I’ve developed an autonomous, AI-powered genealogical research system that combines historical investigation, evidence verification, family-tree reconstruction, and digital storytelling. Powered by GPT-6, scheduled AI workflows, archival research tools, and structured databases, the system continuously investigates family histories, cross-references historical records, identifies ancestral connections, resolves conflicting evidence, and documents discoveries with traceable sources. Research is managed through recurring, coordinated workflows that prioritize unanswered questions, preserve findings between sessions, and distinguish verified facts from working hypotheses. The goal is to build on previous discoveries rather than repeatedly starting from scratch. The platform supports two independent projects, Family Tide and Dare · Nation Family Archive, each with its own research records, evidence, and publishing experience. Using Supabase, GitHub, Cloudflare, and custom web interfaces, verified research can be transformed into interactive family trees, ancestral maps, historical timelines, digital artifact collections, and richly illustrated family narratives. The vision: A continuously evolving genealogical intelligence platform that doesn't simply collect names and dates. It investigates, questions, connects, preserves, and tells the stories of generations.

I built Elo, a voice guide on my curb painting site, for visitors who would rather talk than scroll. It's for anyone who wants to see my work, pricing, and a design preview without clicking around. 1. A visitor opens the site and taps "Talk to Elo". The browser opens a WebRTC voice connection to OpenAI through my server, which checks origin, session, and daily limits first. 2. They just talk. They can interrupt and speak any language, and Elo replies by voice. 3. The model has seven tools, and the page reacts to each one. show_completed_work puts real photos from my catalog on screen. show_website_section opens the real testimonials, FAQ answer, work, or pricing section. get_website_information reads exact public site copy, so reviews and prices are quoted, not invented. 4. show_business_links shows WhatsApp or Messenger when they want to proceed. show_competitor_pricing runs only if they ask to compare. 5. propose_curb_design runs only on an explicit request, such as "make it Knicks colors, bold 25". It generates a preview with gpt-image-2 and edits the last image for changes. remember_visit_choices stores only explicit preferences, with the visitor's exact words as evidence. 6. The page sends its visible state back to the model, so Elo only says "here it is" after the image has loaded. Limits are 12 voice calls per visitor per day, 40 per day total, and a capped number of preview generations. Transcripts are saved for private review, with no raw audio. Elo gives one to three short sentences per turn, uses only published pricing and site copy, and can't book jobs or send messages. I confirm the design, price, and timing myself, and previews are labeled as concepts. Result: nobody scrolls or clicks. Visitors talk, and the site shows them my work, pricing, and a preview. Note: Am just building it not yet build.

I built this workflow for product teams that have research but no clear path from customer evidence to what to build next. It works one discovery stage at a time, keeps evidence separate from inference, and does not move forward until a person approves each stage. 1. Define the outcome you are trying to reach. 2. Upload your research or answer the guided questions. 3. GPT-5.4 Mini extracts evidence-backed facts, insights, assumptions, and quantified customer opportunities. I use this prompt for the extraction step: "Guide one discovery stage at a time, separate evidence from inference, preserve supported numbers, never invent findings, and require human approval." 4. Review the extraction and approve it. Nothing continues without this approval. 5. After approval, the workflow scores the opportunities, proposes solutions, and designs lean experiments. 6. Approve the results, then it generates the final Opportunity Solution Tree and a decision report. The app is built with OpenAI Sites, the Responses API, D1, and R2. What it produces is a traceable map from customer evidence to outcome, solutions, and experiments, with the numbers from the source material kept intact so the team can check every claim against what customers actually said. https://product-discovery-master.vspirola76.chatgpt.site/

