AI agents are often mislabeled; focus on tool design, not just models

The current discourse around AI agents is overly broad, with many systems being mislabeled as agents when they are merely sophisticated function calls. True agents possess objectives, make independent decisions, handle failures, and know when they are complete, rather than requiring human guidance at each step. In production, effective AI agents are typically narrow in scope, focusing on specific tasks like customer support triage or document extraction, and their success hinges on robust tool design, failure handling, and observability, rather than solely on the latest model releases. AI

IMPACT Clarifies the practical application of AI agents, emphasizing robust engineering over model hype and guiding development focus.

RANK_REASON Opinion piece discussing the definition and production reality of AI agents, contrasting with current trends and frameworks.

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