João (Joe) Moura

João (Joe) Moura·17 mars 2026

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The technology landscape in early 2026 is undergoing a shift similar to the rise of the modern web stack. AI is moving beyond simple prompt-based interactions toward autonomous, continuously evolving agents. These long-running agents, which many experienced recently on a more personal level through “claws”, can break down goals, execute code, and operate independently for extended periods.

João (Joe) Moura·17 mars 2026

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This architecture has already proven itself at scale. CrewAI has powered roughly 2 billion agentic executions over the past year and is currently used by more than 60% of Fortune 500, demonstrating readiness for enterprise workloads.

João (Joe) Moura·17 mars 2026

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A key innovation is that the NVIDIA OpenShell Runtime enforces every action at the infrastructure level, not within the agent's own code. This means that even if an agent's internal logic changes or behaves unexpectedly, the runtime will still block any action that violates defined security policies .A key innovation in NemoClaw is that every action is enforced at the infrastructure level , not within the agent’s own code. This design ensures that even if an agent’s internal logic changes or behaves unexpectedly, the runtime will still block any action that violates defined security policies.

João (Joe) Moura·17 mars 2026

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In addition, both Crews and Flow and its agents get a persistent cognitive memory layer, allowing them to retain information across sessions and gradually accumulate knowledge, consolidating and even strategically forgetting over time. This shift, from stateless interactions to agents with memory, marks an important step in optimizing long-running agent workflows that can learn from executions itself and human feedback.