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Optimizing LLM for Agentic Workload: A Practical Guide

This story is from 2026-08-25. It is preserved in the archive; the latest stories are on the live feed.

Agentic workloads differ from simple chat completions because they are stateful loops rather than single-shot requests. An agent reasons, plans, invokes tools, ingests observations, and repeats. Every tool result is appended to the conversation history, so context length grows naturally and often u…

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  1. 2026-08-25 15:33 · DEV Community — AI
    Optimizing LLM for Agentic Workload: A Practical Guide

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