Digital Twins, Not Agents, May Be the Endpoint for AI Systems, Argues Essay
An opinion essay on DEV Community argues that today's wave of AI agents is a transitional technology rather than the final form of autonomous systems. It contends that agents are transactional function-call loops that suffer from context fragmentation when chained together in multi-agent setups. The author proposes digital twins, persistent stateful models of real-world entities that retain memory and behavioral constraints, as the more mature architecture. The piece also suggests that digital twins enable predictive, simulation-based execution instead of reactive, fire-and-forget automation.
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