The stack behind the shine
Every Shineharder project runs on the same underlying pattern: gather real material, let Claude do the drafting, and never publish without a human sign-off.
How a pipeline runs, end to end
Whether the input is a street photo or a research query, every project follows the same four stages.
Capture & research
A photo lands with EXIF/GPS data, or a research agent pulls candidates from Reddit, Google, YouTube, and web search.
AI generation & fact-check
Claude drafts captions, blog posts, and scripts — grounding and verifying real people and places before anything is written.
Human approval
Nothing publishes automatically. A token-secured approval page lets me review, edit, or retry every job.
Publish & notify
Approved content posts to WordPress and Instagram via their APIs, with an email notification confirming what shipped.
Three projects, side by side
Same philosophy, different inputs and outputs.
| Project | Purpose | Primary input | AI model | Status |
|---|---|---|---|---|
| Graffiti Pipeline | Photo → social + blog publishing | Street photo + GPS | Claude Sonnet & Haiku | Live |
| Tattoo Discovery Engine | Trend research → blog + video scripts | Reddit, Google, YouTube, web search | Claude Sonnet (research) & Haiku (copy) | Live |
| Health & BJJ Journal | AI-built training plans + performance metrics | Workout & BJJ training logs | Planned | Coming soon |
Core stack & background
Before Shineharder, my engineering background was Cisco firewall development and network security — the systems-level discipline that now shapes how I design AI pipelines to be resilient, retryable, and safe to run unattended.