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Optimizing LLM for Agentic Workload: Best Practices

This story is from 2026-09-17. It is preserved in the archive; the latest stories are on the live feed.

Agentic workloads move LLMs from single-turn question answering into sustained, multi-step operations where the model plans actions, invokes tools, and refines output based on intermediate observations. Each step adds latency, consumes context window capacity, and introduces potential failure point…

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  1. 2026-09-17 15:36 · DEV Community — AI
    Optimizing LLM for Agentic Workload: Best Practices

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