kW/h can add up to a massive bill at the end of the month. I designed it to be completely free to use, with no accounts or login required, no personal information collected, and zero tracking. My initial prompt was: ```text "I want to create an interesting, interactive, and maybe even FUN app that explains what kilowatthours are and how a small change in the price of a kW/h can have a huge effect on your monthly power bill. I want to make this tool available for free to anyone so it needs to work across devices and OSs and even form factors. I want it to be fun to use so it should have lots of style and flair and be very interactive. a price slider and device selector will enable people to see how much their devices draw power and how much it costs to use." ``` After the initial creation, I discussed the changes and tweaks I wanted, asked Codex to create a logo, and decided on a visual style. Then I provided my web-hosting information so it could upload the app and make it accessible to anyone. Step-by-step: 1. I described my idea about rising power prices and the need to explain kilowatt-hours and monthly costs. 2. I asked OpenAI Codex to create an interactive app with a price slider and device selector that would work across devices, operating systems, and form factors. 3. I discussed changes and tweaks, asked it to create a logo, and decided on the app’s visual style. 4. I provided my web-hosting information so Codex could upload the app and make it publicly accessible.

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.

For years, my family has run a shared birthday fund: five of us contribute a fixed amount for each birthday, while the person whose immediate family is celebrating that month is exempt from paying. Tracking everything in a payment app and a chat thread meant nobody knew the balance, who was behind, or what the next gift would cost. I rebuilt the fund as a small web app with Claude. The app itself isn't the only reason I'm writing this up. The same build is also the demo I use to teach clients and students how AI-assisted product development actually works, including the parts that go wrong. Step-by-step: 1. I described the real rules instead of presenting Claude with a generic app idea: the contributors, the fixed amount per person, the family-exemption rule, and birthdays with birth years so ages could be calculated automatically. Claude built the app as a single, self-contained HTML file with no build step or server, so it opens in any browser. 2. I worked in phases and asked Claude to explain its reasoning at each stage. Instead of using one giant prompt, I added one layer per session: the calculation engine, the setup screen, then reports and CSV export. The explanations made the sessions reusable as teaching material. 3. I required the app to be configured through its own interface rather than by editing code. This was the turning point. Claude removed the hardcoded demo family and added a full setup screen for the group name, contributors, deposits, birthdays, amounts, and alerts. I can now build a family from scratch live in front of a class in about [X] minutes without showing a line of code. 4. I let a data-loss incident shape the next phase. I entered the real family data, then the browser tab closed and the download link I had been using to open the file broke. The data was stored in browser storage tied to that exact URL, and I had no backup. Nothing was recoverable at the time. 5. I turned that failure into features. Claude added CSV export for both reports, CSV import that automatically detects which file it is reading, and a backup reminder that appears in the app's alert banner when the data has never been backed up or has not been backed up for seven days. We also discovered that birth year was missing from the export, which meant a re-import would have silently lost everyone's age. 6. I had Claude test its own work. Before each handoff, it ran a jsdom test suite in a sandbox. By the end, the suite had 46 tests covering the exemption math, empty states, CSV round-trips, and backup logic. Several real bugs surfaced there instead of in front of a class. 7. I made a second version for a different audience. One prompt produced a fully English, left-to-right translation with flipped directional CSS, Latin typography, US date formatting, dollars instead of shekels, and Venmo and Zelle instead of local payment apps. It was a genuinely different build, not a find-and-replace translation. The project took 14 sessions over one week and six hours total. It had no hosting cost, dependencies, or accounts. The data still lives in the browser's local storage on each device. Opening the file on my phone and laptop creates two unrelated pools, so CSV import is the manual bridge between them. There is no authentication or sync; this is a personal record-keeper, not shared infrastructure. The data-loss incident was not a Claude failure. I failed to build a backup path before entering real data. If I did it again, I would add export before adding a single feature. The highest-leverage prompt in the whole project was not a feature request. It was: "let me configure this through the interface instead of the code." That shift turned a static demo into something my family actually uses and my students can watch being built from an empty screen. The broader point is that the failure was the most useful part of the project. A polished demo teaches people that AI makes building easy. Losing the data and rebuilding the safety net around it teaches them what building actually involves—and that is the lesson that survives the workshop.

