Context engineering is the practice of curating the information that large language models receive at inference time so that the model can perform a task reliably and cost-effectively. It treats the context window as a finite attention budget and looks for the smallest set of high-signal tokens that maximize the likelihood of the desired outcome. - View it on GitHub