Despite being powerful tools for decision-making at scale, every LLM still shares a frustrating limitation: they are fundamentally short-term thinkers. The amount of input that an LLM can handle at once is known as its context window, and even as new developments stretch this into the hundreds of thousands of tokens, models still struggle when asked to work across enormous codebases or long-running operational workflows. With larger inputs, LLMs’ decision-making degrades, they take shortcuts, and important details begin disappearing.
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