Autogenesis: A Self-Evolving Agent Protocol

arXiv cs.AI / 4/17/2026

📰 NewsDeveloper Stack & InfrastructureModels & Research

Key Points

  • The paper introduces the Autogenesis Protocol (AGP) to improve how LLM agent systems manage cross-entity lifecycle, context, versioning, and safe evolution updates compared with existing protocols like A2A and MCP.
  • AGP separates concerns into two layers: RSPL, which models prompts, agents, tools, environments, and memory as protocol-registered resources with explicit state/lifecycle/versioned interfaces, and SEPL, which provides a closed-loop interface for proposing, evaluating, and committing improvements with auditable lineage and rollback.
  • Building on AGP, the authors propose the Autogenesis System (AGS), a self-evolving multi-agent system that dynamically instantiates, retrieves, and refines protocol-registered resources during execution.
  • Experiments on multiple long-horizon, tool-using benchmarks show consistent performance improvements over strong baselines, supporting the effectiveness of structured resource management and closed-loop self evolution.

Abstract

Recent advances in LLM based agent systems have shown promise in tackling complex, long horizon tasks. However, existing agent protocols (e.g., A2A and MCP) under specify cross entity lifecycle and context management, version tracking, and evolution safe update interfaces, which encourages monolithic compositions and brittle glue code. We introduce \textbf{\textsc{Autogenesis Protocol (AGP)}}, a self evolution protocol that decouples what evolves from how evolution occurs. Its Resource Substrate Protocol Layer (RSPL) models prompts, agents, tools, environments, and memory as protocol registered resources\footnote{Unless otherwise specified, resources refer to instances of the five RSPL entity types: \emph{prompt}, \emph{agent}, \emph{tool}, \emph{environment}, \emph{memory} with agent \emph{outputs}.} with explicit state, lifecycle, and versioned interfaces. Its Self Evolution Protocol Layer (SEPL) specifies a closed loop operator interface for proposing, assessing, and committing improvements with auditable lineage and rollback. Building on \textbf{\textsc{AGP}}, we present \textbf{\textsc{Autogenesis System (AGS)}}, a self-evolving multi-agent system that dynamically instantiates, retrieves, and refines protocol-registered resources during execution. We evaluate \textbf{\textsc{AGS}} on multiple challenging benchmarks that require long horizon planning and tool use across heterogeneous resources. The results demonstrate consistent improvements over strong baselines, supporting the effectiveness of agent resource management and closed loop self evolution.