Are Agent Harnesses the Boring Way to Continual Learning?
scaling01 · x · 2026-08-14
The ability of DeepSeek Harness (DSH) to allow Agents to dynamically generate and mount plugins at runtime has sparked discussion on whether Agent Harnesses are a "boring but effective" approach to Continual Learning.
Traditional continual learning attempts to make models learn new knowledge without forgetting old knowledge, often facing catastrophic forgetting. The prototype shown by DSH offers a new paradigm: instead of modifying model weights, the Agent temporarily writes code plugins at runtime to acquire new capabilities. Although these dynamically generated plugins currently exist only in memory and disappear on restart, this "build-on-demand" model might bypass the complex issues of weight updates.
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