Workspace

Ángel's desk setup with a laptop, two monitors, speakers, keyboard, and mouse.

Hardware

MacBook Pro: M4 16gb ram, main portable command center.
Homelab 1 & 2: Proxmox, 32gb ram & 32gb ram, Ubuntu server, Unraid, Dockploy, Docker containers, Stremio
Windows PC: The only windows machine, RTX 2080 super, used for highly graphics-demanding tasks, and windows app testing.
VPS: Contabo machine with 8gb ram, ubuntu server, 24/7 agents, hermes/openclaw, chronjobs, bacground jobs

Software

Ghostty My everyday terminal.
Rectangle My window management tool.
Stats The quickest way to see what my Mac is doing from the menu bar.
CodexBar Keeps model limits, reset times, and usage visible in the menu bar.
Macshot My screenshots tool
Other apps I am using: Raycast, Tailscale, Wispr Flow

My AI manager

A standard terminal is no longer enough to manage agents working in parallel. I currently use cmux.

I would like to use T3 Code once it has official subagent support.

I also recommend checking out Herdr and Orca. There are many agent harness and orchestration tools, but these four are my favorites at the moment.

My underlying agent configuration uses OpenCode with angel-ai as its orchestrator. You can find my MCP servers and configuration, skills, and agents there. In short:

cmux + OpenCode + angel-ai.

My token usage

Tokens per day

Daily tokens7-day average

Top 3 models

gpt-5.53.6B
gpt-5.6-sol1.6B
claude-fable-5264M

Cost calculated using API prices, check your usage `npx devrage cost`

Benchmarks

Some time ago, we had models posting very high benchmark scores that did not reflect real-world performance. Since each model has a different price per token, uses varying amounts of reasoning for each task, consumes more or fewer tokens, and completes the task in more or fewer steps, it is more useful to measure cost per completed task or intelligence per unit of cost. These are the benchmarks I recommend.

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