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LLM Context Window Limit EXPOSED! Stop Your AI Coding Agent Getting "Lost in the Middle"

Ever experienced frustration when your AI coding agent suddenly forgets your instructions midway through a task? The culprit is the LLM Context Window, and understanding its limits is the single most important skill for working with Large Language Models (LLMs) effectively.

In this deep dive, we break down exactly what the context window is: the hardcoded limit on the combined input and output tokens an LLM can process. Every time you chat, that window shrinks!

We explain the critical "lost in the middle" problem—why information placed in the center of a long conversation is often deprioritized, leading to degraded performance and buggy code.

More importantly, we show you the pro-tip for fixing it: regularly clearing or compacting conversation histories to maintain a lean context window. This essential technique resets the agent’s working memory and guarantees optimal coding results every single time.

What's the largest context window size you've successfully managed in a coding project? Let us know in the comments! 👇

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