Technical articles on AI, trading systems, and software engineering
The architecture behind operum.ai — Tauri, Rust, SvelteKit, file-based IPC, and a workflow arbiter that keeps 6 AI agents coordinated without a cloud backend.
The hardest part of engineering isn't writing code — it's starting. Here's how an AI PM eliminates the cold-start problem and lets creativity unfold.
Two weeks ago, operum.ai had 17 issues and 10 PRs. Now the dashboard shows 194 issues, 166 PRs, and agents self-coordinating across marketing, PM, and engineering.
AI coding assistants are powerful, but unlocking their full potential in enterprise environments requires a context automation layer. Here's the pattern.
6 specialized AI agents. One orchestrator. Ship products faster with autonomous development, marketing, and community workflows.
Anthropic's 2026 report shows engineers delegate only 20% of tasks to AI. Here's how multi-agent architecture pushes that to 60%.
How I evolved from Tailscale + Termux remote access to running 6 autonomous AI agents using file-based IPC, systemd, and cron — no cloud APIs required.
Practical UI patterns from building trading systems at Millennium, ExodusPoint, and Citi. Flash-on-change, position flattening, smart defaults, and more.
Pick Worker for streaming, WASM for filtering, or JS for simplicity—same API, different superpowers.
How I set up Tailscale and Termux to SSH into my workstation from my phone, enabling continuous Claude Code sessions from anywhere.
After years of building data-intensive applications for finance, I realized there is a gap in practical technical content. This site aims to fill it.