Coding Agent

Agent products are transitioning from concepts to real applications, with a significant surge in 2026. C-end users are declining while B-end and developer users are growing. Product forms are stabilizing, and iteration speed is accelerating.

智谱技术博客揭示了在大规模Coding Agent推理过程中遇到的"Scaling Pain"，包括乱码、复读和生僻字等异常现象，通过深入排查发现这些问题源于高负载下的推理状态管理不当。文章分享了投机采样作为异常检测指标的策略，以及修复KV Cache竞态和HiCache加载时序问题的具体方案，并提出了Prefill阶段的LayerSplit优化来缓解内存与带宽压力，最终显著提升了系统性能。

The author believes that current Coding Agent technology is not mature enough, and the development speed of models and applications does not keep up with demand.