Summary

This post from zhichai.net presents a deep-dive interpretation titled "Learning Beyond Gradients: When Coding Agents Take Over Continual Learning." The piece explores the idea that continual learning in AI systems may extend past traditional gradient-based fine-tuning, with coding agents playing a central role in updating and maintaining models over time. The original article is published with an accompanying architecture diagram hosted on IPFS, which is preserved in this English version. As the source post consists primarily of the title and diagram, this page provides a faithful English rendering of the original entry without additional speculation about its technical contents. Readers interested in continual learning, agentic workflows, and alternatives to gradient descent-based adaptation are encouraged to view the original post and its diagram on zhichai.net. Key topics: continual learning, gradient-based training, coding agents, and agent-driven model maintenance.