Agent Infrastructure on Eigenform Continuous Learning Tool Tipshttps://www.eigenform.ai/continuous-learning-tool-tips/tags/agent-infrastructure/Recent content in Agent Infrastructure on Eigenform Continuous Learning Tool TipsHugoen-USFri, 13 Nov 2026 11:00:00 +0800Decoupled Framework Design for Test-Time Learning Agentshttps://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/Fri, 13 Nov 2026 11:00:00 +0800https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/<figure class="article-image"> <picture> <source type="image/webp" srcset="https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/cover-decoupled-agent-framework-design_hu_9113158aab425508.webp 480w, https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/cover-decoupled-agent-framework-design_hu_c2f196e3bdc5ad4d.webp 800w, https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/cover-decoupled-agent-framework-design_hu_7fd4de6646363faf.webp 1200w" sizes="(min-width: 900px) 800px, 100vw"> <source type="image/webp" srcset="https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/cover-decoupled-agent-framework-design_hu_bccead2be73e2a74.webp 480w, https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/cover-decoupled-agent-framework-design_hu_b80eaad5b1e96c89.webp 800w, https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/cover-decoupled-agent-framework-design_hu_aed3db3c7fbea491.webp 1200w" sizes="(min-width: 900px) 800px, 100vw"> <img src="https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/cover-decoupled-agent-framework-design_hu_b80eaad5b1e96c89.webp" alt="Decoupled framework design for test-time learning agents as an etched parchment engraving: on the left, two different harness machines plug into one task contract socket; on the right, a glass partition lets a public scroll pass to the harness while a locked strongbox of secrets stays behind it" title="One task contract runs across different agent harnesses, while verification secrets never reach the harness" width="1672" height="941" loading="eager" fetchpriority="high" decoding="async" class="zoomable" data-full-url="https://www.eigenform.ai/continuous-learning-tool-tips/decoupled-agent-framework-design/cover-decoupled-agent-framework-design.webp"> </picture><figcaption>One task contract runs across different agent harnesses, while verification secrets never reach the harness</figcaption></figure><p><strong>TL;DR:</strong> Training language model agents across multi-container tasks often stalls because benchmark definitions, prompt formatting, tool schemas, and inference clients are tightly coupled inside monolithic runner scripts. Separating the domain contract (<code>TaskSpec</code>) from the turn-level execution loop (<code>HarnessSpec</code>), the inference wrapper stack (<code>Genner</code> and <code>Backend</code>), and the parallel slot scheduler (<code>Execution</code>) allows any task to run unchanged across in-process orchestrators or containerized third-party agents. This four-layer boundary preserves secret isolation during reward verification and produces uniform supervised fine-tuning (SFT) trajectories for iterative LoRA consolidation.</p>