The problem was never too few AI tools — it was that nobody had connected them into one pipeline that produces work worth publishing, instead of slop. Before I engineered content, I made it by hand for years: neuroscience videos, courses, essays. That taste is the part automation can't fake, and it's what I build into every system I ship.
CLOUDFLARE WORKERS
IN PRODUCTION
LIVE PRODUCTS USING
AUTOMATIONS I BUILT
NODES IN MY LARGEST
n8n PRODUCTION WORKFLOW
HOURS SAVED MONTHLY
BY A TYPICAL BUILD
Learn the domain, the audience, and what “good” looks like here — before a single word is generated.
Turn that judgment into the system: prompts, guardrails, source hierarchies, and structure the model has to follow.
Nothing publishes unvetted — fact-checks, quality gates, and a human veto where it earns its place.
Watch what ships, measure what lands, and tighten the system so it compounds instead of drifting.
Knowing the difference between publishable and passable. It doesn't come from a model — it comes from years of making the work by hand.
Cited sources, real structure, no hallucinated stats. If it wouldn't survive an editor, it doesn't ship.
Content that earns attention and gets cited — not volume for a dashboard.
Impossible workflows, built end to end.
n8n where speed wins. Cloudflare where production counts.