Greg Isenberg and Ryan Carson describe agent management as a distinct operating skill. Instead of treating one assistant as a chat partner, they run several workstreams in parallel, give each task focused context and reserve human attention for product choices and high-stakes decisions.
The workflow depends on strong boundaries. Production credentials stay separate from development agents, important threads remain pinned and recoverable, and automated browser tests, monitoring and watchdogs provide evidence that shipped changes behave correctly.
Ryan Carson also describes feedback loops that grade agent work, identify recurring failures and improve the system over time. The broader lesson is that an AI software factory needs management structure, evaluation and cost-aware model routing, not just more autonomous tools.
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