π€ AI Summary
This work addresses the lack of effective governance and lifecycle management mechanisms for code artifacts generated by agents in multi-agent systems. It proposes HarnessMutation, a framework that models runtime evolution as a bounded and observable process over persistent operational memory. By integrating verifiable, traceable, evaluable, and rollback-capable mechanisms, HarnessMutation enables continuous self-adaptation within the cognitive loop. The approach combines an executable operational cognitive model with a governance-oriented orchestration system to support lifecycle-aware runtime evolution. This study establishes both a theoretical foundation and a practical pathway for adaptive agent infrastructures that balance flexibility with controllability.
π Abstract
Recent advances in agentic systems increasingly treat code as an executable operational substrate rather than as a disposable output artifact. Prior work such as \emph{Code as Agent Harness} frames validated agent-generated artifacts as runtime entities that can be created, executed, revised, persisted, and reused within long-running cognitive loops. However, the governance, lifecycle management, and operational evolution of such artifacts remain under-specified.
This paper proposes a framework for governed runtime evolution in multi-agent systems through executable operational cognition. We formalize agent-generated artifacts as persistent runtime capabilities that progressively become part of the operational substrate rather than transient intermediate outputs. Building on this perspective, we introduce \emph{HarnessMutation} as a governed mechanism for lifecycle-aware runtime adaptation operating under explicit validation, traceability, evaluation, and rollback constraints.
Rather than treating runtime adaptation as unrestricted self-modification, the proposed framework models evolution as a bounded and observable process over persistent operational memory. It further shows how these ideas can be operationalized over modern agent runtimes and governance-oriented orchestration systems, providing a conceptual foundation for adaptive infrastructures whose evolution remains explicit, auditable, and constrained.