Engineers often build complex systems around large language models (LLMs) that are unnecessary because LLMs can handle many tasks on their own with proper configuration. This complexity hinders debugging, evaluation, and maintenance. Developers should focus on clear tool descriptions, single-step prompts, quality data retrieval, and robust failure case evaluations to create more effective AI agents.
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