• The Problem: Three Apps, Three Silos, Zero Insight
• The Spark: What If I Built This Myself?
• 7 Days: From Zero to Full Platform
• This Is NOT Vibe Coding
• Why Sovereignty Matters
• Lessons Learned
• Try It Yourself
• Summary
• References

Bitcoin has Proof of Work. After 15 months of tracking every biomarker in my body, I now have Proof of Blood.

In January 2025, I decided to go full carnivore. Not because of a medical condition, out of pure curiosity. Can we survive without carbohydrates? Can we thrive?

15 months later, I feel like I’m 20 again. But this article isn’t about diet advice. It’s about what happened when an analytical mind met fragmented health data, and what AI-assisted engineering made possible in 7 days.

§The Problem: Three Apps, Three Silos, Zero Insight

To back up my experiment with real data, I started testing my biomarkers weekly. Cholesterol, ketones, uric acid, hematocrit, hemoglobin, weight, body fat, muscle mass, the full picture, every week since January 2025.

The problem? Three different measurement devices, three different apps, three isolated data sets. Valuable health data, locked in silos with no way to cross-reference or correlate.

I started with what every data person starts with: a spreadsheet. Formulas, conditional formatting, color coding. It worked, but it was tedious and didn’t scale.

Then I tried ChatGPT. I’ll be honest, the health analysis was genuinely helpful. More useful than what most doctors have time to provide, and available 24/7. I could discuss scenarios, ask follow-up questions, iterate.

But then it hit me: I was feeding my most personal data, blood work, body composition, health history, into a system with zero GDPR guarantees. My data was being stored somewhere I couldn’t audit, couldn’t encrypt, couldn’t delete.

That was the wake-up call.

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§The Spark: What If I Built This Myself?

Working in a digital-first company like Accenture that embraces AI from day one, I see every day how AI accelerates complex engineering projects. So I asked myself: what if I applied the same approach to my own problem?

I started with OpenClaw, an interface for Claude AI, to turn my biomarker tracking table into a proper specification. Back and forth, refining requirements, adding features, specifying the technology stack. After 5 days, I had a complete functional and non-functional requirements document, ready for implementation.

What I had specified was not a simple tracker. It was an enterprise-grade, privacy-first health intelligence platform. And the spec was detailed enough to hand directly to an AI coding assistant.

§7 Days: From Zero to Full Platform

I used Claude Code to set up the development environment. Rust backend, CI/CD pipeline, GitHub integration, server deployment, all dependencies. Day one went nearly flawlessly.

What happened over the next 7 days still amazes me. I built the complete backend, frontend, and marketing website. Not a prototype, a production-ready platform. (link below)

Here’s what “production-ready” means in numbers:

• over 100 biomarkers across 8 health zones (metabolic, cardiovascular, immune, hormonal, cognitive, nutritional, structural, detoxification)

• 8 calculated markers derived automatically: GKI, Dr. Boz Ratio, HOMA-IR, TyG Index, BMI, WHtR, TG/HDL Ratio, HCT/HB Ratio

• 13 diet protocols (carnivore, keto, OMAD, paleo, Mediterranean, and more) with 7 fasting patterns

• Dr. Alex - an AI health assistant with 8 specialist modes for labs, trends, diet, supplements, and protocols

• Multi-tenant architecture - doctors, clinics, and families can run their own white-labeled instance

• Multi-language support (English and German), with full GDPR and HIPAA audit reporting

• Automated sprint planning and CI/CD - 7 sprints completed, 57 commits in Sprint 001 alone, 826 files touched

• 35,000 lines of Rust code, 117 SQL database migrations, 500+ frontend test files

I felt like the development manager of an entire department where every team member worked 24/7. Three more days of cleanup and fine-tuning, and Sovereign Health Intelligence was live.

§This Is NOT Vibe Coding

I’ve had this discussion a few times already, so let me address it directly.

This is not vibe coding. I’m not dragging and dropping pre-built components in a web tool. I’m not configuring workflows in a no-code builder. There’s no magic “generate my app” button.

