Running AI agents locally is very different from running them reliably in production. Production agents face unique failure modes: lost state after restarts, silent tool-call hangs, browser session drift, memory spikes, and credential expiry. Container uptime is not the same as agent health. A proper production runtime needs persistent workspaces, meaningful restart semantics (resume vs. fail vs. escalate), task-level observability, per-agent resource limits, scoped secret handling, and human override paths. For multi-tenant or fleet deployments, isolation between agents and customers is critical from day one. The post also covers the self-hosted vs. managed runtime tradeoff and provides a deployment checklist. The author discloses they work on Molted, a managed runtime for autonomous agent fleets.
