On-edge agent workflows and automated loops
Run agent workflows that persist near local tools, private data, and internal systems. Keep the runtime on-edge first, then move the same workflow to cloud when the workload belongs there.
The Challenge
Useful autonomous workflows are rarely "one-and-done" scripts. They need to wait on streams, wake up on specific events, process them, checkpoint progress, and go back to sleep.
Managing lifecycle, failure recovery, and isolation for background agent workflows becomes complex when teams have to build custom orchestration before proving the workflow.
MirrorNeuron Capabilities
- Delayed Self-Scheduling: Agents can put themselves to sleep and wake up periodically without consuming active execution resources.
- OpenShell Isolation: Give agents terminal capabilities with confidence. OpenShell bounded execution ensures sandboxed processes can't break the host system.
- Local Restart Recovery: If the underlying node restarts, long-lived workflows can resume their exact state upon reboot.
Featured Blueprints
Python SDK Live Research Daemon
A long-lived Python-defined daemon that keeps state across repeated turns, sleeps between work, and can be adapted to internal monitoring, research, or scheduled analysis loops.
View BlueprintLLM Codegen & Review Loop
A multi-agent setup where one agent writes code to fulfill a spec, and another agent runs tests and reviews the code. They iterate until the review passes, executed safely within OpenShell.
View BlueprintWhy MirrorNeuron fits background agent workflows
Long-lived agent workflows need to wait, retry, checkpoint, recover, and continue safely near the systems they operate. MirrorNeuron keeps that operational story closer to a simple on-edge runtime than a heavyweight orchestration platform.