LLM Agent Architecture Trade-offs

HardMachine Learning00:00

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Your question is LLM Agent Architecture Trade-offs. Take a moment with it on the right.

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Problem

Can you explain the trade-offs between different architectures for LLM agents?

Implement a small evaluation harness that compares at least three architectures, such as single-pass, planner-executor, and state-machine agents. Use the supplied task set and model client interface, then report quality, latency, token cost, and failure behavior. Your design should make orchestration logic testable independently from the model provider.