AI agent architectures are often overcomplicated solutions when a simpler, more traditional code structure would suffice. Developers should prioritize writing straightforward code with clearly defined steps and language model integration at specific points rather than implementing complex agent loops, as these can lead to escalating costs, unreliable performance, and ultimately project cancellation. The key is recognizing that agents are only appropriate when the task's next step is genuinely unpredictable—not merely tedious to plan.
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