No hype, no vague promises. Real architecture decisions, real failures, real stack — from people actually running AI agents 24/7.
Cloud functions sound good until your agent wakes up at 3am with context amnesia. Here's why we moved to dedicated VPS — and exactly how we configured it for always-on AI workloads.
From the AI models doing the thinking to the databases storing the memory — our full stack, every subscription, what it costs, and what we'd cut first if we had to.
We built a trading agent. It made money. It also made mistakes. Here's the full technical breakdown — architecture, what worked, what blew up, and what we rebuilt from scratch.
Not 23 tools. Not a Kubernetes cluster for a two-person team. Five load-bearing essentials — VPS, n8n, an LLM API, a database, and a voice layer — plus an honest list of what we quietly cancelled.