I build tools that do the boring parts of creative work.

Most AI tools give you a chatbot and wish you luck. I build the infrastructure underneath: pipelines that break complex creative tasks into reliable steps, route them through the right AI models, and deliver structured output you can actually use.

Image generation that maintains character identity across providers. Video synthesis driven by music. Knowledge graphs that grow themselves. Data pipelines that detect anomalies in climate datasets. Different domains, same architecture.

The throughline is structural. Every project runs on the same engine. The difference between generating one image and orchestrating a hundred-frame video is depth, not shape.

You hand a tool a reference image, and it doesn't just describe what it sees. It extracts structured visual DNA: color palettes, face geometry, texture patterns, stylistic lineage. That extraction becomes a schema, and the schema drives generation across any provider. Swap from one AI model to another and the character still looks like herself.

The same principle applies everywhere. Feed a knowledge system raw vocabulary and it doesn't just store definitions; it maps relationships, detects gaps, and grows its own understanding over time. Give a data pipeline a stream of weather observations and it doesn't just chart the numbers; it learns what normal looks like so it can flag when something breaks pattern.

Every tool is provider-agnostic. The models change constantly (what's best today won't be best in six months), so nothing is hardcoded to a single AI service. The architecture routes to whichever model fits the task. When a better one shows up, it slots in without rebuilding anything.

I build all of this solo, on Cloudflare's edge stack, with AI handling the structural work and human judgment handling the creative decisions. That's the philosophy in one sentence: invisible labor, visible results.