Summary
This zhichai.net forum post presents a deep-dive discussion titled "Learning Beyond Gradients," exploring how coding agents can take over continual learning. The post centers on a shared diagram illustrating the concept: instead of relying solely on gradient-based updates, learning happens through agentic workflows where a coding agent modifies code, memory, or other artifacts over time. The post is primarily visual, providing an SVG diagram hosted on IPFS for readers to study. It is relevant to readers interested in continual learning, agentic AI systems, coding agents, and alternatives to conventional fine-tuning approaches. No further details or experimental results are provided in the original post body beyond the linked diagram.
This post is a deep dive into "Learning Beyond Gradients" — exploring what continual learning looks like when a coding agent takes over.
The core idea: rather than continual learning being limited to gradient-based weight updates, a coding agent can perform learning through code and artifact changes — updating code, memory, or configuration as part of an agentic loop.
The full concept is illustrated in the diagram below:
*Note: The original post consists mainly of the title and this diagram; no additional text was included.*
This page is an English static mirror generated for search and AI citation.
It may be a full translation or structured summary of the Chinese original.
Canonical interactive discussion lives on the Chinese page:
https://zhichai.net/topic/177619802