The available task apps don’t meet my needs, so I’m building a personal dashboard to manage my tasks from email.

If you have a large jar of pennies or other coins, spread them out and take a picture. Upload the picture to your AI app and ask it to identify any coins that may be valuable. This is much easier than checking them one by one. Step-by-step: 1. Spread the coins out so they are visible. 2. Take a picture of the coins. 3. Upload the picture to your AI app. 4. Ask the app to identify any coins that may be worth more than their face value. 5. Check the identified coins individually to verify their value.

I created an iPhone bookmark that looks and works like an app, using Claude. It includes massages, habits, and stretches targeting the shoulders, neck, jaw, and temples for when I feel a tension headache coming on. I took screenshots from a Gemini conversation about preventing and treating tension headaches, then uploaded them to Claude. I asked Fable to create a simple, accessible app I could use when I noticed my shoulders starting to rise or felt a headache coming on. Some stretches and massages include timers and tell me how many repetitions to do. It also reminds me to stop clenching my teeth and frowning while I’m working. Step-by-step: 1. I took screenshots from a Gemini conversation about preventing and treating tension headaches. 2. I uploaded the screenshots to Claude. 3. I asked Fable to create a simple, accessible app based on that information. 4. I saved the result as an iPhone bookmark that looks like an app. 5. I use the stretches, massages, and habits when I notice shoulder tension or a headache coming on. 6. I follow the built-in timers and repetition guidance, while using the reminders to stop clenching my teeth and frowning when I’m working.

I used ChatGPT Voice Mode to help me program my mom’s garage door keypad—and the most important step happened before I touched a single button. I photographed the labels on both the garage door opener and the wireless keypad. ChatGPT spotted the real problem: the previous homeowner had replaced the opener but kept the old, incompatible keypad. That explained why we couldn’t get them to pair. Once ChatGPT identified the exact models, it helped me find a replacement keypad that was compatible with the newer opener. I also had it find and load the instruction manuals for both devices, since pairing required a specific sequence of button presses across them. Before we started, I had ChatGPT explain the complete pairing process so I knew what to expect and where timing would matter. Then I set my phone on top of the ladder so both hands were free to work with the keypad and opener. I gave ChatGPT one important instruction: “Walk me through one step at a time. After each step, stop and wait until I tell you what happened.” ChatGPT gave me one instruction, paused, and waited while I reported what the lights were doing. Then it adjusted and gave me the next step. That let me follow the crucial sequence of button presses—and the timing between them—exactly. The real lesson: AI troubleshooting gets much better when you provide the exact model numbers and manuals, let it preview the process, and have it guide you through the work one confirmed step at a time. Step-by-step: 1. I photographed every model number on the garage door opener and wireless keypad. 2. I used ChatGPT to identify the models and determine that the previous homeowner had left an old, incompatible keypad paired with the newer opener. 3. I used ChatGPT to find a compatible replacement keypad instead of guessing based on appearance or brand alone. 4. I had ChatGPT find and load the instruction manuals for the new keypad and garage door opener. 5. I asked ChatGPT to preview the complete pairing sequence, including where timing would matter. 6. I placed my phone on top of the ladder so both hands were free to work with the keypad and opener. 7. I switched to Voice Mode and told ChatGPT to give me one step at a time, pausing after each step until I reported what happened. 8. I reported what the lights were doing after each instruction so ChatGPT could adjust and give me the next step.

Every Sunday night, my Openclaw asks me to recap my week and send it some photos I took. It makes a collage of the photos and generates a stylized "magazine cover" based on the recap. At the end of the year, I should have a neat collection of time capsules. Step-by-step: 1. I scheduled OpenClaw to prompt me every Sunday night for a recap of the week. 2. I wrote a short summary and sent the photos I had taken during the week. 3. I had it arrange the photos into a collage. 4. I asked it to generate a stylized magazine cover inspired by the recap. 5. I saved each weekly cover so the collection can become a set of time capsules at the end of the year.

