On-Edge Background Agents & Automated Loops
Deploy AI workers that run persistently 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
True autonomous workers are rarely "one-and-done" scripts. They need to sit idle listening to streams (like Slack or Discord), wake up on specific events, process them, and go back to sleep. Alternatively, they might be engaged in infinite iterative loops, like a developer agent that continuously pulls tickets, writes code, submits PRs, and incorporates reviewer feedback.
Managing the lifecycle, failure recovery, and isolation of these background workers is complex and error-prone when building custom orchestration.
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 workers 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 autonomous workers
Long-lived AI workers need to wait, retry, 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, which is part of its core differentiation.