This is raw, high-performance Rust code (Actix-web 4). A Next.js 16 frontend. A PostgreSQL 16 database. Every measurement encrypted with AES-256-GCM at rest, not just in transit. Row-level security enforced on 15 database tables. Even the server administrator cannot read your health data. Fully encrypted Blob storage and more for selfhosting on Start9 Server is on the roadmap.

I was the human in the loop. Every architectural decision (adr full log), every security design (full log), every feature prioritization, that was me. The AI was the accelerator. I was the architect.

The entire codebase is AGPL-3.0 licensed. Every line is auditable. Every encryption claim is verifiable. That’s not something you get from vibe coding.

§Why Sovereignty Matters

This project didn’t come from nowhere. I wrote a book called “Brick By Brick - A Sovereign Life with Bitcoin” about owning your financial infrastructure. Sovereign Health Intelligence is the health chapter of that same philosophy.

Own your money. Own your data. Own your health records.

The platform is self-hostable via Docker, run it on your own server, your own VPS, your own Raspberry Pi. Payments are accepted via Stripe and Bitcoin Lightning. The code is open source.

Your body, your data, your server.

Bitcoin gave us Proof of Work. Now I have my Proof of Blood, 15 months of weekly biomarker data, encrypted, sovereign, and mine.

§Lessons Learned

1. Data without analysis is noise.

Three apps gave me data. One platform gave me insight. Collecting biomarkers is step one, correlating them across health zones is where the value lives.

2. AI is a force multiplier, not a replacement.

Claude Code wrote the Rust. I made every architectural decision. The human-in-the-loop is not optional, it’s what separates engineering from generated output.

3. Privacy is a foundation, not a feature.

The moment I realized I was feeding my blood work into ChatGPT with no GDPR guarantee, I knew I had to build something different. Encryption at rest is the minimum, not the ceiling. Anonymizing data before feeding an AI is a must have.

4. Specification before speed.

5 days on a proper spec with OpenClaw saved weeks of rework. AI can generate code fast. Without clear requirements, it generates the wrong code fast.

5. Open source is accountability.

AGPL-3.0 means anyone can verify the encryption claims, audit the security model, and fork the project. Trust, but verify, starting with the code.

6. Start with your own problem.

The best tools come from genuine frustration, not market research. I built this because I needed it. That’s why it works.

§Try It Yourself

Sovereign Health Intelligence is live and free to use.

Register at sovereignhealth.io, the free tier (Glimpse) gives you access to core biomarker tracking with 8 key markers. Five subscription tiers scale from personal use through enterprise.

Prefer to self-host? The full codebase is on GitHub under AGPL-3.0. docker compose up and you’re running your own sovereign health stack.

For readers of this article: reach out to me directly for a 50% discount code on any paid tier. If registered by the end of April you get a full license tier upgrade for free.

What would you build if you had 15 days and an AI pair programmer?

§Summary

• Started carnivore in Jan 2025 out of curiosity, now 15 months in, tracking 108 biomarkers 6 of them weekly across 8 health zones

• Frustration with 3 siloed apps and GDPR-blind AI led to building my own platform

• Used OpenClaw + Claude AI for a 5-day specification, then Claude Code for 7 days of implementation and 3 day clean-up

• Result: ~35,000 lines of Rust, 117 migrations, 500+ frontend tests - enterprise-grade, encrypted, open source

• This is human-in-the-loop AI engineering, not vibe coding: raw Rust, AES-256-GCM encryption, row-level security

• Sovereign Health Intelligence is live, free to try, and open source

§References

1. Sovereign Health Intelligence - https://sovereignhealth.io

2. GitHub Repository - https://github.com/sovereignbrick/brickos

3. OpenClaw (AI specification interface) - https://openclaw.ai

4. Claude Code (Anthropic) - https://claude.ai

5. “Brick By Brick - A Sovereign Life with Bitcoin” Helmut Schindlwick https://amzn.to/4mW2pK4

6. Rust Programming Language - https://www.rust-lang.org

7. Actix-web (Rust web framework) - https://actix.rs

8. Next.js - https://nextjs.org

9. PostgreSQL - https://www.postgresql.org

10. AGPL-3.0 License - https://www.gnu.org/licenses/agpl-3.0.html

11. AES-256-GCM (NIST encryption standard) - https://csrc.nist.gov/publications/detail/sp/800-38d/final