Hannes Rudolph speaks with Jacqueline Henriksen and Vitor Cepeda Lopes about sharing an OpenClaw agent across team sessions. They describe seeing one another’s work, sharing contextContext engineering designs how relevant instructions, evidence, state and tool information are assembled for a model's task. and coordinating contributionsAgent orchestration coordinates AI agents, tools, people, tasks, state, and control flow so a larger workflow reaches a verified outcome..
The participants compare a main agent with many sessions to separate agentsA multi-agent system contains multiple AI agents that interact, coordinate, divide work, or influence one another while pursuing tasks. or gateways for work, family and privacyData privacy governs how personal, confidential, or sensitive information is collected, used, shared, retained, and protected in AI systems.. They discuss messaging channels and interfaces as different ways to start tasks and review results.
The discussion ends with long-running goals: the guests emphasize specific instructions and checking outcomesAgent completion verification checks evidence that an agent achieved the requested outcome rather than merely producing intermediate work., since an agent running for a long time does not itself show that it accomplished useful work.
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