I’ve found it useful to use Claude while reading nonfiction books, such as *Factfulness* by Rosling. I ask Claude for a synopsis of the book and save the result as a PDF on my computer for future reference. I also ask Claude to quiz me about the book, either with multiple-choice questions or in short-answer format, to test whether I’ve fully understood what I’ve read. In an ongoing conversation, Claude can also relate the current book to other books I’ve recently read and provide additional synopses. Step-by-step: 1. I tell Claude which nonfiction book I’m reading, such as *Factfulness* by Rosling. 2. I ask Claude to create a synopsis of the book. 3. I save the synopsis as a PDF on my computer for future reference. 4. I ask Claude to quiz me using either multiple-choice or short-answer questions. 5. I continue the conversation so Claude can relate the book to other books I’ve recently read and provide further synopses.

My girlfriend has a professional camera and lens for photographing birds. Because the camera captures an enormous number of images per second, sorting through them and keeping only the good ones after a day at the wetlands took a very long time. She showed me the two tools she was using to tag, crop, view, and zoom into photos, inspect focal points, and view the color histogram. I decided to vibe-code a C# tool using Cursor, Grok, and Claude Opus. The tool reads the EXIF and MakerNotes metadata in each picture and lets her scroll through all the photos in fullscreen with the mouse. It displays the histogram in the top-right corner and useful information—aperture, shutter speed, focal length in millimeters, and ISO—in the top-left, with color coding from red to green. It also shows the Nikon focus zone. Clicking the left mouse button zooms to 75%, allowing us to pan, while clicking the right mouse button zooms to 100%. Once we decide visually on the best crop and judge the photo’s potential, pressing a keyboard key instantly crops the image at the current view, saves a copy, tags the photo, and adds her copyright in the bottom-right corner. This makes the process much faster because she can view, tag, crop, and add copyright at the same time. It took about two hours of working with her to iterate on the tool and find the right balance of features and ease of use. Step-by-step: 1. I observed the two tools she was using to tag, crop, view, and inspect bird photographs. 2. I used Cursor, Grok, and Claude Opus to vibe-code a C# application for her workflow. 3. I made the tool read each photo’s EXIF and MakerNotes metadata. 4. I added fullscreen mouse scrolling, a histogram in the top-right, and camera information in the top-left, including aperture, shutter speed, focal length, and ISO. 5. I added red-to-green color coding and a display of the Nikon focus zone. 6. I set up left-click zoom to 75% with panning and right-click zoom to 100%. 7. I added a keyboard shortcut that crops the image at the current view, saves a copy, tags the photo, and adds her copyright in the bottom-right corner. 8. I iterated on the tool with her for about two hours until the features and ease of use were balanced for her needs.

I've been taking topics I want to learn about (mostly coding docs for new technologies) and giving them to NotebookLM to create customized podcasts for my runs when there aren't interesting podcasts available from the channels I frequent. And it really is actually good and enjoyable, and not just AI slop. Step-by-step: 1. I chose a technical topic I wanted to learn and gathered the most useful documentation for it. 2. I added those sources to NotebookLM instead of relying on a generic podcast. 3. I asked NotebookLM to create a customized audio overview from the material. 4. I listened to the generated episode while running. 5. I repeated the workflow whenever I wanted an engaging podcast for a topic that existing shows had not covered.

Every RSVP tool I found wanted a monthly subscription to collect a few hundred yes-or-no answers, and none would return my data in a format I could use. So I built my own with Claude Code. The RSVP system is small: a form deployed on Vercel and embedded into our wedding website. We also emailed the direct link because plenty of guests might never visit the site. The form asks for more than a yes-or-no response. It collects meal choices, dietary restrictions, and plus-ones. Every submission adds a row to a Google Sheet through the Sheets API. That sheet ended up mattering more than the app. Months later, when it was time to create the seating chart, every guest was already represented in clean, structured rows that I could give to a completely different tool. For seating, I opened the same sheet in Claude and wrote out the rules in plain English: who had to sit together, who could not sit anywhere near each other, which relatives needed a quiet corner, and which friends could anchor a table of people who did not know anyone else. Claude produced a first draft that respected those constraints, along with an interactive board where I could drag people between tables. Step-by-step: 1. Tell Claude Code which fields you want on the RSVP form and have it build the front end and back end. Have Claude deploy it to Vercel. 2. Set up a Google Cloud service account, enable the Google Sheets API, and share the sheet with the service account’s email address. Configure each submission to append a row. 3. Embed the form on your wedding website and email the direct link separately. Some people will never open the website. 4. Ask for everything you will eventually need, not just attendance. Your caterer and venue will want meal counts and dietary restrictions, and going back to collect that information later is miserable. 5. When it is time to seat people, point Claude at the same sheet and write your rules in plain language: who must sit together, who cannot sit together, who needs a quiet table, and who can anchor a table of strangers. 6. Have Claude generate a first draft based on those rules, then move people yourself. This works anywhere you have a public form collecting data and a private tool that needs to reason about it. Put a spreadsheet between them instead of building one app that tries to do both. The form stays simple, and whatever you build six months later can read from the same place.

