Prompt engineering alone is insufficient for developing robust AI agents because agents are complex systems involving multiple components beyond just the LLM. Developers need to implement an evaluation loop to systematically test agent behavior, ensuring changes don't introduce regressions across planning, retrieval, tool use, and other critical functions. The implication is that a robust evaluation framework is paramount for safe and effective AI agent iteration.
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