I built this to test whether a short-term BTC strategy was worth trusting before it ever touched real money.

It pulls live Kalshi data, signs requests, simulates long / short / flat trades, and records every decision. A strategy only graduates from paper mode if it survives fees, slippage, and multi-week holdouts; live ordering stays disabled by default.

I built a personal feed because generic feeds kept mixing useful research with noise and forgot what I had already seen.

It collects sources into an offline SwiftData queue, remembers read / save / like / skip decisions, refreshes in the background, and notifies me about high-severity posts. Sources open inside the app so the research trail stays intact.

I repurposed an old first-generation iPhone SE into a local security camera instead of buying another camera.

The phone captures H.264, serves an RTSP stream, advertises itself over Bonjour, survives a locked screen, and exposes health checks. Scrypted rebroadcasts it into HomeKit, with a frame watchdog and thermal guardrails for the parts that fail in real use.

I built the layer around my scheduled agents because a green cron job does not mean the useful work actually happened.

Hermes shows gateway pulses, model routes, cron state, browser-tool boundaries, Pi-side checks, and durable run notes. Jobs report proof or a specific failure class, then recover through an explicit path instead of silently staying stuck.

I built this because a headline is not a trade thesis until the underlying price and volume action agree with it.

It collects six-plus news providers, hashes and archives each headline in JSONL, deduplicates repeats, and sends selected items through hypothesis generation plus price / volume checks. Collection and analysis stay separate so every alert has a traceable source.