I gave my second brain two agents that read the outside world and collide it against my notes. A Magpie watches my GitHub stars and only speaks when something hits live work. A Blue Jay reads a handful of RSS feeds and surfaces the distant, not-yet-relevant connection. They share a security spine — and they have deliberately opposite jobs. Here’s why the split is the whole design.
A rejection isn’t actionable data. So an n8n workflow now extracts skill demand from live job listings, diffs it against what I can prove, and renders the gap as a dashboard — deployed like everything else here: via git push.
A farm robot is replacing pesticides with UV light at night. The clever part isn’t the robot — it’s the darkness. Here’s the home version, and the honest scope of what it can and can’t do.
You don’t have to be job-hunting to want to know your market — what’s out there, what it pays, where you’d fit. So I built an n8n workflow: it polls the public ATS APIs (Greenhouse/Lever/Ashby) plus a broad remote-jobs feed, filters for remote-EU infra roles, scores each posting against my CV with an LLM, and emails me only the 80%+ matches. No database, no scraping.