Guides·Guide
Long-running agents fail in quiet ways at scale. Here is why, and how to run them reliably.
TL;DR
Long-running AI agents do not fail loudly. They crash and stay down, corrupt their own config, leak memory until the machine dies, or break on the next version update.
Long-running agents do not fail loudly.
Babysitting one agent is doable: you restart it when it dies, fix the config by hand, watch the memory. Multiply that by hundreds, each on its own version, each expected to be online around the clock, and the manual approach collapses. You would need watchers, automatic recovery, memory protection and rollback running continuously. That is a platform, and building it has nothing to do with your product.
One agent
Easy to babysit.
A fleet, by hand
Reliability is a runtime property, not a prompt.
01
In-pod restart
A daemon restarts OpenClaw the instant it dies.
02
Pod recreation
If the pod fails, it is recreated with state intact.
03
Known-good restore
Config auto-repair and a versioned restore.
04
Critical alert
Only if all else fails, with a full post-mortem.
All of the above is buildable. It is also months of platform engineering plus a permanent on-call rotation. The alternative is a managed runtime. Molted runs long-running agents (OpenClaw today) on bare pods that never crashloop, with a daemon that survives the agent dying, automatic config repair, a memory semaphore for safe density, a versioned filesystem with point-in-time restore, and 4-tier self-healing that catches crashes in under 60s and restores them in under 90s, with a post-mortem on every failure. You run agents instead of running a recovery system.
Q.01
Usually silent process death, corrupted configs, memory spikes on shared machines, or breaking version updates. None are fixed by a better prompt; they are runtime problems.
Q.02
Yes, with supervision, self-healing, memory protection and versioned recovery. By hand it is hard for one and impractical for many; a managed runtime makes it the default.
Q.03
Throttle startups and shed by priority before the node runs out of memory. Molted does this with a RAM semaphore so high density stays safe.
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