UN TEMA, EN CONTEXTO

agent memory architecture

Judgments in this source concerning agent memory architecture. Explora 1 punto de vista con evidencias de 1 fuente.

1 personas · 1 fuentes · 1 opiniones expresadas

Contenido actualizado:

Explorar conexiones ↗

Mapa de perspectivas

Explore por persona. Seleccione dos o tres para compararlas.

1 personas · 1 fuentes · 1 opiniones expresadas

João (Joe) Moura

Persistent cognitive memory for agents

CrewAI provides persistent cognitive memory for both Crews and Flows, enabling agents to retain information across sessions, accumulate knowledge over time, and strategically forget — shifting from stateless interactions to learning-capable, long-running workflows.

Evidencia a favor

Orchestrating Self-Evolving Agents with CrewAI and NVIDIA NemoClaw | CrewAI

Extracto original

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.
Contexto

Persistence is also essential when agents need to pause for human input or recover from interruptions. CrewAI’s @persist() decorator automatically saves workflow state so execution can resume later.

Compartir informaciónVerificar esta afirmación

Estas son perspectivas individuales, no una medida de consenso. El material fuente permanece en su idioma original.