Running AI agents in production: what breaks when your laptop sleeps

The demo-to-production gap

An agent on your laptop works until you close the lid. An agent on a serverless runtime works until the timeout. Production agents need four boring things: a machine that stays on, storage that survives a restart, secrets that are not pasted into a chat window, and a restart policy that assumes failure.

Four requirements

1. Persistent storage. Agent memory, uploaded files and vector indexes must live on a volume, not in the container filesystem. Otherwise every deploy wipes your context.

1. A real secret store. Model API keys should be injected at runtime from an encrypted vault. If your key sits in a prompt history or a public repo, assume it is compromised.

1. Health checks and auto-restart. Long-running agents leak memory and stall on network hiccups. A supervisor that restarts on failed health checks turns a 40-hour outage into a 40-second blip.

1. Channel reliability. WhatsApp and Telegram sessions drop. Reconnect logic and idempotent message handling matter more than the model you chose.

What we do about it

OpenClaw hosting on Infinite Host gives you an isolated instance, a persistent NVMe volume, an encrypted key vault, health checks with auto-restart, snapshots and live logs. When it is your agent doing the work, the infrastructure should be boring.