I took pictures of the labels on the back of my TV and my old Sennheiser headphones. I submitted both pictures to Grok and asked how my old RCA-connected headphones could work with my new Vizio TV, which did not have an RCA output. Grok directed me to Amazon to buy a $15.00 DAC converter. Following its instructions, I plugged the optical lead supplied with the DAC into the TV, made one adjustment to the audio settings, and voilà—my old headphones worked again. I didn't need to provide descriptions of my products; the pictures of the labels were enough. Step-by-step: 1. I took pictures of the labels on the back of my Vizio TV and old Sennheiser headphones. 2. I submitted both pictures to Grok and explained that the TV did not have an RCA output. 3. I followed Grok's recommendation to buy a $15.00 DAC converter from Amazon. 4. I connected the optical lead supplied with the DAC to the TV. 5. I made one adjustment to the TV's audio settings and used my old headphones again.

Every Monday, Hermes checks my favorite coffee brand’s website and grocery stores for sales. When it finds a deal worth knowing about, it emails me so I can stock up. Step-by-step: 1. Hermes checks my favorite coffee brand’s website every Monday. 2. It checks grocery stores for sales on the same day. 3. When it finds a worthwhile deal, it emails me. 4. I use the alert to decide when to stock up.

I kept forgetting who I had lent books to, and spreadsheets felt like overkill. So I built Runo, a book-lending app for friends, without traditional coding. Runo (runo.club) is a web app where I can catalog my home library, get a unique shareable link, and let friends browse my books and request to borrow them. I can approve or decline each request with one click. Step-by-step: 1. I used Claude to think through the feature set, data model, and UX flow before writing a single prompt. This helped me avoid building the wrong thing first and gave me a clear blueprint for the Lovable prompts that followed. 2. I used Claude to create precise, narrowly scoped prompts for Lovable, with each prompt focused on a single change so existing functionality would be less likely to break. This significantly conserved Lovable credits. The React, TypeScript, and Supabase stack came out of the box. 3. I added two ways to scan books instead of requiring users to type titles manually: - Barcode scanner: Point the camera at an ISBN barcode to autofill the title, author, and cover using the Open Library API. - Cover photo scanner: Photograph the cover so Gemini 2.5 Flash can extract the title and author in under 2 seconds. 4. I routed the cover scanner through a Supabase Edge Function using Lovable’s AI Gateway, so the API key never touches the client bundle. 5. For every bug fix and feature, I followed the same iteration loop: describe the problem to Claude, get a precise Lovable prompt, push the changes to GitHub, and let Lovable auto-sync them. Claude and Lovable’s bidirectional GitHub sync made the process feel like pair programming. Tools used: Lovable, Claude (Sonnet), Gemini 2.5 Flash (via Lovable AI Gateway), Supabase, and GitHub. Live at: runo.club — public beta and free to use. Feedback welcome. #appbuilding #vibecoding #buildinpublic #lovable #nocode

I asked Claude to build me an artifact that works as my own personal book tracker. It includes separate sections for books I want to read, books I’m currently reading, and books I’ve read. I also asked Claude to collect specific data points about each book and create an insights tab that can gather information about my likes and dislikes over time, then make future recommendations. I personally dislike Goodreads’ UI and don’t use its social media features, so I wanted a personalized alternative housed within Claude alongside all my other workflows—a one-stop shop. Step-by-step: 1. I asked Claude to build an artifact for tracking my books. 2. I organized the tracker into books I want to read, books I’m currently reading, and books I’ve read. 3. I specified the data points I wanted to collect for each book. 4. I asked Claude to add an insights tab to gather data about my likes and dislikes. 5. I set it up to use those insights for future recommendations and keep the entire workflow within Claude.