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I built a website that turns property photos, architectural renderings, or even just an address into cinematic property videos. I’m a civil engineer and photographer/videographer, not a software developer, so I used ChatGPT, Gemini, and Claude Code to help build the site and work through problems as they came up. Much of the process involved translating the way I would personally edit a real estate video into usable software. For example, kitchen and living room shots should usually stay together and have longer durations, bedrooms should stay near their bathrooms, an opening shot should feel different from a detail shot, and every clip should include some movement so the result does not feel like a generic slideshow. I used AI to turn those editing principles into actual logic for the site. The system analyzes and organizes the images, builds a storyboard, ranks scenes to decide which ones to use, creates prompts for video models, generates the clips, and assembles everything into a finished video. Most of the development has been iterative. I test the site with real properties I’ve shot, watch the results, identify what feels off, and then improve the prompts, scene planning, timing, or video assembly process. AI has been useful for much more than generating the final video. I’ve also used it to write code, troubleshoot errors, plan features, improve the user experience, and think through how the product should work from the perspective of its primary user. Step-by-step: 1. I defined the video-editing principles I use for real estate footage, including grouping related rooms, varying shot durations, distinguishing opening shots from detail shots, and adding movement to every clip. 2. I used ChatGPT, Gemini, and Claude Code to translate those principles into software logic. 3. I built the site to accept property photos, architectural renderings, or an address as input. 4. I had the system analyze and organize the images, build a storyboard, rank scenes, and select the footage to use. 5. I used AI to create prompts for video models and generate the clips. 6. I assembled the generated clips into a finished property video. 7. I tested the site with real properties I had shot, reviewed the results, and iteratively improved the prompts, scene planning, timing, and video assembly. 8. I used AI throughout development to write code, troubleshoot errors, plan features, improve the user experience, and think through the product from the primary user’s perspective.

Several months ago, my dad was in and out of the hospital. My two brothers and I were trying to coordinate his doctor appointments, manage his medications and potential interactions, and keep track of all the other details involved in his care. At one point, up to seven different doctors were seeing him in the hospital on any given day. It became important to track every medication he was taking, what each one was for, and information such as his weight and other vital statistics. When he returned home, we also had to make sure someone checked on him and his wife every day, helped him stay on schedule with his medications, and recorded his diet, mood, and weight. We initially used Apple Notes, a shared iCalendar, multiple text threads, and a weekly call between the three of us. The mental load was huge. If we needed to find information from the previous week, we had to scroll through pages of Apple Notes to locate it. We also struggled to keep the rest of the family updated. Before my dad passed away, I started using Claude Code and Codex to build a simple tool that would keep everything organized and searchable. It also displayed trends in areas such as his mood, appetite, and vital signs, and included a calendar showing who was covering which days and times. The tool was still fairly basic when he passed away. Afterward, we encountered the administrative headaches involved in closing out his estate. It was far more complicated than we expected. We thought having a will, power of attorney, and other documents meant we were prepared, but we were wrong. I began integrating those lessons—and the things we learned not to do—into the final product, Eldercare Log: eldercarelog.com. I built the final tool with Claude helping draft a PRD, which I then handed to Codex for the coding work. It took a few weeks of refining the product with Codex. The tool is hosted on Vercel, with Supabase and Stripe on the backend, and includes the security features I built into it. It is the tool I wish had existed when my brothers and I were going through this journey before my dad’s passing. Step-by-step: 1. I coordinated my dad’s doctor appointments, medications, vital statistics, and other care details with my two brothers while he was in and out of the hospital. 2. We tracked his medications, their purposes, his weight, diet, mood, appetite, and other vital signs while he was at home. 3. We coordinated daily visits and coverage using Apple Notes, a shared iCalendar, text threads, and a weekly call. 4. I used Claude Code and Codex to start building a searchable tool that organized his care information and showed simple trends. 5. I added a calendar to track which family member was covering each day and time. 6. After my dad passed away, I incorporated what we learned from handling his estate, including the things we wished we had known earlier. 7. I used Claude to draft a PRD, then gave it to Codex to handle the coding work and refined the product with Codex over several weeks. 8. I built the final tool with Vercel, Supabase, and Stripe on the backend.

My doctor asked me to track my blood pressure for a month because it was on the high side before prescribing any medication. I initially recorded each reading manually in an Excel sheet, but after a few days, I wanted a simpler way to enter and manage the data. I uploaded the sheet to Claude Code and asked it to build a blood pressure tracking app. After the app was built, I hosted it on Netlify, used Supabase as the backend to save data for both my wife and me, and added it to my iPhone Home Screen. Step-by-step: 1. I started tracking my blood pressure in an Excel sheet as my doctor requested. 2. After several days of entering the readings manually, I uploaded the sheet to Claude Code. 3. I asked Claude Code to build an app for tracking blood pressure. 4. I hosted the app on Netlify. 5. I used Supabase as the backend to save blood pressure data for both my wife and me. 6. I saved the app to my iPhone Home Screen for easier access.

I used Claude Code to find scientific seminars hosted by colleges and universities across the US and collate them into a single, searchable list. Researchers can use it to find talks that match their interests near them. The site, seminarsearch.org, runs mostly on free-tier SaaS services, costs me $5 per month to operate, and currently supports a few thousand users. The same pattern could be adapted to collate all 5K runs in the US, tennis matches, craft shows, quilting bees, or any other type of event that interests you. I started by explaining to Claude what I wanted to build. We then spent a few hours exploring where and how to identify seminar calendars at universities across the US, which was arguably the hardest part. We developed a pluggable framework with scraping plugins for the common CMSs used by universities, along with iCal parsers, HTML parsers, and JavaScript interpreters to handle the complexity of normalizing content from hundreds of departmental websites. Once we had the seminar-scraping infrastructure, we built a database schema in Supabase and simple APIs to create, read, update, and delete records. The APIs are written in Python and hosted on Railway for $5 per month. We used Vercel to deploy a simple React-based frontend for presenting the data. Now I can ask Claude to implement a feature or add a new university to the list of sources. It figures out where the data is hosted, creates entries for the university and its departments, finds their seminar feeds, collects the seminar data, puts it into the database, and runs GitHub Actions to send alerts to registered users. The scraping job runs once a week to collect new data, and it also runs through GitHub Actions. I wrote zero code during this process and have never even looked at the code. I only had to paste a few error messages from Railway into Claude so it could debug them, and there were only a few errors. Since building seminarsearch.org, I have cloned the infrastructure and codebase and modified it to build a site that collects road bike rides and group mountain bike rides across the country. The system is highly extensible to new areas of interest and is useful when traveling or living in a large metropolitan area where it is difficult to keep track of all the opportunities available for your interests. Step-by-step: 1. I explained to Claude Code that I wanted to build a searchable directory of scientific seminars hosted by colleges and universities across the US. 2. We explored where and how to identify university seminar calendars, focusing on the challenge of finding sources across many institutions. 3. We built a pluggable scraping framework with plugins for common university CMSs, plus iCal parsers, HTML parsers, and JavaScript interpreters. 4. We created a Supabase database schema and simple Python APIs for creating, reading, updating, and deleting seminar records. 5. We hosted the APIs on Railway for $5 per month and deployed a React-based frontend on Vercel. 6. We configured Claude to add universities and implement features by finding source locations, creating university and department records, locating seminar feeds, collecting seminar data, and adding it to the database. 7. We used GitHub Actions to run the weekly scraping job and send alerts to registered users. 8. When Railway returned errors, I pasted a few error messages into Claude so it could debug them. 9. I cloned and modified the infrastructure and codebase to create additional sites for road bike rides and group mountain bike rides across the country.

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