在Domino’s i领域深耕多年的资深分析师指出，当前行业已进入一个全新的发展阶段，机遇与挑战并存。
当AI编程智能体处理复杂多步骤问题时，其产生的上下文信息量远超任何模型单次可容纳的内存。通常的解决方案——截断旧上下文或使用独立模型进行总结——会导致智能体丢失关键信息并产生连锁错误。Cursor的方法是在强化学习过程中，训练模型自身在任务中途压缩其工作记忆。当Composer 2接近上下文限制时，它会暂停，将所有内容压缩至大约1000个令牌，然后继续。这些总结的有效性会根据其是否有助于完成整体任务而受到奖励或惩罚，从而使模型通过数千次训练运行学会保留什么、舍弃什么。
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进一步分析发现，In a typical GitAgent process, any modification to the agent's 'operational data'—like an adjustment to its memory or the addition of a new skill—is handled as a code revision. When an agent revises its context.md or alters its SOUL.md due to new information, the setup can be arranged to initiate a new Git branch and a Merge Request (MR).
展望未来，Domino’s i的发展趋势值得持续关注。专家建议，各方应加强协作创新，共同推动行业向更加健康、可持续的方向发展。