I’m on a GLP-1 medication that heavily suppresses my appetite, and I’m also managing a bilateral vestibular condition that causes balance and gaze issues. I needed a way to hit my protein and calorie targets despite having a low appetite, track body composition accurately, log vestibular symptoms, connect my actual training data, and get coaching guidance that reflects my situation instead of generic fitness-app advice. I built FuelStrong: three connected apps created with Claude over many sessions. They include a daily tracker for meals, water, energy, and training check-ins; a Progress and analytics module; and a standalone Vestibular symptom tracker. They share a Cloudflare Worker and D1 database backend, with KV for cross-device sync. I describe a feature or problem to Claude in plain language. Claude proposes structural options, I push back or choose a direction, and Claude writes the HTML, CSS, and JavaScript. I program my lifts in Fitbod using an Upper/Lower/Upper split, with an arms-and-back priority and the Build Muscle goal. I export those workouts as CSV and drop them into FuelStrong’s import zone, which parses exercises, sets, reps, and volume into my training history. Custom foods receive macro estimates through a Claude API call routed through my own Worker endpoint. Evolt body-scan data feeds dynamic calorie and protein targets based on BMR × activity factor, minus a deficit, with hard floors instead of static numbers. The Vestibular module intentionally uses open text fields for now, so Claude and I can identify which data matters before formalizing the inputs. Everything syncs across devices through Cloudflare KV. The coaching layer uses a three-tier framework—evidence floor, confirmed operating range, and aspirational target—to drive every recommendation. Two calorie floors, a daily target of approximately 1,000–1,100 kcal and a weekly average of approximately 1,300–1,400 kcal, reflect that chronic under-eating—not missed protein—is the real GLP-1 risk. Muscle mass has remained stable since my February 2026 baseline, so the coaching treats that as a genuine win rather than a plateau. Vestibular-training coaching connects dry-needling focus areas—SCM, suboccipitals, and splenius capitis/cervicis—to gaze-stabilization symptoms, since cervical proprioception substitutes for non-functional vestibular canals. The result is one dashboard that brings together training, nutrition, body composition, vestibular symptoms, and coaching logic. My muscle mass has held stable through it all. Step-by-step: 1. I describe a feature or problem to Claude in plain language, review its structural options, choose a direction, and have Claude write the HTML, CSS, and JavaScript. 2. I use FuelStrong’s daily tracker to record meals, water, energy, and training check-ins, while the Progress and analytics module tracks body composition and related trends. 3. I program my Upper/Lower/Upper workouts in Fitbod with an arms-and-back priority and the Build Muscle goal. 4. I export Fitbod workouts as CSV and import them into FuelStrong so it can parse exercises, sets, reps, and volume into my training history. 5. I route Claude API requests for custom-food macro estimates through my own Cloudflare Worker endpoint. 6. I use Evolt body-scan data to calculate dynamic calorie and protein targets from BMR × activity factor, minus a deficit, while maintaining hard floors. 7. I log vestibular symptoms in the standalone Vestibular tracker using open text fields while Claude and I determine which inputs should eventually be formalized. 8. I sync the three apps across devices through the shared Cloudflare Worker, D1 database, and KV backend. 9. I use the evidence floor, confirmed operating range, and aspirational target framework to guide recommendations, including the daily and weekly calorie floors. 10. I connect vestibular-training coaching to dry-needling focus areas and gaze-stabilization symptoms, then use stable muscle mass since the February 2026 baseline as a positive outcome rather than treating it as a plateau.

I built a suite of teaching tools that work independently and together. Chalkline supports maths, while Penline supports literacy. Both tools provide quick access to the New Zealand curriculum for planning and feed information directly into my planning utility, Planline, making teacher planning faster. Planline integrates with Google Drive and is set up with Stripe billing for subscriptions. The suite also includes Compass World News, a news aggregator with a freemium model and a pro unlock. The apps are designed without user tracking. Findaroo is a freemium word-find game with ads. Slashkit helps Minecraft players quickly create commands to use in games. Everything is built into my website, www.danielsoutham.co.nz, which is hosted on Cloudflare. I push updates and changes through GitHub, so I can make changes—big or small—from anywhere, on any device. Changes are then pushed and merged in one prompt. Step-by-step: 1. I built Chalkline for maths and Penline for literacy, with each tool able to work independently. 2. I connected both tools to the New Zealand curriculum so teachers can quickly access it for planning. 3. I connected Chalkline and Penline to Planline so they can feed information into the planning utility. 4. I integrated Planline with Google Drive and set up Stripe billing for subscriptions. 5. I added Compass World News as a freemium news aggregator with a pro unlock and no user tracking. 6. I added Findaroo as a freemium word-find game supported by ads. 7. I built Slashkit to help Minecraft players quickly create commands for use in games. 8. I brought all of the apps together on www.danielsoutham.co.nz and hosted the website on Cloudflare. 9. I use GitHub to push and merge updates, allowing me to make changes from anywhere, on any device, in one prompt.