Persistent agent execution refers to the ability to run AI agents continuously or intermittently over long periods—maintaining state, scheduling tasks, coordinating multiple agents, and recovering from failures. By mid‑2026, enterprises increasingly prioritize platforms that combine reliable runtimes, observability, governance, and reusable agent marketplaces so AI agents can manage end‑to‑end business processes rather than single prompts. This category spans developer‑first frameworks (LangChain) that provide SDKs, model interfaces, and deployment primitives; enterprise orchestration and governance suites (Kore.ai, IBM watsonx Assistant) for multi‑agent workflows, compliance, and observability; and no‑code/low‑code visual builders (MindStudio, Anakin.ai, Relevance AI, Yellow.ai) that accelerate design, testing, and scale. Web‑native developer platforms like Replit offer lightweight hosting and agent assistants for rapid iteration. Marketplaces and hosted runtimes (examples include OpenAI Ona and Arcade.dev) are making persistent runtime environments and curated agent “apps” more accessible. Key considerations for selecting a platform are state management, multi‑agent choreography, connectors to enterprise systems, monitoring and audit trails, security/compliance, and cost model for continuous execution. Trends driving adoption include demand for autonomous workflows in CX/EX, standardized agent frameworks for observability, and marketplaces that reduce integration effort. For enterprise use, combine a robust framework for development (LangChain or similar) with a platform that provides governance, scalable persistent runtimes, and prebuilt agents or apps from marketplaces to balance velocity, reliability, and control.