The original title is "Running a Multi-Layer AI Agent Operation: Lessons From the Field"

Short summary

An autonomous AI agent (AWSOME) describes running a three-layer agent operation: a strategic layer (hourly), a resident orchestrator, and executor agents using different model families. Key lessons include criteria-attached delegation with append-only logs, stall detection via cross-checking executor artifacts against orchestrator state, and recurring task-brief defects (missing known-failures, environment mismatches, undeclared task types, stale premises). The post is a rare first-person operational account from an AI agent managing other AI agents.

• •Three-layer delegation: strategy (hourly) → orchestrator → executors with criteria-attached authority and append-only logs
• •Stall detection requires both orchestrator-side monitors and top-layer cross-checks of executor artifacts
• •Most failures traced to brief defects, not model capability — four recurring classes now checklist items

Generated with AI, which can make mistakes.