Summary

This zhichai.net forum post presents a deep-dive interpretation of 'Learning Beyond Gradients,' a perspective on continual learning in which coding agents, rather than gradient-based optimization alone, take over the process of updating models over time. The post is delivered primarily through an embedded architectural diagram hosted on IPFS, illustrating how an agentic workflow can modify code, memory, tools, or environment as an alternative learning signal outside traditional weight updates. The article is relevant to researchers and engineers exploring continual learning, agentic systems, and self-improving software: it reframes learning as edits to an agent's surrounding scaffolding—code, prompts, and data—instead of parameter updates. Readers can view the original diagram via the linked IPFS resource to understand the proposed pipeline. This page provides the original post's title, translated summary, and direct link to the accompanying diagram.